No full-text available
To read the full-text of this research,
you can request a copy directly from the author.
Water and nitrogen limitations in soybean grain production I. Model development
Abstract
A simple, phenomenological model was developed to describe the carbon, nitrogen, and water budgets of a soybean (Glycine max (L.) Merr) crop from emergence to maturity. Daily meteorological data input to the model were minimum temperature, maximum temperature, solar radiation, and precipitation. Leaves were grown to give a linear function of mean daily temperature. From the calculated leaf area index the daily intercepted solar radiation by the crop was determined. Daily carbon accumulation was calculated as a linear function of intercepted radiation. The daily nitrogen accumulation rate was calculated as a linear function of vegetative biomass. Leaf growth, carbon accumulation and symbiotic-nitrogen fixation rates were all made sensitive to the amount of soil water. Experimental data were collected to develop the empirical relationships between these three physiological processes and the amount of transpirable soil water. These data showed nitrogen fixation rates to be more sensitive to soil dehydration than either leaf growth or leaf gas exchange. Preliminary tests showed that model predictions compared favorably with field observations. An analysis of the model's behavior showed that crop yield was most sensitive to those variables influencing the interception of solar radiation and its conversion to biomass.
... Complex crop variables such as seed yield and seed composition are controlled by other variables, often called secondary traits, which are determined sequentially during the growing season (Sinclair, 1986). The understanding of the contribution of secondary traits to final yield potential has been proposed to design trait-based hybridization strategies (trait complementarity) for breeding purposes (Reynolds et al., 2011). ...
... Moreover, in a physiological framework, crop variables are defined by a sequence of processes starting from light interception through the development of LAI and the production of biomass followed by the partitioning of biomass into reproductive structures (seeds); and finally, the conversion of assimilates into seed components such as carbohydrates, protein and oil. A conceptual framework for the association of physiological processes with yield determination can be described as follows (Monteith, 1977;Sinclair, 1986): ...
... Physiological processes that determine soybean seed yield and their association to light interception has been demonstrated (Monteith, 1972;Sinclair, 1986). Soybean yield determination starts with the amount of intercepted photosynthetically active radiation (iPAR), which in turn depends on incident, transmitted, and reflected radiation, assuming that the radiation reflected by the soil is negligible (Monteith, 1972). ...
Prediction of soybean seed yield and seed composition at a plot scale before harvesting has potential uses in breeding programs for early-season selection and harvesting decisions. Reflectance information from hyperspectral bands have been mainly used for predicting yield and other crop variables. However, an analysis comparing the prediction accuracy among different crop variables such as LAI, biomass, seed yield and seed protein and oil, when using hyperspectral bands as predictors, is lacking. Our objective is to rank the prediction accuracy among different crop variables using hyperspectral bands captured at different timepoints during the growing season. Our hypothesis is based on a physiological framework where crop variables that are closely associated with light interception (i.e., LAI) would be best predicted by the hyperspectral signal (350 nm–2500 nm) than variables that involve more physiological processes (i.e., biomass, seed yield and seed protein and oil) for their determination. The dataset used for testing this hypothesis involved different genotypes, environments, and management practices. We used Partial Least Squares regression with cross-validation to test the association between the observed variables and the hyperspectral bands. Our results showed that LAI can be best predicted using reflectance information, and suggest that hyperspectral bands are necessary but not sufficient to improve the prediction of other crop variables such as biomass, seed yield, and seed composition traits.
... Field Crops Research 91 (2005) [273][274][275][276][277][278][279][280][281][282][283][284][285] van Laar, 1994). In some other crop models, seed yield accumulation is calculated as the product of biomass accumulation and harvest index (HI), and harvest index is assumed to increase linearly as a function of time after beginning seed growth with a constant rate (dHI/dt) (Sinclair, 1986). ...
... The strength of this approach lies in its simplicity, intrinsically combining the contribution of current and stored assimilate to seed yield and so removing the need for complex predictions of seed number and size in the prediction of seed yield (Chapman et al., 1993). Use of a constant dHI/dt has proved effective and robust in a number of crop simulation models including soybean (Sinclair, 1986), maize (Muchow et al., 1990), wheat (Amir and Sinclair, 1991), sunflower (Chapman et al., 1993), and chickpea (Soltani et al., 1999). ...
... The chickpea crop model of Soltani et al. (1999) was used in this study. This model is similar to the models of Sinclair (1986) and Hammer et al. (1995). The model is based on a daily time step and simulates crop growth and development as a function of temperature, solar radiation and water availability. ...
The linearity of harvest index (HI) increase has been used as a simple means to analyze and predict crop yield in experimental and simulation studies. It has been shown that this approach may introduce significant error in grain yield predictions when applied to diverse environments. This error has been ascribed to variability in the rate of linear increase in HI with time (dHI/dt). Data from two field experiments indicated in chickpea (Cicer arietinum L.) that dHI/dt varied among sowing dates. This variation was related to the length of pre-seed growth phase and vegetative growth (dry matter production) during this phase and could be described by the mean daily temperature from sowing to beginning seed growth. dHI/dt increased linearly with increase in the temperature up to 17 8C when it reached to its maximum value and remained constant. Simulation of these field experiments using a chickpea crop model including a constant dHI/dt resulted in yield over-prediction for some sowing dates. However, a modified HI-based approach greatly improved model predictions. In this approach, potential seed growth rate (SGR) is calculated using the linear HI concept, but actual SGR is limited to current biomass production and the remobilisation of dry matter accumulated in vegetative organs before the seed growth period. This modification well accounted for temperature and drought effects on HI and resulted in better yield predictions under conditions of major chickpea producing areas of Iran. Therefore, we recommend that the modification to be applied in the other HI-based models. #
... The CROPGRO model estimates the potential nitrogen fixation rate based on nodule biomass including the carbon cost for nodule activities (Boote et al., 2008). By contrast, the Sinclair model estimates the potential nitrogen fixation rate based simply on the linear relationship between nitrogen fixation and aboveground biomass (Sinclair, 1986). This linear relationship was confirmed by experimental results for soybean production in upland fields converted from paddy fields in Japan (Shiraiwa et al., 1994). ...
... The objective of the present study was to develop a soybean crop model that simulates crop growth and production in upland fields converted from paddy fields by incorporating nitrogen components of biological fixation and soil nitrogen mineralization. The soybean crop model reported by Sinclair (1986) and Sinclair et al. (2003), which estimated nitrogen fixation based on its linear relationship with aboveground biomass, was used as base model and the zero-order reaction kinetics model was introduced to estimate soil nitrogen mineralization (Nira & Hamaguchi, 2012). For validation of the model, we compared the model results to the experimental data of nodulating and non-nodulating soybeans cultivated in upland fields converted from paddy fields. ...
... The harvest index (HI) -the ratio of seed biomass to total plant biomass -is used to estimate seed growth in crop models because the HI linearly increases with time during the seed filling period (Brisson et al., 2003;Robertson et al., 2002;Sinclair, 1986). This linear increase has also been reported for Japanese soybean cultivars (Sameshima, 2000). ...
Crop models can help in identifying constraints to crop production and enhancing crop yield. Because one of the major constraints is the availability of nitrogen for seed production, evaluation of nitrogen accumulation is important for soybean crop models. In the present study, we developed a soybean crop model to evaluate biomass production and nitrogen accumulation of Japanese soybean cultivars grown in upland fields converted from paddy fields. The model simplified the effects of leaf nitrogen deficit on biomass production by reducing only the leaf area while maintaining leaf nitrogen concentration, and we introduced a zero-order reaction kinetics model to estimate soil nitrogen supply. The proposed model was observed to simulate the accumulation of aboveground biomass and nitrogen content in both nodulating and non-nodulating soybean cultivars until the mid-seed filling period. The model accounts for 94% of the observed variations in aboveground biomass and nitrogen content and for 69% of the observed variation in seed biomass. The normalized root mean square errors of aboveground biomass, nitrogen content, and seed biomass are 19.3%, 19.6%, and 20.2%, respectively. Because the model does not include the effects of soil water status on pod formation and nitrogen fixation, seed biomass was overestimated in some cases. However, our model quantified the effects of changes in the soil nitrogen supply and biological nitrogen fixation on soybean production and will be useful for identifying and eliminating production constraints in Japanese soybeans.
... The results of this investigation showed that the availability of P-Olsen did not generate a significant effect (p>0.05) on EUR. This confirms the conservative nature of EUR (Gallagher and Biscoe, 1978;Sinclair, 1986), even in a harvestable crop in vegetative stage. This is reinforced with other research, where similar EUR stability responses were found, facing the same variability factor (P) or other soil constraints (Valle et al., 2009, Salvagiotti andMiralles, 2008;Plénet et al., 2000b;Fletcher et al., 2008b andSandaña et al., 2012), although this work is the first report of its constancy in Daucus carota. ...
... Many crop models assume EUR as a constant (Sinclair, 1986), but other studies reported that it varies widely depending on plant phenology (Garcia et al., 1988 andArkebauer et al., 1994). In this regard, Lecoeur and Ney (2003) reported a change in EUR during the development of the Pisum sativum crop, and in particular a decrease was observed during the vegetative phase; and Werker and Jaggard (1998) found that sugar beet had a decrease in EUR at the end of the crop cycle, under rainfed conditions. ...
The adoption of more efficient management practices, such as recognizing the adequate level of P availability (Olsen) in the soil, can result in improved production efficiency in the carrot (Daucus carota L.) cropping system. Complementarily, knowing the behavior of radiation use efficiency (EUR) is relevant in the optimization of resources (P-fertilizer and radiation), due to the continuous concern for environmental impact and for the reduction of production costs. The objective of this work was to evaluate the EUR performance of two commercial carrot cultivars, across five levels of P-Olsen availability, under field conditions (13, 16, 19, 24, 28 ppm). The experiment was established at the Santa Rosa Experimental Station (39º47'S; 73º14'W), belonging to the Universidad Austral de Chile (UACh) located in the city of Valdivia in the Los Ríos Region, during the 2010-2011 growing season. EUR (g DM MJ-1) was calculated using photosynthetically active radiation (RIFA) and biomass (aerial and total). In this study, EUR of D. carota cultivars was not influenced by soil P-Olsen availability (p>0.05), but differences (p<0.01) were found in photosynthetically active radiation intercepted (RIFA) and specific leaf area.
... The use of crop development simulation models associated with probability analysis enables the characterization of data distribution of a given variable and production risks. Among the models that can be used to simulate soybean plant development are the models proposed by Sinclair (1986) and Setiyono et al. (2007). However, these models require specific information on cultivars or relative maturity groups that are not yet available for the most recent indeterminate growth cultivars in Brazil. ...
... The date of physiological maturity (R7) stage was simulated from the date of R5 stage occurrence by calculating the thermal time and adopting the base temperature of 10 °C and the accumulated thermal time of 554 °C day (Martorano et al., 2012). The date of harvest maturity (R8) was simulated by the model proposed by Sinclair (1986), without the water deficit response function in the algorithm and the plastochron values obtained by Streck et al. (2008). For using the Sinclair model (1986), the flux density of incident global solar radiation (Rg) was required to be estimated by means of the Ångström Prescott equation with adjusted monthly coefficients for Santa Maria (Buriol et al., 2012 ) and for Pelotas (Steinmetz and Assis, 1999). ...
The objective of this study was to determine the mean duration and the interannual variability of phenological subperiods and total soybean development cycle for 11 sowing dates in the humid subtropical climate conditions of the state of Rio Grande do Sul. Daily meteorological data were used from 1971 to 2017 obtained from the Pelotas agroclimatological station and from 1968 to 2017 from the main climatological station of Santa Maria. The soybean development simulation was performed considering three sets of cultivars of relative maturity groups between 5.9-6.8, 6.9-7.3 and 7.4-8.0, with intervals between the sowing dates of approximately 10 days, comprising September, 21 to December, 31. The data of phenological subperiods duration and total development cycle were subjected to the exploratory analysis BoxPlot, analysis of variance and mean comparison by the Scott-Knott test, with 5% of probability. The development cycle duration is greater in Pelotas than in Santa Maria. There was a decrease in soybean cycle duration from the first to the last sowing date for both locations. The R1-R5 subperiod duration is decreasing from October to December due to photoperiod reduction.
... Simple simulation models (SSM) are a group of crop models based on Sinclair's approach (Sinclair 1986;Soltani and Sinclair 2012;Sinclair et al. 2020) in crop modelling. The development and application of the models dates back to 1986 when a soybean model was developed (Sinclair 1986). ...
... Simple simulation models (SSM) are a group of crop models based on Sinclair's approach (Sinclair 1986;Soltani and Sinclair 2012;Sinclair et al. 2020) in crop modelling. The development and application of the models dates back to 1986 when a soybean model was developed (Sinclair 1986). The modelling framework was then improved and applied over the past 35 years to nearly all major grain crops including maize (Sinclair and Muchow 1995). ...
Process-based crop growth models have become indispensable tools for investigating the effects of genetic, management, and environmental factors on crop productivity. One source of uncertainty in crop model predictions is model parameterization, i.e. estimating the values of model input parameters, which is carried out very differently by crop modellers. One simple (SSM-iCrop) and one detailed (APSIM) maize (Zea mays L.) model were partially or fully parameterized using observed data from a 2-year field experiment conducted in 2016 and 2017 at the UFT (Universitäts-und Forschungszentrum Tulln, BOKU) in Austria. Model initialisation was identical for both models based on field measurements. Partial parameteriza-tion (ParLevel_1) was first performed by estimating only those parameters related to crop phenology. Full parameterization (ParLevel_2) was then conducted by estimating parameters related to phenology plus those affecting dry mass production and partitioning, nitrogen uptake, and grain yield formation. With ParLevel_1, both models failed to provide accurate estimation of LAI, dry mass accumulation, nitrogen uptake and grain yield, but the performance of APSIM was generally better than SSM-iCrop. Full parameterization greatly improved the performance of both crop models, but it was more effective for the simple model, so that SSM-iCrop was equally well or even better compared to APSIM. It was concluded that full parameteri-zation is indispensable for improving the accuracy of crop model predictions regardless whether they are simple or detailed. Simple models seem to be more vulnerable to incomplete parameterization, but they better respond to full parameterization. This needs confirmation by further research.
... These models are comprised of a singular collection of subroutines and are parameterized with coefficients that are externally sourced to the code. Nevertheless, it has been recognized that this particular approach, while enhancing the functionality of the model for a variety of species, may result in a trade-off in terms of physiological rigor and predictive capability [5] . ...
... The field pea module in APSIM assumes that N 2 fixation only occurs when soil mineral N supply is inadequate to meet plant demand (Chen et al., 2016). Therefore, when soils that have high mineralisation rates (and nitrate concentration in the soil solution), fixation ceases (Sinclair, 1986;Chen et al., 2016). This reflects the observation that some species preferentially accumulate N from the soil rather than rhizobia based on the assumption that N 2 fixation costs more energy to the plant (Herridge et al., 1984). ...
... The soybean model within APSIM (Robertson and Carberry, 1998) is later in its origin and has been widely evaluated against Midwestern USA soybean data. The SSM model was designed to represent soybean plant-soil processes in a simplified manner (Sinclair, 1986) and was previously evaluated for simulation of plant C and N dynamics for a limited number of sites in the USA. Recently, the SSM model has been used to simulate soybean in Iran (Nehbandani et al., 2021(Nehbandani et al., , 2020). ...
• First soybean multi-model evaluation for simulation of in-season growth dynamics.
• Evidence of high variability in simulated leaf area, reproductive growth, and partitioning.
• Opportunities to improve model processes to resemble soybean reproductive growth.
• Description of processes that can benefit from further model improvement.
• Recommendations for collection of key experimental data for model evaluation.
... Some examples include sowing date in the Middle East in wheat (Schoppach et al. 2017), plant density in peanut in Sub-Saharan Africa (Vadez et al. 2017), irrigation management in bean in southern France (Marrou et al. 2014), and blue water resource management at country level in Iran (Soltani et al. 2020b). The basic form of SSM was originally published in 1986 (Sinclair 1986), and SSM has now been applied over the past 30 years to simulations of nearly all major crop species (Soltani and Sinclair 2012;Sinclair et al. 2020;Soltani et al. 2020a). ...
Aerobic rice cultivation has been proposed as a water-saving option. Regional assessments are necessary to quantify its importance as such an option because aerobic rice exhibits varying effects on crop yield and irrigation water, depending on location, management, and cultivar. Currently, there is a lack of such regional assessments. In this study, we evaluated the potential of aerobic-direct-seeded rice cultivation as an alternative to the traditional flooded-transplanting system (FTS) in Golestan province, Iran. Using a bottom-up approach, rice production zones and buffers were identified, and the SSM-iCrop2 model was employed to simulate crop growth and water use for FTS and two aerobic systems in the entire province. The results revealed significant reductions in irrigation water volume for the aerobic systems, ranging from 22 to 50% compared to FTS. However, there was a trade-off in terms of crop yield, with reductions ranging from 9 to 31% in the aerobic systems. The variation was due to genotype × environment × management interactions on the performance of aerobic cultivation and emphasized the value of crop models in assessing and understanding these interactions. However, at the regional scale (Golestan province), it was found that transitioning from FTS to aerobic systems can effectively mitigate water over-withdrawal in the region, potentially saving 272–362 million m3 of water annually. This amount represents 70–90% of the current goal of reducing water withdrawal in the province. This study provides valuable insights into the water-saving potential of aerobic rice cultivation, with implications for sustainable water resource management in rice-producing regions of Iran.
... Excessive N fertilizer applications inhibit soybean growth. Soybean leaf photosynthesis [38,39] and seed yield [21,40] are likely to be inhibited under high FR conditions. Similar effects on root growth parameters have been identified. ...
Root traits (RTs) of soybean (Glycine max (L.) Merr.) that can be improved through long-term genetic breeding have been identified. However, whether resistance to environmental stresses can be enhanced and more detailed information on the relationships between RTs and seed yield remain unclear. Here, we used a pot-culture experiment with 13 varieties released in different years to investigate the changes in some RTs resulting from genetic breeding-based improvements. We determined whether RTs in different varieties respond to increasing fertilization rates (FRs) differently and quantified the contributions of RTs to seed yield variation among varieties. Decades of genetic selection have resulted in significant desired changes in RTs as well as the seed yield (per plant) under different FR conditions. The RT values of soybean receiving the 1.1 g pot−1 FR treatment increased significantly by 8.20%, 8.75% and 8.68%, whereas those receiving the 2.2 g pot−1 FR treatment decreased by 14.31%, 13.28% and 5.52%, for old, middle and new variety groups, respectively, compared with the no fertilizer treatment, indicating that the tolerance of root to fertilizer stress was enhanced. The results of artificial interference analysis showed that root length at the full bloom stage, root-to-shoot ratio at the full seed stage and root activity at the beginning maturity stage were the most important factors affecting seed yield, contributing approximately 54%, 58% and 59%, respectively, to seed yield variation. Overall, our work provides a theoretical basis for future breeding, suggesting a direct selection of soybean RTs to improve soybean yield.
... Many different assumptions have been used in modelling N fixation in plants, some estimating N-fixation rate from plant N demand/uptake (Cabelguenne et al., 1999;Fitton et al., 2019) or the mass of different plant compartments, that is root, nodule, or aboveground biomass (Sinclair, 1986;Thornley et al., 1995;Wu & McGechan, 1999;Boote et al., 2002;Robertson et al., 2002;Soussana et al., 2002). Alternatively, FBA models forego such assumptions by directly simulating fluxes through the complete metabolic network built from genome annotations. ...
Nitrogen‐fixing symbioses allow legumes to thrive in nitrogen‐poor soils at the cost of diverting some photoassimilate to their microsymbionts. Effort is being made to bioengineer nitrogen fixation into nonleguminous crops. This requires a quantitative understanding of its energetic costs and the links between metabolic variations and symbiotic efficiency.
A whole‐plant metabolic model for soybean (Glycine max) with its associated microsymbiont Bradyrhizobium diazoefficiens was developed and applied to predict the cost–benefit of nitrogen fixation with varying soil nitrogen availability.
The model predicted a nitrogen‐fixation cost of c. 4.13 g C g⁻¹ N, which when implemented into a crop scale model, translated to a grain yield reduction of 27% compared with a non‐nodulating plant receiving its nitrogen from the soil. Considering the lower nitrogen content of cereals, the yield cost to a hypothetical N‐fixing cereal is predicted to be less than half that of soybean. Soybean growth was predicted to be c. 5% greater when the nodule nitrogen export products were amides versus ureides.
This is the first metabolic reconstruction in a tropical crop species that simulates the entire plant and nodule metabolism. Going forward, this model will serve as a tool to investigate carbon use efficiency and key mechanisms within N‐fixing symbiosis in a tropical species forming determinate nodules.
... The aboveground sink strength is the sum of the potential growth of leaves and stems which set the respective carbohydrate allocation rates and are a function of tiller density, elongation rates and respective morphological parameters. Elongation rates are affected by water stress described by a logistic function (Sinclair, 1986;Richter et al., 2006) and are a linear function of average daily temperature (Hazard et al., 2006;Hoglind et al., 2001). The ability of LINGRA to simulate the roots, rhizome, dead leaves and litter along with the aboveground biomass makes it suitable to simulate the biomass for bioenergy and belowground biomass input for C storage in to the soil. ...
Reductions in CO2 emissions are essential to support the UK in achieving its net zero policy objective by around mid-century. Both changing climate and land use change (LUC) offer an opportunity to deploy suitable bioenergy crops strategically to enhance energy production and C sequestration to help deliver net zero through capturing atmospheric CO2. Against this background, we applied process-based models to evaluate the extent of net primary productivity (NPP) losses/gains associated with perennial bioenergy crops and to assess their C sequestration potential under changing climate in the upper River Taw observatory catchment in southwest England. In so doing, we also determined whether LUC from permanent grassland to perennial bioenergy crops, considered in this study, can increase the production and C sequestration potential in the study area. The results show that a warming climate positively impacts the production of all crops considered (permanent grassland, Miscanthus and two cultivars of short rotation coppice (SRC) willow). Overall, Miscanthus provides higher aboveground biomass for energy compared to willow and grassland whereas the broadleaf willow cultivar 'Endurance' is best suited, among all crops considered, for C sequestration in this environment, and more so in the changing climate. In warmer lowlands, LUC from permanent grassland to Miscanthus and in cooler uplands from permanent grassland to 'Endurance', enhances NPP. Colder areas are predicted to benefit more from changing climate in terms of above and belowground biomass for both Miscanthus and willow. The study shows that above LUC can help augment non-fossil energy production and increase C sequestration potential if C losses from land conversion do not exceed the benefits from LUC. In the wake of a changing climate, aboveground biomass for bioenergy and belowground biomass to enhance carbon sequestration can be managed by the careful selection of bioenergy crops and targeted deployment within certain climatic zones.
... Over the years, models have advanced to account for more complex interactions within production systems, including multi-paddock simulations and enterprise diversity within farms Ho et al., 2014;Whish et al., 2015;Harrison et al., 2019;Christie et al., 2020). These include the dynamic simulation of the soil water and nutrient availability (Freebairn et al., 1989;Littleboy et al., 1992;Liu et al., 2020a), as well as water and nutrient balance (Jones et al., 1974;Probert et al., 1998;Foster et al., 2017) for the growth and development of crops under varying environmental conditions (de Wit, 1953;Sinclair, 1986;Carberry et al., 1993;Schepen et al., 2020). These modelling approaches are commonly regarded as dynamic systems or process-based models, which have been demonstrated as useful to understand crop growth dynamics (Ewert et al., 2015) and while designed to predict crop responses in a given production situation (Manivasagam and Rozenstein, 2020), they are often contextualised by genotype by environment by management interactions (Phelan et al., 2018;Ibrahim et al., 2019;Ara et al., 2021). ...
Impacts of pest and diseases on crop productivity comprise one of the greatest existential threats to food security in the 21st century. Despite this, crop models have historically adopted an abiotic lens. Here, we reviewed previous methods aimed at modelling effects of pests on crops and revealed a dearth of integrated approaches that account for pest lifecycles. The few integrated models that do exist tend to be empirical constructs that discount yield, with models of underpinning pest dynamics being extremely rare. Interaction between pests and crops has tended towards pest-induced reductions in plant biomass, leaf area, light interception and/or photosynthetic rates of infected plants, rather than biological modelling of the pest lifecycle per se. The use of process-based models that couple the pest-host interactions and capture the resource competition between the two are more suited to understanding the complexity of the farming system. Given that management interventions – such as crop rotation, intercropping, sowing time, nitrogen fertilisation, planting density and insecticide or fungicide use – underpin host colonisation success, we solicit advances in the modelling of management decisions to mitigate and manage pest and disease populations. Such information will become ever more crucial as global temperatures and extreme weather events increase in frequency and disease infestation proliferates. Harnessing this integrated weather-pest-crop-management continuum within farming systems models will improve farm management decisions. We conceptualise a framework using the lifecycle of blackleg disease (Leptosphaeria maculans) as an example; however, our approach could be generically adapted to other crop-pest interactions.
... Fitting crop growth models [45][46][47][48] is another strategy to associate LAI dynamics with yield formation. These models include the effects of self-destruction and water deficit on the LAI, suggesting that the causes can be estimated based on LAI dynamics. ...
Soybean yield largely varies spatially and yearly in farmer fields. Appropriate growth diagnosis is recommended to stabilize the yield. Leaf area index (LAI) is a representative diagnostic item, but an evaluation method of LAI dynamics with growth has not been established. In this study, we utilized a growth function consisting of an exponential function and a power math function. Parameters were derived from the growth function to be analyzed with yield variability. The LAI was measured weekly by a plant canopy analyzer in farmer fields for 4 years. The dynamics were parameterized by fitting the growth function. The relationship between the parameters of LAI dynamics and soybean yield was analyzed. The growth function was well fitted to measured LAI at R2 = 0.82~0.90 and RMSE = 0.54~0.69 m2 m−2. The parameters of the growth function, such as maximum LAI (LAImax) and cumulative temperature at maximum LAI (TLAImax), quantified the spatial and yearly differences in LAI dynamics, partly explaining those in the yield. The growth function utilized in this study is considered a robust method to quantify LAI dynamics and to diagnose soybean production. The quantification of LAI dynamics may help to develop crop growth monitoring with UAVs (Unmanned Aerial Vehicles) remote sensing as a new diagnostic tool.
... Since defoliation affects canopy reflectance, satellite images are promising for wide-area evaluations (Hongo et al., 2022;Manago et al., 2020), although an increase in sensitivity may be necessary. To assess the damage of RCR to soybean yield, combining the present type of assessment with crop growth models (Jones et al., 2003;Sinclair, 1986) would be promising. ...
Red crown rot (RCR) is a soil-borne disease that damages soybean growth and decreases yield. Infected plants show earlier defoliation and pencil-like roots, sometimes resulting in mortality. This disease became common relatively recently, and information about its field-scale appearance is insufficient. Insufficient data is a major constraint when planning countermeasures. In this study, unmanned aerial vehicle (UAV)-acquired images were used to visualize the spatial and time series variation in the area damaged by RCR in the same farmer fields in 2018 and 2020. Field investigation showed that RCR severely damaged soybean production. The reductions of yield were estimated at 17.5% and 12.7% in 2018 and 2020, respectively. The visualized damage clarified the difference in the increasing rate and patterns of RCR between the 2 years. In 2018, the damaged area expanded along the planting row to the whole field, but in 2020, the expansion along the planting row was not great, and half of the fields remained sparsely damage. This difference implies that various factors are associated with damage occurrence and pathogen distribution. The method applied in this study is effective in visualizing RCR damage, but further improvement is required in the evaluation of intermediate damage and the generalization of the evaluation procedure.
... In such studies, therefore, a wide range of plant species must be simulated, which is challenging for most simulation models. Simple Simulation Models (SSM) are a group of crop models that date back to 1986 when a simple simulation model was developed for soybean (Sinclair, 1986). The framework has been improved and applied over the past 30 years to nearly all major grain crops including maize (Sinclair and Muchow, 1995), sorghum (Sinclair et al., 1997), wheat (Sinclair and Amir, 1992;Soltani et al., 2013), barley (Wahbi and Sinclair, 2005), peanut (Hammer et al., 1995), and chickpea (Soltani and Sinclair, 2011). ...
Crop models are essential in undertaking large scale estimation of crop production of diverse crop species, especially in assessing food availability and climate change impacts. In this study, an existing model (SSM, Simple Simulation Models) was adapted to simulate a large number of plant species including orchard species and perennial forages. Simplification of some methods employed in the original model was necessary to deal with limited data availability for some of the plant species to be simulated. The model requires limited, readily available input information. The simulations account for plant phenology, leaf area development and senes-cence, dry matter accumulation, yield formation, and soil water balance in a daily time step. Parameterization of the model for new crops/cultivars is easy and straightforward. The resultant model (SSM-iCrop2) was para-meterized and tested for more than 30 crop species of Iran using numerous field experiments. Tests showed the model was robust in the predictions of crop yield and water use. Root mean square of error as percentage of observed mean for yield was 18% for grain field crops, 14% for non-grain crops 14% for vegetables and 28% for fruit trees.
... harvest) is crucial where the vine growing cycle is exposed to the impact of climate change (Biasi et al., 2019;Hannah et al., 2013;Leolini et al., 2018b;Moriondo et al., 2011Moriondo et al., , 2013Wolkovich et al., 2018). In this context, process-based models are the preferred tools for assessing the effects of the environment on plant development and growth since they describe potential biomass accumulation as limited by nutrient or water stress (Bindi et al., 1997a(Bindi et al., , 1997bLeolini et al., 2018a;Moriondo et al., 2007Moriondo et al., , 2019Sinclair, 1986). However, crop growth models usually require many inputs to define local environmental conditions, such as weather, soil and management practices, and for monitoring the ongoing growing season, so limiting their application to the plot scale where this information is generally fully available. ...
Grapevine simulation models are mostly used to estimate plant development, growth and yield at plot scale. However, the spatial variability of pedologic and micro-climatic conditions can influence vine growth, leading to a sub-field heterogeneity in plant vigor and final yield that may be better estimated through the assimilation of high spatial resolution data in crop models. In this study, the spatial variability of grapevine intercepted radiation at fruit-set was used as input for a grapevine simulation model to estimate the variability in biomass accumulation and yield in two Tuscan vineyards (Sites A and B). In Site A, the model, forced with intercepted radiation data as derived from the leaf area index (LAI), measured at canopy level in three main vigor areas of the vineyard, provided a satisfactory simulation of the final pruning weight (r ² = 0.61; RMSE = 19.86 dry matter g m ⁻² ). In Site B, Normalized Difference Vegetation Index (NDVI) from Sentinel-2A images was firstly re-scaled to account for canopy fraction cover over the study areas and then used as a proxy for grapevine intercepted radiation for each single pixel. These data were used to drive the grapevine simulation model accounting for spatial variability of plant vigor to reproduce yield variability at pixel scale (r ² = 0.47; RMSE = 75.52 dry matter g m ⁻² ). This study represents the first step towards the realization of a decision tool supporting winegrowers in the selection of the most appropriate agronomic practices for reducing the vine vigor and yield variability at sub-field level.
... This framework proposes that economic yield depends upon the amount of RAD that the crop actually absorbs (ARAD) or intercepts (IRAD) during the growing season, its conversion into crop biomass, which is commonly referred to as radiation use efficiency (RUE), and its partitioning into harvestable organs (harvest index) (Kiniry et al., 1989;Monteith et al., 1977;Sinclair and Muchow, 1999). The RUE, estimated based on ARAD (ARUE) or IRAD (IRUE) depending upon the study, has been used as a parameter for estimating crop productivity using remote sensing (Garbulsky et al., 2011), simple empirical models (Monteith, 1972), and process-based simulation models (Jones and Kiniry, 1986;Sinclair, 1986;Chapman et al., 1993;Villalobos et al., 1996). Despite the intrinsic empiricism of the RUE concept, which integrates multiple processes and scales, it does provide a useful framework to evaluate hypotheses related to crop traits such as leaf area, photosynthesis, and biomass partitioning (Reynolds et al., 2000;Koester et al., 2014;Chen et al., 2019;Araus et al., 2021). ...
Ontogenic changes in soybean radiation-use efficiency (RUE) have been attributed to variation in specific leaf nitrogen (SLN) based only on data collected during seed filling. We evaluated this hypothesis using data on leaf area, absorbed radiation (ARAD), aboveground dry matter (ADM), and plant nitrogen (N) concentration collected during the entire crop season from seven field experiments conducted in a stress-free environment. Each experiment included a full N treatment that received ample N fertilizer and a zero N treatment that relied on N fixation and soil N mineralization. We estimated RUE based on changes in ADM between sampling times and associated ARAD, accounting for changes in biomass composition. The RUE and SLN exhibited different seasonal patterns: a bell-shaped pattern with a peak around the beginning of seed filling, and a convex pattern followed by an abrupt decline during late seed filling, respectively. Changes in SLN explained the decline in RUE during seed filling but failed to predict changes in RUE in earlier stages and underestimated the maximum RUE observed during pod setting. Comparison between observed and simulated RUE using a process-based crop simulation model revealed similar discrepancies. The decoupling between RUE and SLN during early crop stages suggests that leaf N is above that needed to maximize crop growth but may play a role in storing N that can be used in later reproductive stages to meet the large seed N demand associated with high-yielding crops.
... Assuming that plant growth is influenced by the ratio of ATSW to TTSW in the layer explored by plant roots (Sinclair et al., 1998) we used this ratio, called the fraction of transpirable soil water, FTSW (%, Eq. 10), to rescale potential RUE to its actual value according to the general equation of Sinclair (1986) and Bindi et al. (2005) (Eq. 11): ...
This article presents the structure and results of a simplified model (VISTOCK) for simulating grass growth and water dynamics of grassland systems. The model, based on a process-based approach coupled with proximal (SKR 1800 2-Channel Light Sensor) and remote (Sentinel-2) NDVI-derived data for estimating LAI, simulates aboveground biomass (AGB), net primary production (NPP), evapotranspiration (ET), and the fraction of transpirable water in soil (FTSW). VISTOCK simulated a grassland system with few meteorological data (i.e., minimum and maximum daily temperatures, precipitation, global solar radiation), considering limitations to vegetation growth due to thermal and water stresses. It was calibrated for a natural alpine grassland in Italy (site T) during the most contrasting meteorological seasons of the dataset (2012, 2017, and 2018). It was then evaluated for the remaining years at site T (2013, 2014, 2015, and 2016) and for other two sites in Italy (sites B1, B2 and M) with different soil and climate conditions and diverse management strategies (2020 and 2021). VISTOCK accurately predicted AGB during the growing season (RMSE = 445, 240, 219, 365 kg DM ha⁻¹ for T, M, B1, and B2, respectively) as well as for NPP, ET, and FSTW at site T. Simulation results suggest the ability of the model to simulate grassland in diverse environments with few inputs and parameters to be calibrated. The model’s simplified structure, combined with easy-to obtain input data and easy applicability, encourages its wider use for out- and/or upscaling and decision making.
... ET c was calculated from emergence as a product of Penman-Monteith reference evapotranspiration (ET o ) for short crops for Gatton, accessed through the SILO LongPaddock database (Anon, 2021) and the estimated crop coefficient (k c ) for green gram and cowpea, which ranged from 0.15 in the beginning of the growing season to 0.64 before flowering and 1.05 mid-season, relative to canopy development (Allen et al., 1998). In both experiments, water available to the crop was greater than the water demand, and the fraction of transpirable soil water (FTSW) in the profile was greater than 0.25 throughout the crop cycles (Supplementary Figure 1), indicating no limitation on transpiration (Sinclair, 1986). ...
A comprehensive understanding of key drivers of grain yield is essential to identify opportunities to improve productivity in mungbean (Vigna radiata (L.) Wilczek). The objective of this study was to assess and quantify physiological factors underpinning yield of mungbean grown in non-water-limiting conditions. Two field experiments, employing three genotypes (Jade-AU, Opal-AU and Satin II) and four canopy density treatments were conducted in the summer growing season (Jan-Mar) of 2019 and 2020 at Gatton campus, The University of Queensland, Australia. Crop leaf area dynamics, radiation interception, extinction coefficient (k), radiation use efficiency (RUE), total dry matter (TDM) (above ground dry matter) and grain yield (GY) were measured. Leaf area index (LAI), influenced by the canopy density treatments, was the key driver of differences in radiation interception. The variation in intercepted radiation resulted in differences in TDM and GY across canopy density treatments. Genotypes did not differ significantly and partitioned more than 90% of TDM to pod development. The radiation extinction coefficient, k, was stable and estimated to be 0.68, while average RUE was calculated as 1.3 g MJ⁻¹. Variations in GY were strongly associated with grain number, which was related to intercepted radiation per unit of accumulated temperature around flowering. Using this quantification of the physiology of crop growth and yield in mungbean to form a simple crop model, simulations suggested that median potential yields of 1.88–2.48 tonnes ha⁻¹ were possible in NE Australian production environments, with greater yield associated with spring sowing. Understanding the physiological basis of the very low RUE in mungbean was considered a key avenue to improve potential yield. This study has provided a quantitative framework for potential yield that will enable more comprehensive modelling of crop adaptation in mungbean.
... In such studies, therefore, a wide range of plant species must be simulated, which is challenging for most simulation models. Simple Simulation Models (SSM) are a group of crop models that date back to 1986 when a simple simulation model was developed for soybean (Sinclair, 1986). The framework has been improved and applied over the past 30 years to nearly all major grain crops including maize (Sinclair and Muchow, 1995), sorghum (Sinclair et al., 1997), wheat (Sinclair and Amir, 1992;Soltani et al., 2013), barley (Wahbi and Sinclair, 2005), peanut (Hammer et al., 1995), and chickpea (Soltani and Sinclair, 2011). ...
Crop models are essential in undertaking large scale estimation of crop production of diverse crop species, especially in assessing food availability and climate change impacts. In this study, an existing model (SSM, Simple Simulation Models) was adapted to simulate a large number of plant species including orchard species and perennial forages. Simplification of some methods employed in the original model was necessary to deal with limited data availability for some of the plant species to be simulated. The model requires limited, readily available input information. The simulations account for plant phenology, leaf area development and senes-cence, dry matter accumulation, yield formation, and soil water balance in a daily time step. Parameterization of the model for new crops/cultivars is easy and straightforward. The resultant model (SSM-iCrop2) was para-meterized and tested for more than 30 crop species of Iran using numerous field experiments. Tests showed the model was robust in the predictions of crop yield and water use. Root mean square of error as percentage of observed mean for yield was 18% for grain field crops, 14% for non-grain crops 14% for vegetables and 28% for fruit trees.
... Studies of trends in LAI can provide technical support for simulations of dynamic changes in grape biomass and yields. There have been several techniques to predict LAI using crop simulation models [1][2][3] and generic crop models [4][5][6][7]. ...
The Leaf Area Index (LAI) strongly influences crop biomass production and yields. The variation characteristic of LAI and the development of crop growth models can provide a theoretical basis for predicting crops’ water consumption, fruit quality and yields. This paper analyzes the relationship between measurements of aboveground grape biomass and trends in LAI and dry biomass production in grapes grown in the Turpan area. The LAI changes in grapes were estimated using the modified logistic model, the modified Gaussian model, the log-normal model, the cubic polynomial model, and the Gaussian model. Universal models of LAI were established in which the applied irrigation quota was applied to calculate the maximum LAI. The relationship between the irrigation quota and biomass production, yields, and the harvest index was investigated. The developed models could accurately predict the LAI of grapevines grown in an extremely arid area. However, the Gaussian and cubic polynomial models produced less accurate results than the other models tested. The Michaelis–Menten model analyzed the relationship between biomass and LAI, providing a numerical method for predicting dynamic changes in grapevine LAI. Moreover, the crop biomass increased linearly with the irrigation quota for quotas between 6375 and 13,200 m3/hm. This made it possible to describe the grape yield and harvest index with a quadratic polynomial function, which increases during the early stages of the growing season and then decreases. The analyses of the relationship between yield and harvest index provide important theoretical insights that can be used to improve water use efficiency in grape cultivation and to identify optimal irrigation quotas.
... , or process-based simulation models (Chapman et al., 1993;76 Jones and Kiniry, 1986; Sinclair, 1986;Villalobos et al., 1996). The first estimates of RUE for CC-BY-NC-ND 4.0 International license available under a (which was not certified by peer review) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. ...
Ontogenic changes in soybean radiation-use efficiency (RUE) have been attributed to variation in specific leaf nitrogen (SLN) based only on data collected during seed filling. We evaluated this hypothesis using data on leaf area, absorbed photosynthetically active radiation (APAR), aboveground dry matter (ADM), and plant nitrogen (N) concentration collected during the entire crop season from seven field experiments conducted in a stress-free environment. Each experiment included a full N treatment that received ample N fertilizer and a zero N treatment that relied on N fixation and soil N mineralization. We estimated RUE based on changes in ADM between sampling times and associated APAR, accounting for changes in biomass composition. The SLN and RUE exhibited different seasonal patterns: a bell-shaped pattern with a peak around the beginning of seed filling, and a convex pattern followed by an abrupt decline during late seed filling, respectively. The level of N supply influenced SLN more than RUE via changes in leaf N concentration, with small changes in specific leaf weight. Changes in SLN explained the decline in RUE during seed filling but failed to predict changes in RUE in earlier stages. A simple approach based on phenological stages may give more realistic estimates of RUE before seed filling, improving crop growth and yield prediction via crop models and remote sensing.
Highlight
Changes in radiation-use efficiency during soybean vegetative and early reproductive stages are not related to specific leaf nitrogen.
... The SSM model appears to meet the above-mentioned criteria for development and geospatial application of decision support tools for improving crop management. The development of the SSM dates back to 1986, when a soybean model was published (Sinclair, 1986). The SSM modelling framework was then improved and applied over the past 35 years to nearly all major grain crops including maize (Sinclair and Muchow, 1995; and wheat (Soltani et al., 2013;Soltani and Sinclair, 2015). ...
Process-based crop models are essential tools for representing the fundamental interactions between the cropping environment (weather, soil, and management) and plant development, growth, resource use, and yield formation. Due to these capabilities, crop models are considered as an integral component of smart farming tools for evaluating and improving crop management at field, farm, and regional scales. However, prior to application of a crop model in geospatial decision support tools, its robustness should be established by comparing model predictions with observations from the target cropping environment. The objective of this study was to assess the performance of the Simple Simulation Model (SSM-iCrop) for predicting growth and nitrogen (N) dynamics of winter wheat (Triticum aestivum) cultivars in a temperate environment. Detailed plant and soil data were collected from three field experiments conducted with four widely-grown cultivars under four N application rates in Austria. Variation in N fertilisation and differences in soil properties and weather conditions in the three field experiments generated a wide range of observed crop total dry mass (585–2034 g m⁻²), N uptake (5–32 g N m⁻²), and grain yield (211–898 g m⁻²). The SSM-iCrop model required parameterisation of a relatively small number of plant input parameters. As these parameters could be directly calculated from the experimental data, except for two phenology-related coefficients, there was no need for calibrating the model. In initial simulations, SSM-iCrop was not able to predict the response of leaf area index (LAI) to decreasing N supply. Introducing an additional parameter defining the minimum stem N concentration from emergence to begin grain growth improved the model performance substantially. The simulated time-course of crop attributes through the growing season showed good overall correspondence with observed data. Across the three field experiments, the model performed well in simulating above-ground dry mass (CV=5.9, RMSE=115.6 g N m⁻²), grain yield (CV=1.9, RMSE=60.5 g N m⁻²), total crop N uptake (CV=4.5, RMSE=1.9 g N m⁻²), and grain N content (CV=1.1; RMSE=2.2 g N m⁻²). Overall, The results of this study confirmed the robustness of SSM-iCrop for predicting wheat development, growth, N dynamics, and yield in the target cropping environments. The relatively simple structure and high degree of transparency make the SSM-iCrop suitable for integration in smart farming tools for improving tactical decision making in crop production. This study also highlights the essential role of high-quality detailed experimental data for adequate parameterisation and evaluation of crop models..
... Soybean is sensitive to soil moisture, 44 and has different water requirements during each growth period. 45 A timely and sufficient supply of water during the critical period of soybean demand is therefore an important measure to ensure a high soybean yield. ...
BACKGROUND
Although climate change and agricultural practices have non‐negligible impacts on crop yields, their quantitative contributions to soybean yields remain unclear. First‐order difference multiple regression was used to determine the respective contributions of climate change and agricultural practice to changes in soybean yields at station level from 1981 to 2010 in northeast China.
RESULTS
From 1981 to 2010, the soybean yields at 87% of the stations were increasing with an average 41.18 kg ha year⁻¹ change trend in northeast China. The individual impacts of climate change and agricultural practice on soybean yield were −0.33% to 0.58% year⁻¹ and −3.3% to 7.89% year⁻¹, respectively. The sensitivity of the soybean yield to climatic factors was related to latitude, and yields at high‐latitude stations were positively correlated with temperature but negatively correlated with accumulated sunshine hours. Climate change contributed −24% to 38% to the trend in soybean yield, and the temperature had the greatest effect of all the climatic factors.
CONCLUSION
The contribution of agricultural practices was greater than that of climate change, counteracting the adverse effects of climate change and even affecting the direction of soybean yield changes. In adaptive decision making, priority should be given to management measures that have less impact on the environment, such as breeding new varieties adapted to specific latitudes, thus promoting the sustainable production of soybeans. © 2021 Society of Chemical Industry.
... The SSM model was originally developed by Sinclair (1986) and updated and fully described by Soltani and Sinclair (2012).The faba bean version of the model (SSM-fababean) was developed, parameterized, and tested for robustness by Marrou et al. (2021). The robustness tests were based on 30 experimental observations collected from a total of eight sites in Morocco, Tunisia, Lebanon, and Syria. ...
Faba bean (Vicia faba L.) is a useful grain legume for production in Mediterranean climates due to its consumption as food for humans and feed for animals, and its ability to symbiotically fix atmospheric nitrogen. Currently, in Morocco a substantial fraction of faba bean is sown under a rainfed management scheme in which the crop is sown after about a 15-day delay following the first rains after the dry season. The 15-day delay allows weed seeds to germinate and be killed during land tillage prior to sowing of faba bean. However, the 15-day delay shortens the growing season and may negatively impact seed yield. Two alternate sowing date criteria were simulated for faba bean sowing date in Morocco as approaches to increase production. In addition to the 15-day delay management by farmers, sowing was simulated to occur immediately following accumulation of 10 mm or 25 mm of water in the soil. A geospatial analysis was undertaken using the SSM-faba bean model to simulate production on a 1° × 1° grid across Morocco. Eighty three locations were each simulated for 30 growing seasons of weather input. The simulation results for the 25-mm sowing date criteria resulted in decreased geographical area in which faba bean could be grown while the 10-mm sowing date criteria resulted in an expanded geographical area for faba bean production. The average yield based only on seasons in which sowing was achieved, was fairly stable among the sowing-date criteria. The probability of yield increase of the 10-mm sowing date criterion as compared to the 15-day delay sowing was greater than 50% in much of the area found suitable for faba bean production. Assuming an acceptable method for weed control for the 10-mm sowing date criterion, this alternate management could expand faba bean production in Morocco as compared to the current practice of a 15-delay in sowing date.
... First, it is directly computed by means of translocating nitrogen from leaves to seed. The model assumes that half of the nitrogen for seed growth is provided from leaves and the remaining from other vegetative tissues or nitrogen uptake during grain filling (Ortez et al., 2019;Sinclair, 1986). Nitrogen content in seeds and leaves is assumed on average 6.5% and 3.5%, respectively (Ortez et al., 2019). ...
Accurate within-field yield estimation is an essential step to conduct yield gap analysis and steer crop management towards more efficient use of resources. This study aims to develop and validate a process-based soybean model and to predict within-field yield variability by coupling leaf area index (LAI) retrieval from Sentinel-2 into the crop model. First, a soybean model is presented, which was successfully validated with field observations of total aboveground biomass, LAI and yield from seven contrasting field campaigns with strongly varying conditions. Within-field yield predictions were achieved by combining the model and the observations of LAI through an assimilation strategy. Four model parameters were chosen to optimize against the LAI curve: soil depth, field capacity, initial LAI and nitrogen translocated from leaves to seed. Six fields were used to evaluate the methodology (21175 pixels). The accuracy assessment was conducted on a pixel-by-pixel basis using high density of information from the yield monitor. The overall accuracy quantified by the relative root mean square error (rRMSE) ranged from 28 to 51% (overall rRMSE 35.8%) across the studied fields. The Lee statistics index ranged from 0.61 to 0.71, confirming a high level of similarity between observed and simulated yield maps. Therefore, the methodology was capable of representing the observed spatial patterns of yield. Furthermore, the high consistency of the optimized WHC reflects the value of the assimilation data strategy to spatialize this relevant characteristic. Some challenges were identified for further study to reduce the sources of uncertainty and improve accuracy: i) the inability of the model to reallocate biomass by simulating plant response to source limitation, ii) the generalization of empirical algorithms to retrieve LAI, and iii) the exploration of an updating method as an assimilation strategy to overcome discrepancy between simulated and retrieved LAI.
... Advances in computing and data science have driven massive increases in data availability and a concomitant increase in models describing biological systems, and models describing these systems vary in their purpose, accuracy, correctness, granularity and interpretability. Prior to the increase in compute power, models of plant phenotypic outcomes given an environment typically existed either as parametric statistical models with explicit G×E interactions or as knowledge-based models composed of functions explicitly defining plant processes (Sinclair 1986;Prusinkiewicz 2004;van Eeuwijk et al. 2016). More recent efforts have focused on integrating G×E by coupling whole genome prediction with dynamical crop growth models, thereby generating phenotypic outcomes via non-linear functions of marker effects and environmental inputs (Technow et al. 2015;Cooper et al. 2016;Onogi et al. 2016;Messina et al. 2018). ...
The timing of crop development has significant impacts on management decisions and subsequent yield formation. A large intercontinental dataset recording the timing of soybean developmental stages was used to establish ensembling approaches that leverage both knowledge-based, human-defined models of soybean phenology and data-driven, machine-learned models to achieve accurate and interpretable predictions. We demonstrate that the knowledge-based models can improve machine learning by generating expert-engineered features. The collection of knowledge-based and data-driven models was combined via super learning to both improve prediction and identify the most performant models. Stacking the predictions of the component models resulted in a mean absolute error of 4.41 and 5.27 days to flowering (R1) and physiological maturity (R7), providing an improvement relative to the benchmark knowledge-based model error of 6.94 and 15.53 days, respectively, in cross-validation. The hybrid intercontinental model applies to a much wider range of management and temperature conditions than previous mechanistic models, enabling improved decision support as alternative cropping systems arise, farm sizes increase and changes in the global climate continue to accelerate.
... Les premiers travaux de modélisation des cultures sont apparus avec la mise en relation des processus instantanés, tels que la photosynthèse et la respiration, avec l'évolution de la biomasse accumulée (de Wit et al., 1970). Par la suite, l'appropriation de concepts existants (Monteith, 1972) et l'émergence de nouveaux concepts (Spaeth et Sinclair, 1985 ;Sinclair, 1986) vont constituer un référentiel pour l'ensemble des modèles de culture. Au Pays-Bas, les travaux de De Wit (1978) et Van Ittersum et al. (2002 ont produit des modèles, dérivés de SUCROS, s'attachant à décrire précisément l'écophysiologie des cultures à des fins souvent didactiques. ...
Il est désormais bien reconnu que les activités agricoles sont à l’origine d’une grande part de la pollution des nappes souterraines par les ions nitrate. Le cas des plaines alluviales est particulièrement intéressant puisqu’elles associent la présence d’un sol riche et profond, très favorable à l’agriculture, et d’une nappe alluviale peu profonde. Dans ce travail nous nous sommes intéressés à deux types de plaine alluviale. La plaine alluviale de la rivière Alegria (Pays-Basque ; Espagne) représente le cas d’une nappe alluviale avec un cours d’eau de faible importance. La recharge de l’aquifère se fait alors principalement par l’infiltration et la percolation de l’eau à travers la zone non saturée du sol. Dans une telle situation les fuites de nitrate sous les parcelles agricoles influencent donc significativement les concentrations en nitrate de la nappe. La modélisation de deux situations culturales (une culture de pommes de terre en 1993 et une culture de betteraves à sucre en 2002) avec le modèle de culture STICS a permis d’une part de confirmer que les pratiques agricoles avaient un impact significatif sur l’évolution des concentrations en nitrate de la nappe, et d’autre part d’expliquer en partie la diminution des concentrations en nitrate de la nappe qui a été observé entre les études (1993 et 2002). La plaine alluviale de la Garonne correspond à une situation ou les concentrations en solutés de la nappe sont influencées par les échanges nappe-zone non saturée mais également par les échanges nappe-rivière. Le couplage des sorties du modèle STICS (drainage et concentration en nitrate) avec le modèle hydro-biogéochimique 2SWEM a permis de rendre compte de ces deux types d’interactions, et ainsi d’une part d’expliquer la répartition spatiale des concentrations en nitrate dans la nappe alluviale, et d’autre part d’évaluer l’impact de modifications des pratiques agricoles sur ces concentrations (notamment l’effet des Cultures Intermédiaires Piège À Nitrate).
... [8] reported that N2-fixation began 14 days after planting only when soybean was cultivated under optimum temperature and moisture conditions, thus a small amount of nitrogen fertilizer at planting might be beneficial to early vegetative growth. It was pointed out that nitrogen applied before sowing was beneficial to soybean growth, given that soybean root nodules were not formed until at least 9 days after soybean emergence [9]. Additionally, starter nitrogen fertilizer can supply nitrogen until biological N2-fixation begins by the root nodule [10]. ...
The soybean (Glycine max L.) is a crop with a high demand for nitrogen (N). The root nodules that form in soybeans can fix atmospheric N effectively. To quantify available N in the soil a field experiment was conducted at Regional Sugarcane and Rice Research Station, Rudrur to evaluate the impact of varying sowing methods and seed rates on yield of soybean and available N in soil after harvest of crop. Planting methods and seed rates significantly influenced seed yield and available nitrogen in the soil. Broad Bed Furrow (BBF) method with seed rate 50 kg ha-1 recorded significantly higher number of pods per plant (105) and mean seed yield of 1891 kg ha-1 over flatbed with 50 kg seed rate ha-1 (1757 kg ha-1) respectively. Broad Bed and Furrow method of planting recorded a significantly higher live root nodules and available nitrogen in soil with 50 kg seed rate Original Research Article Swapna et al.; IRJPAC, 21(24): 321-327, 2020; Article no.IRJPAC.65586 322 ha-1. Seed rate of 75 kg/ha recorded highest available N in soil on broad bed and furrow method. Broad Bed Furrow (BBF) method with seed rate 50 kg ha-1 recorded highest net returns (53,233 ha-1) and highest B:C ratio (2.72) over flat bed of planting.
... [8] reported that N2-fixation began 14 days after planting only when soybean was cultivated under optimum temperature and moisture conditions, thus a small amount of nitrogen fertilizer at planting might be beneficial to early vegetative growth. It was pointed out that nitrogen applied before sowing was beneficial to soybean growth, given that soybean root nodules were not formed until at least 9 days after soybean emergence [9]. Additionally, starter nitrogen fertilizer can supply nitrogen until biological N2-fixation begins by the root nodule [10]. ...
The soybean (Glycine max L.) is a crop with a high demand for nitrogen (N). The root nodules that form in soybeans can fix atmospheric N effectively. To quantify available N in the soil a field experiment was conducted at Regional Sugarcane and Rice Research Station, Rudrur to evaluate the impact of varying sowing methods and seed rates on yield of soybean and available N in soil after harvest of crop. Planting methods and seed rates significantly influenced seed yield and available nitrogen in the soil. Broad Bed Furrow (BBF) method with seed rate 50 kg ha-1 recorded significantly higher number of pods per plant (105) and mean seed yield of 1891 kg ha-1 over flatbed with 50 kg seed rate ha-1 (1757 kg ha-1) respectively. Broad Bed and Furrow method of planting recorded a significantly higher live root nodules and available nitrogen in soil with 50 kg seed rate Original Research Article Swapna et al.; IRJPAC, 21(24): 321-327, 2020; Article no.IRJPAC.65586 322 ha-1. Seed rate of 75 kg/ha recorded highest available N in soil on broad bed and furrow method. Broad Bed Furrow (BBF) method with seed rate 50 kg ha-1 recorded highest net returns (53,233 ha-1) and highest B:C ratio (2.72) over flat bed of planting.
... Examples of crop model applications in research studies involve the quantification of trade-offs among crop productivity, management, and the environment; assessment of climate change impacts on agricultural products; support of the implementation of adaptation strategies; impact of fungal diseases; and most recently, the evaluation of pre-harvest crop quality and design of future crop ideotypes [23]. Although a variety of generic (e.g., CROP-GRO [24], APSIM-Legume [25], and STICS [26]) and specific models [27][28][29] have been developed to simulate diverse legume species (e.g., common bean, peanut, soybean, cowpea, black gram, and chickpea), a process-based model of sunn hemp to investigate its biomass productivity potential is still lacking. The few prior modeling studies were all performed using a generic simulator, originally developed for cereals and adapted via parameterization (e.g., EPIC [30]), or using empirical relationships between productive/biometric traits (e.g., total dry matter, plant height, and stem diameters) and time after sowing [31,32]. ...
Sunn hemp (Crotalaria juncea L.) is a fast growing, drought tolerant legume crop with potential as a biomass feedstock for advanced biofuels in Southern Europe, grown in either a single or double crop system. This study presents a new simulation model, SunnGro, which reproduces sunn hemp productivity, while providing a detailed description of leaf/branch size heterogeneity and its evolution during the vegetative season. The model was calibrated and validated using 20 field datasets collected from 2016 to 2018 in Greece, Spain, and Italy under non-limiting soil water conditions. High correlation between the simulated and measured values of branch number (R 2 = 0.80), leaf number (R 2 = 0.92), and biomass accumulation (0.67 < R 2 < 0.82) demonstrated good model predictivity across sites, seasons, alternative sowing densities, dates, and harvest times. An uncertainty analysis was carried out under varying seasonal air temperatures and sowing times in five European locations to explore the capability of the model to identify the best agronomic practices for maximizing sunn hemp yield. Therefore, the current version of SunnGro is an effective tool for scenario analyses under varying management practices and changing climatic conditions.
... N uptake is assumed to comprise three processes: (1) mass flow, which is a function of transpiration, (2) the nitrate concentration in soil solution, and (3) active uptake and diffusion estimated in terms of the rate at which plants can assimilate nitrate from soil and fixation (Sinclair, 1986). If N demand cannot be satisfied by mass flow, then it is supplied by either diffusion or N 2 fixation, depending on the legume species (Robertson et al., 2002). ...
Peanut is presently grown in over 26 Mha worldwide with a total production of over 45 Mt. About 80% of the world peanut production comes from rainfed regions of the semiarid tropics, where the yields are generally low and variable due to erratic water deficits and elevated temperature.
Peanut generally responds favourably to water deficit applied from emergence to start of flowering, resulting in increased pod yields. Sensitivity to water deficit increases progressively during the reproductive phase.
Biomass accumulation in peanut is usually proportional to the amount of water transpired by the plant. Researchers have demonstrated variation in transpiration efficiency (TE) between peanut genotypes with similar transpiration (T). Tis chapter describes genotypic, environmental, and management factors affecting T and TE.
This chapter describes major nutrient deficiencies that affect productivity and seed quality production in many regions of the world.
With increasing drought frequency in semiarid tropics, there is interest in breeding shorter duration cultivars. However, much of the short-duration germplasm available in the global gene banks has low yield in favourable environments, and poor seed quality and foliar disease resistance. Major introgression effort to incorporate all these traits into adapted early-maturing genotypes has been largely successful over the past decade.
In 1950’s peanut has been described as ‘the unpredictable legume’ because of its unpredictable responses to inputs. However, the physiological principles developed in the past decades have been successfully applied in peanut crop models making the crop performance predictable across diverse environments.
... inspirées des travaux de Sinclair (Sinclair, 1986). La biomasse totale produite est ensuite partitionnée entre les parties aériennes et les parties racinaires, selon les principes formalisés par Savary (Savary et Willocquet, 2012). ...
Thanks to the fast evolution of computing power and the increasing number of data processing tools over the last few years, knowledge of various scientific disciplines such as agronomy, soil science or crop physiology can be ef-ficiently used into crop models able to integrate data from multiple sources. CHN is a crop model developed by ARVALIS –Institut du Végétal which first purpose is to be used during the cropping season. CHN is able to simulate crop growth and its limiting factors, in real time and in anticipation thanks to frequency calculations, thus allowing to manage nitrogen fer-tilization. The model’s performances are presented for very diverse water and nitrogen stress situations, as well as on-go-ing work about building and validating crop management tools for nitrogen on wheat.The aim of the model is also to add value through real time decision-making processes to multiple data sources. Pairing this crop model with proxydetection (oriented photographs) or remote sensing (multispectral data by satellite, plane or UAV images) is therefore considered in the short term. Using data assimilation methods is required to make use in real time of measurements from plant sensors, such as leaf area index and chlorophyll content.
... It is particularly important that the model simulates well the partitioning between vegetative and reproductive organs in dual-purpose varieties. Several soybean models have been developed (Meyer et al. 1979 ;Sinclair 1986 ) . The CROPGRO is one of the crop simulation models that is included in the Decision Support System for Agro-technology Transfer (DSSAT) Hoogenboom et al. 1999 ; and has been used in many applications around the world Boote et al. 1998b ) . ...
Africa is the continent with the lowest fertilizer use per hectare notwithstanding the fact it possesses geologically old, infertile and degraded soils. This chapter discusses the agroecological zones (AEZ) and main soil types in Africa followed by a section on the extent, effects and costs of land degradation including issues of soil productivity and profitability associated with fertilizer use in Africa. There are a variety of soil types in the five major agro-ecological zones of Africa. Ferralsols and the Acrisol are dominant in the humid zones. Ferralsols are dominant in the sub-humid zone and so are Lixisols while in the semi-arid zone Lixisols have the larger share. Sixty five percent of the agricultural land in Africa is degraded and soil fertility depletion, a manifestation of soil degradation, is currently a serious threat to food security among small-holder farmers. Because of this state of affairs there is a strong case for enhanced fertilizer use. Maize yield has reportedly increased over the control due to NPK fertilizer application from various AEZ and when soils are amended with lime and manure yield response has been even higher. Indeed, there is credible evidence of fertilizer response and profitability in Africa relative to other parts of the world, particularly, for maize and rice thus making fertilizer investment worthwhile. In conclusion, there is need for agricultural intensification through efficient use of soil nutrient and water resources. Technologies need to be adapted to the specific biophysical and socio-economics circumstances of the small scale farmers in Africa. There is also need to focus more on increasing the fertilizers use efficiency and the development of the local fertilizer sector in order to make them more profitable.
... Bastidas et al. (2008) reported the soybean phyllochron rates of 3.7 to 4.1 days per node. In other studies the phyllochron value of 55.5 o C days leaf -1 in soybean (Sinclair, 1986), 51.7 o C days leaf -1 in sorghum (Major et al., 1990) and 45.2 o C days leaf -1 in maize (Warrington and Kanemasu, 1983) has been reported. Non-significant effect of plant density on phyllochron in the current study is in agreement with findings of other researchers; Soltani et al. (2006) in chickpea, Turpin et al. (2002) in fababean and Ranganathan et al. (2001) in pigeonpea reported that plant density has no significant effect on phyllochron. ...
Precise estimation of leaf area index (LAI) in simulation models of crops is necessary to predict dry matter production and grain yield. This study was conducted to determine phyllochron and to evaluate relationships between plant leaf area and main stem node number, and between LAI and the leaf dry weight in soybean (Glycine max). The effects of cultivar and plant density on these relationships were also investigated. Two field experiments were conducted using cultivars Sahar and DPX and a wide range of plant density in Research Farm of Gorgan University of Agricultural Sciences and Natural Resources during 2006 and 2011. Robust relationships were found between main stem node number and cumulative temperature unit (R 2 > 0.90), plant leaf area and main stem node number (R 2 > 0.88) as well as LAI and leaf dry weight (R 2 > 0.94). The effect of cultivar, but not plant density was significant on phyllochron value. The relationship between plant leaf area and main stem node number was density dependent. However, one relationship was adequate to describe dependency of LAI to leaf dry weight across cultivars and plant densities. The estimated functions and parameters in this study can be used in simulation models of soybean.
Preparation and proper implementation of water scarcity adaptation programs at the provincial level requires diverse, reliable and integrated information related to the province's water resources. To obtain this information in an integrated and dynamic manner, a system called 'System for regional Agricultural Water balance and water Accounting' (SAWA) was prepared for Fars province. First, the irrigated agricultural lands of the province were divided into 17 homogenous Agro-Ecological-Zones (AEZ). Then, a crop model (SSM-iCrop2) was calibrated and set up to simulate the growth, yield and field water balance of 35 agricultural plants under potential and farmers' conditions in the 17 AEZ. The simulations were done using weather data of 2011-2021. The outputs of the system are produced on a daily basis and for the end of the growing season. The system is also able to produce monthly outputs of water balance that are essential information for water scarcity adaptation programs such as cropping pattern. Some of the outputs of the system are crop planting date and the date of bud burst in trees, the time of occurrence of important phenological stages, total biomass, leaf area index and field water balance components such as runoff, evaporation, transpiration, deep drainage, weeds' transpiration and applied irrigation water. The outputs of this system are available for each plant or all plants in each of the zones, counties and the whole province. The testing of the system showed that the simulated yields and applied irrigation water are in satisfactory agreement with the measured ones.
Introduction: Chickpea is one of the important legumes in West Asia and North Africa. It is also
one of the important legumes in rainfed agricultural systems in these regions. Although Iran has the
fifth rank in terms of under chickpea cultivation, it ranks 47th in terms of average grain yield per
hectare (400 kg/ha). In dry areas of Iran, chickpea yield is highly dependent on the amount of rainfall
and its seasonal distribution. Therefore, annual changes in rainfall make it difficult to employ a
unitary agricultural management that leads to maximum crop yield with a predictable trend over the
years. Chickpea is the most important legume crop in Iran, accounting for over 50% of cultivated
legume lands, and is primarily planted under rainfed conditions. Chickpea production is significantly
lower than other crops.
Methodology: Simulation of the potential yield of rainfed chickpea was carried out using the SSMChickpea model and rainfed chickpea yield resulting from farmers' crop management practices,
including planting date, plant density, and nitrogen in 12 main chickpea growing regions were
evaluated. These experiments consisted of 9 independent field experiments. In the current research,
the model was evaluated based on the comparison of measured and simulated values for grain yield.
Statistical indices including determination coefficients (R2
) and normalized root mean square error
(nRMS) were used.
Research findings: The simulation with model SSM-Chickpea showed that the average potential
rainfed chickpea yield was 1200 kg/ha. The simulation results also indicated that the optimal planting
date for all regions was mid-December, as dormant seeding management, led to an increase in grain
yield of about 10% in Urmia and 60% in Khorramabad compared with the spring sowing date.
Optimal plant density was 20 plants/m2
resulted in a 27% increase in grain yield in Islamabad-e
Gharb. Regarding the plant nutrition, the results showed that using 20 kg/ha as a starter fertilizer led
to up to a 10% increase in grain yield in the Eqlid and Khorramabad. In all studied regions cv. Bivanij
had 23% greater grain yield comparing ILC 482 and a large part of chickpea grain yield potential
depented on agricultural management practices in general and planting date, specifically.
Europe imports large amounts of soybean that are predominantly used for livestock feed, mainly sourced from Brazil, USA and Argentina. In addition, the demand for GM-free soybean for human consumption is project to increase. Soybean has higher protein quality and digestibility than other legumes, along with high concentrations of isoflavones, phytosterols and minerals that enhance the nutritional value as a human food ingredient. Here, we examine the potential to increase soybean production across Europe for livestock feed and direct human consumption, and review possible effects on the environment and human health. Simulations and field data indicate rainfed soybean yields of 3.1 ± 1.2 t ha⁻¹ from southern UK through to southern Europe (compared to a 3.5 t ha⁻¹ average from North America). Drought-prone southern regions and cooler northern regions require breeding to incorporate stress-tolerance traits. Literature synthesized in this work evidenced soybean properties important to human nutrition, health, and traits related to food processing compared to alternative protein sources. While acknowledging the uncertainties inherent in any modelling exercise, our findings suggest that further integrating soybean into European agriculture could reduce GHG emissions by 37–291 Mt CO2e year⁻¹ and fertiliser N use by 0.6–1.2 Mt year⁻¹, concurrently improving human health and nutrition.
This book provides a global perspective of Indian Sandalwood categorized as ‘Vulnerable’ by the International Union for Conservation of Nature. It deals with history, distribution, propagation, chemistry, utilization, improvement, trade, and conservation in the present context. This book explores ways and means for restoring its past glory by creating awareness for its conservation and sustainable utilization. The content encompasses informative tables, appropriate graphs and figures, and illustrations with photographs and line drawings. This compendium would be useful for foresters, forestry professionals, botanists, policymakers, conservationists, NGOs, and researchers in the academia and the industry sectors.
Photosynthesis is an important process having direct relevance on the growth and development of trees, and information generated on this process in sandalwood is limited. As reported in many crop, plants and trees growth performance can be effectively assessed with the help of the photosynthetic process. Hence, this process is measured to determine biomass production efficiency. There are studies on variation in sandalwood genotypes and associated hosts for photosynthetic traits. However, there are no reports on key factors governing photosynthesis. This chapter elucidates research developments in sandalwood photosynthesis.
In this chapter, we focus on the current status of knowledge on the floral biology of Santalum album and the role of flower visitors in its pollination and fruit set. Flowers are bisexual, actinomorphic and epigynous, borne on axillary or terminal panicles. Based on the position of stigma, three types of flowers are observed: pin (stigma above the level of anther), thrum (stigma at a lower level) and homostylous (stigma and anther at the same level). A flower lasts for about three days, and its colour gradually changes from pale green or white to dark red with age. Though the ovary has 2‒4 embryo sacs, only one matures. From flowering to fruit maturation, it takes 80‒85 days, and the berries are eaten by birds, especially the Asian Koel, which may also be involved in the dispersion of seeds. There appear to be some contradictions concerning pollination, though many workers suggest that S. album is an obligate outcrossing species. However, the per cent fruit set under open pollination conditions appears to be very low, indicating a deficit in pollinators. Of the 46 species of flower visitors recorded, syrphids, calliphorids and honey bees have been reported as the most frequent visitors. However, there have been no studies to identify efficient pollinators, as most of the reports are subjective and are not supported by hard data. We also discuss the methods to be followed in sandalwood pollination studies.
Introduction:
Crop simulation models are very useful tools for evaluation plant growth and development processes. Crop simulating models may be used to estimate yield and evaluate climatic, plant and management parameters on yield. Also, it may be used to predict crop water requirement under different conditions. Crop models should be evaluated and parameterized to simulate crop growth and development. Parameterization is used for precise simulation of crop growth and development and can estimate the best and most appropriate values for model parameters obtained via observed data or calibration. The objectives of this study were to describe SSM-iCrop2 model, determine plant parameters and evaluation of alfalfa in its major production regions using SSM-iCrop2 model in Iran.
Materials and Methods:
SSM-iCrop2 crop simulation model is a simplified form of SSM crop models which is suitable for simulation of growth, development and yield of different crops under different environmental conditions and large-scale estimation of crop production, especially in evaluation of nutrient availability and climatic effects. This model includes sub models of phenology, leaf expansion and senescence, dry matter production and distribution and soil water balance. Daily weather data, agronomic management, soil properties and plant parameters are required for simulation in this model. The present study investigates the performance of SSM-iCrop2 model regarding the prediction of single cuts and overall cuts, phonologic stages and water requirement of alfalfa under changing climatic conditions of Iran. To simulate the growth, development and yield of alfalfa using SSM-iCrop2 model in Iran, the major irrigated alfalfa production provinces including East Azarbaijan, Hamedan, West Azarbaijan, Sistan and Baluchestan, Khorasan Razavi, Esfahan, Kordestan, Ghazvin, Ardabil, Markazi, Fars, Zanjan, Chaharmahal and Bakhtiyari and Tehran were identified based on the data available in Ministry of Agriculture statistics. Then, field experiment data required for model parameterization and estimation were collected from these provinces.
Results and Discussion:
According to the results of SSM-iCrop2 model parameterization, two cultivars with different leaf area indices (high-yielding and low-yielding) were determined in major alfalfa production provinces. The model was evaluated using the independent experimental data which had not been used for parameterization. The results of evaluation for alfalfa yield showed that the range of the observed single-cut forage yield was between 112 to 640 g m-2 with an average of 330 g m-2; the observed total annual forage yield ranged from 646 to 4042 g m-2 with an average of 1717 g m-2; and water requirement of alfalfa obtained from NETWAT software was between 5140 to 12690 m3 ha-1 with an average of 8746 m3 ha-1. The range of the predicted single-cut forage yield, the predicted total annual forage yield, and alfalfa water requirement were obtained 189 to 457 g m-2 with an average of 351 g m-2, 693 to 3296 g m-2 with an average of 1654 g m-2 and 4093 to 16874 m3 ha-1 with an average of 10940 m3 ha-1. Overall, in the evaluation for observed versus simulated alfalfa forage yield, 31 points were obtained for single-cut yield with the correlation coefficient (r) 0.79, root mean square error (RMSE) 88.3 g m-2, and coefficient of variation (CV) 26.78%, respectively, and 21 points were obtained for annual yield with 0.90 for r, 344.4 g m-2 for RMSE, and 20.05% for CV, respectively. Besides, the evaluation results indicated that r, RMSE, and CV for observed versus simulated alfalfa water requirement were 0.43, 3503 m3 ha-1, and 40%, respectively.
Conclusion:
The results obtained from parameterization and evaluation of SSM-iCrop2 model show that the mentioned model presents a logical prediction and accurate estimation of model parameters for yield and water requirement of alfalfa crop in Iran. Thus, this model may be used for prediction of alfalfa yield under different climates and management conditions.
Due to global climate change, Korea is facing severe droughts that affect the planting and early vegetative periods of upland crops. Soybean and adzuki bean are important legume crops in Korea, so it is critical to understand their adaptations to water stress. This study investigated the changes in root morphological properties in soybean and adzuki bean and quantified the findings using fractal analysis. The experiment was performed at the National Institute of Crop Science in Miryang, Korea. Soybeans and adzuki beans were planted in test boxes and grown for 30 days. The boxes were filled with bed soil with various soil moisture treatments. Root images were obtained and scanned every two days, and the root properties were characterized by root length, depth and surface area, number of roots, and fractal parameters (fractal dimension and lacunarity). Root depth, length and surface area and the number of roots increased in both crops as the soil moisture content increased. The fractal dimension and lacunarity values increased as the soil moisture content increased. These results indicated that the greater the soil moisture, the more heterogeneous the root structure. Correlation analysis of the morphological properties and fractal parameters indicated that soybean and adzuki bean had different root structure developments. Both soybean and adzuki bean were sensitive to the amount of soil moisture in the early vegetative stage. Soybean required a soil moisture content greater than 70% of the field capacity to develop a full root structure, while adzuki bean required 100% of the field capacity. These results would be useful in understanding the responses of soybean and adzuki bean to water stress and managing irrigation during cultivation.
Mechanistic simulation models can assist in developing recommendations to optimize yield and nutritive value and in understanding the complex interaction among plant growth, nutritive value, and environmental conditions. In this paper, we present the growth and N concentration modules of an integrated model [CATIMO (Canadian Timothy Model)] of timothy (Phleum pratense L.) primary growth and nutritive value. This growth model features radiation interception and use efficiency, leaf and stem growth, leaf senescence, and a N function based on the critical N concentration of whole plants. Model parameters were calibrated to key model attributes: leaf area index (LAI); forage N concentration; and leaf, stem, and forage dry matter (DM) yields. Calibration measurements were taken weekly on timothy primary growth in four different years at one location (Fredericton, NB, Canada). Overall, the model satisfactorily fitted the measured values with root mean square errors of 32.8, 42.0, and 65.9 g m⁻² leaf, stem, and forage DM yield, respectively. The model tended to underestimate stem DM yield at the end of the primary growth cycle, overestimate forage N concentration under nonlimiting N conditions, and underestimate N concentration under limiting N conditions. The model satisfactorily fitted LAI in 3 of 4 yr. Summary statistics of the calibration indicate a successful description of growth and development of the essential plant components required for modeling digestibility.
Soybean is the major source of vegetable protein in the world. It is produced over a wide range of latitudes, from the Canadian prairies and Northern Great Plains in the USA to tropical areas in the Brazilian Cerrados. This chapter evaluates the environmental (E) and genetic (G) factors regulating soybean development, growth, seed yield, and seed constituents, as influenced by management (M) practices as well. The chapter focuses on three major soybean-producing regions of the world (Corn Belt in USA, Brazilian Cerrados, and Argentinean Pampas), providing examples about how G × E × M interactions are exploited for regional and local adaptation. Opportunities for yield improvement and future research are highlighted.
Chickpea is an important pulse crop, cultivated on about 18 Mha worldwide, and is both a critical diet component for large populations of semiarid tropical climate and one of the most beneficial crops for farming systems’ sustainable productivity. Chickpea originates from a fairly narrow centre of origin, that is, the middle East Anatolia, although it enjoys large variation in its wild ancestors. As a cultigen, it has adapted to extremely varied cropping systems, either as a winter crop in tropical environments to a spring crop in more temperate climates, requiring in each case adaptive traits such as photoperiod sensitivity, or tolerance to cold, or Aeschochyta blight. In this chapter, we outline opportunities to meet the main challenges of chickpea adaptation to stresses, including heat, drought, and salinity, to improve agronomic management, to develop new plant types towards harvest mechanisation, and to increase quality standards to cater for the renewed interest on nutrition.
To make a unified and broad assessment of the accuracy of laboratory measurements for estimating field soil water, a comprehensive data base of field-measured upper and lower limits of the soil water reservoir was obtained and evaluated.-from Authors
A model is presented for calculating the daily evaporation rate from a
crop surface. It applies to a row crop canopy situation in which the
soil water supply to the plant roots is not limited and the crop has not
come into an advanced stage of maturation or senescence. The crop
evaporation rate is calculated by adding the soil surface and plant
surface components (each of these requiring daily numbers for the leaf
area index), the potential evaporation, the rainfall, and the net
radiation above the canopy. The evaporation from the soil surface
Es is calculated in two stages: (1) the constant rate stage
in which Es is limited only by the supply of energy to the
surface and (2) the falling rate stage in which water movement to the
evaporating sites near the surface is controlled by the hydraulic
properties of the soil. The evaporation from the plant surfaces
Ep is predicted by using an empirical relation based on local
data, which shows how Ep is related to Eo through
the leaf area index. The model was used to obtain the total evaporation
rate E = Es + Ep of a developing grain sorghum
(Sorghum bicolor L.) canopy in central Texas. The results agreed well
with values for E measured directly with a weighing lysimeter.
The onset of water stress within a crop is defined as the time at which the rate of water loss declines below that of a well watered crop in the same locality. The relation to the onset of water stress and soil water status of several readily measured plant parameters was investigated in crops of wheat and soybeans over three years. Evapotranspiration ET was monitored with weighing lysimeters. A noticeable decline in the rate of ET for both wheat and soybeans was detected once 20% to 30% of the total plant available water PAW remained in the 1 m deep lysimeter soil profile. Extension growth of wheat declined when PAW was 33% and 34% in two years of measurement. In soybeans, the decline in the rate of leaf extension coincided with the decline in the rate of ET. Midmorning measurement of exposed leaf water potential L, covered leaf water potential CL and covered plant leaf water potential CP yielded similar results for both wheat and soybeans. Day-to-day variability was least in CP and most in L. Values of CP, L and CL decreased rapidly with PAW < 30%.="" daily="" values="" of="" leaf="" diffusive="" conductance="" were="" variable="" but="" there="" was="" a="" general="" decline="" in="" conductance="" with="" paw="">< 30%.="" it="" is="" suggested="" that="">CL may be the easiest and most reliable parameter to monitor as a means of detecting the onset of stress. The results indicated that PAW levels in the root zone of 50% for wheat and 30% for soybean probably do not affect extension growth or plant water status parameters and can thus be used as criteria for irrigation scheduling.
Soyabeans were grown in nutrient sol. in a controlled environment. 50% developed normally but the rest were depodded once a wk. During 9 wk of seed development, growth of roots, shoots, leaves and pods as well as their total percentage N was monitored by weekly harvests. In the normal plants, only the pods continued to increase in dry wt. after the 2nd harvest and the wt. of the other plant parts remained nearly constant. N in roots and stems decreased slightly during pod filling and N in the leaves decreased considerably. Increase in N in the pods was relatively greater than the increase in total dry wt. The amount of N taken up from the nutrient sol. and that redistributed between plant parts was calculated. In the depodded plants, DM continued to accumulate in all plant parts throughout the experiment including the detached pods. The amount of N also increased in all plant parts. N uptake/unit DM produced was about the same for both groups of plants. The results are discussed in relation to the hypothesis that in leguminous plants the fixation or uptake of N by the roots cannot cope with the demand of the developing pods so that the necessary withdrawal from other plants parts, especially the leaves, causes the plants to die prematurely. (Abstract retrieved from CAB Abstracts by CABI’s permission)
Two kidney bean cultivars, Taishokintoki (dwarf) and Tokachishirokintoki (determinate, bush) were grown in the equidistant square pattern at five population densities, and dry matter accumulation in plant conlmunities were analyzed. The main results obtained were summarized as follows: 1. Total dry weight was highest at the highest density (44.4 plants/m²), although the difference between 25.0 and 44.4 plants/m² was very little. The maxirnum dry matter production was 641 g/m² and 734 g/m² for Taishokintoki and Tokachishirokintoki, respectively. 2. With increase in population density, dry weight of branches decreased more remarkably than that of main stem, but the ratio of the branch to the main stem was about 1 to 1 at the highest density. 3. CGR and LAI shifted higher with higher densities. NAR which was lower in higher densities, declined with progress of season, but rose temporarily at the middle of July. 4. Relative light intensity at the bottom of the canopy (logarithmic scale) decreased linearly with increasing LAI. The regression value (Ks) was low for Tokachishirokintoki, and the LAI requared for 95% light interception was 2.9 and 4.2 for Taishokintoki and Tokachishirokintoki, respectively. 5. The decrease in NAR with increase in LAI initiated from LAI 0.5. The decreasing rate was high for Taishokintoki with high Ks valuc. 6. LAIopt. and CGRnlax. were higher at stage III (the middle July) with larger solar radiation, compared with stage II and IV. At each stage the value of LAiopt. was high for Tokachishirokintoki, but the varietal difference of CGRmax. was very little. 7. The efficiency of dry matter accumulation per unit photosynthetically-activc radiation (PAR) intercepted (EPAR, dry weight mg/kcal) incrcased gradually up to the middle July and then decreased for Taishokintoki. However, those of Tokachishirokintoki were relatively constant up to the early August. The mean EPAR during the middle growing season (stage II-IV) did not differ between varicties and stages.
Senescence, as judged by the time courses of leaf lamina photosynthesis, soluble protein and chlorophyll contents, was studied in relation to mineral redistribution in field-grown soya beans [Glycine max (L.) Merr] to investigate the hypothesis that the depletion of nutrients m the leaves by the developing seeds is the cause of soya bean senescence. A mineral nutrient solution was applied to the canopy during the seed-filling period, and the effects on senescence and mineral depletion of the leaves were determined in three cultivars, at two leaf positions, weekly from beginning of seed filling through physiological maturity.
The onset of senescence occurred shortly after the beginning of rapid seed filling Photosynthetic rate declined about 60 per cent within 3 weeks. Protein dropped by 52 per cent and chlorophyll by 48 per cent over the same period.
Foliar nutrient application, at a rate previously shown to give significant yield increases in soya beans, increased the concentrations of N, P and K in the leaf laminae, but tended only to delay their decline and failed to either delay the onset or alter the course of senescence.
The results of this experiment seem to indicate that, under normal growth conditions, the events of senescence in the soya bean are not causally related to the N, P or K concentrations of the leaf laminae
Two soybean cultivars, Tokachinagaha (determinate) and Harosoy (indeterminate), were grown in the equidistant square pattern at five population densities, and dry matter accumulation in plant community were analyzed. The main results obtained were summarized as follows: 1. The maximum dry matter production was 1, 205 g/m2 at 25 pls./m2 for Tokachinagaha and 1, 123 g/m2 at l6 pls./m2 for Harosoy at about 120 days after planting. 2. With increase in population density, dry weight of branches decreased more remarkably than that of main stem, and it resulted in varying branch-main stem ratio in the plant community. 3. Relative light intensity at the bottom of the canopy was associated with LAI in whole varietics and growth stages. However, the regression value became larger in the later stage and that of Tokachinagaha (narrow leaf type) was slightly smaller than that of Harosoy (round leaf type) in each stage. The LAI required for 95% light interception was in the range from 3 to 4. 4. The decrease in NAR with increase in LAI initiated from LAI 0.3. This fact was also confirmed in LAI 0.06 to 0.6 for Harosoy at the early growth stage. 5. The estimated value of LAIopt. and CGRmax. varyed with varieties and growth stages. 6. CGR was closely related to photosyntheticallyactive radiation(PAR) intercepted by the canopy. However, the efficiency of dry matter accumulation per unit PAR intercepted (EPAR=CGR/PAR intercepted, dry weight mg/kcal) changed with growth. EPAR attained to the maximum at the young pod stage (near the maximum leaf area stage), then decreased. 7. Significant simple correlation coefficients were recognized between LAIopt., CGRmax. and EPAR, but a partial correlation coefHcient was signiticant only between CGRmax. and EPAR. CGR showed highly positive correlations with EPAR throughout the stages of pod filling.
Effects were studied of fertilizer applications for nodulating and non-nodulating soybeans and of varieties on the amounts of N, P, and K accumulated in aboveground plant parts of soybeans at successive stages of plant development. Total accumulation of N, P, and K in the plants followed patterns similar to that of drymatter accumulation. Rates of accumulation were slow early in the season, but became rapid, and the nutrients accumulated at constant daily rates between stages 5 and 9. Approximately 79% of the total accumulation of these nutrients occurred during the 46-day period between stages 5 and 9. Approximately half of the N, P, and K in the mature seeds were translocated from other plant parts, and the remaining half taken up from the soil and nodules during seed development. Fertilizer applications increased the amounts of N, P, and K accumulated by the plants. Nutrient accumulation was similar in 8 varieties.
Please view the pdf by using the Full Text (PDF) link under 'View' to the left. Copyright © . .
The water balance of soybean (Glycine max), cowpea (Vigna unguiculata), black gram (Vigna mungo), and pigeonpea (Cajanus cajan) grown in pots was studied during a soil drying cycle. The response of the plants was analysed for three distinct stages of dehydration. In stage I, the rate of transpiration remained constant and equal to that of well watered plants even though soil water status fell by more than 50%. Stage II began when the rate of soil water supply to the plant was less than potential transpiration and stomates closed resultingjn the maintenance of plant water balance. When soil water content was expressed as a fraction of transpirable soil water, all species showed a transition from stage I to stage II at a fraction of transpirable soil water of about 0.3 to 0.2. As the soil water declined further, all species had a similar decrease in relative transpiration rate. Consequently, the responses of the four species in stages I and II were essentially identical, except that pigeonpea extracted a slightly greater amount of soil water.
Stage III occurred once stomates had reached minimum conductance and water loss was then a function of the epidermal conductance and the environment around the leaf. Substantial differences were found among the four grain legumes in epidermal conductance. Soybean had the highest conductance, followed by black gram, cowpea and pigeonpea. Substantial variation in dehydration tolerance among the four grain legumes was also found: the ranking of dehydration tolerance based on the relative water content was pigeonpea > cowpea > mungbean > soybean. Differences among the four grain legume species in the duration of stage III which finished when plants died, were consistent with differences in epidermal conductance and in dehydration tolerance of leaves.
Physiological studies of soybean ( Glycine max L. Merr.) genotypes with wide differences in seed protein concentration may permit detection of important yield‐related processes. Crop growth analyses were performed in 1977 and 1980, at Gainesville, FL, on seven and eight near homozygouds eterminates oybean genotypes, respectively. In 1977, the relationships between yield, seed protein concentration, and the visual length of seed filling were also studied in 23 genotypes. The purpose of this work was to characterize N partitioning and dry matter allocation to seed, and their association with yield and other characteristics. Soybean genotypes with a range in seed protein concentration of approximately 0.38 to 0.50 kg/kg were used. Nitrogen partitioning to seeds was estimated as the change in Harvest Nitrogen Index (HNI), the ratio of seed N weight shoot N weight (disregarding fallen leaves) with time, from beginning linear seed growth until maturity. Nitrogen partitioning in high seed protein genotypes was positively associated with their higher seed N demanda nd faster or earlier vegetative N depletion. In both years, Harvest Index (HI) estimated as the ratio of seed dry weight to shoot dry weight (disregarding fallen leaves) increased linearly with lime in all genotypes from the beginning of linear seed growth until maturity (R8). The Dry Matter Allocation Coefficient (DMAC), an estimate of the rate of dry matter allocation to seed, is defined as the derivative of HI with respect to time, during the linear phase of HI increase. Thus, DMAC is a constant for each genotype‐environment combination. Dry Matter Allocation Coefficient exhibited less variability than Seed GrowthR ate estimated on a land area basis (CV = 6.8 vs. 21.8%). In both years, DMAwCa s positively associated with seed protein conten~ and faster vegetative dry weight decline during seed filling, and negatively associated with seedfilling duration, and yield. Yield was positively associated with seed‐filling duration (RS‐R7), and negatively associated with seed protein concentration. Thus, in general, high seed protein genotypes exhibited faster N partitioning and dry matter allocation into seeds, shorter seed‐filling duration, and lower yield.
The duration of the seed filling period for soybean [ Glycine max (L.) Merr.] may be limited by rapid nutrient diversion from leaves to seeds resulting in reduced leaf assimilation capacity. In this study, the effect of short‐day and long‐day photoperiods on the duration and rate of seed filling and on nutrient remobilization were examined in two determinate genotypes, ‘Ransom’ and ‘D72‐8126’. The photoperiod treatments were imposed during the seed development phase in controlled‐environment chambers. Dry matter and N distributions throughout reproductive development were measured.
Under long days, both genotypes maintained far greater leaf area and attained greater total and vegetative growth relative to short days. Reproductive growth was decreased 11% for Ransom but was increased 16% for D72‐8126 under long day conditions. The rates of growth and N accumulation per seed also were reduced by long days for Ransom but were unaffected for D72‐8126. The duration of the seed filling period was not extended for either genotype. Seed number was increased 5 and 18% by long days for Ransom and D72‐8126, respectively.
Ransom plants grown under long days had higher N concentrations in vegetative parts and lower seed N concentrations than short day plants as the reproductive phase progressed. Long‐day photoperiods caused a similar increase in vegetative N concentrations for D72‐8126, but by final harvest reproductive N concentration under long days was equal to that under short days. Nitrogen remobilization from leaves to seeds under short days did not appear to limit the dry matter or N assimilation efficiency of either genotype.
Nitrogen nutrition of soybeans [ Glycine max (L.) Merr.] during pod development is important in determining seed yield. Soybeans utilize leaf N to meet the N needs of developing fruit which may reduce yield potential. A field experiment was undertaken using ¹⁵ N to test the hypothesis that high N 2 ‐fixing rhizobia would delay mobilization of N from leaves to developing pods. Three strains of Rhizobium japonicum , USDA strains 110, 31, and an ineffective mutant of strain 8‐0, varying in N 2 ‐fixation effectiveness were used as inoculum to determine their influence on the utilization and translocation of N during pod fill. Foliarly applied ¹⁵ N urea was sprayed onto leaves five times prior to pod formation to label vegetative N. Total application of N was approximately 3 kg/ha. During the first 17 days of pod development approximately 25% of the incorporated ¹⁵ N was mobilized to the pods regardless of the rhizobial strain. During the final stages of pod development, mobilization of labelled N continued at nearly a linear rate for all rhizobial treatments. for USDA strain 110, there was an insignificant net loss in leaf and petiole N during the first 17 days of pod development which indicated there was an exchange between N 2 recently fixed and N previously incorporated into leaves. The rate of N 2 ‐fixation by both effective strains of rhizobia increased during pod development. Even though strain 110 fixed more total N than strain 31 the final seed yield for both treatments was similar due to differential partitioning of N. Future research is needed to elucidate the partitioning of N 2 fixed during pod development and to determine why the better N status of plants inoculated by strain 110 did not result in increased yields.
The objective of this study was to examine seasonal changes in specific leaf weight (SLW) of soybean ( Glycine max [L.] Merrill) leaves and to compare these with changes in leaf area, thickness, and anatomical features. For individual leaves, SLW generally decreased as leaf area increased, and then increased as leaves thickened. In most cases, leaves thickened after the period of greatest leaf area expansion. Specific leaf weight then decreased as leaves senesced. In general, the maximum SLW achieved by each leaf was successively greater with each successive node. Similarly, leaves at upper nodes were thicker than those of the lower nodes. Leaf thickening was largely the result of concurrent thickening of palisade and spongy mesophyll tissues. An important discovery was that in the uppermost, thickest leaves a third layer of palisade mesophyll cells was formed by periclinal division in the outermost palisade layer. The final SLW and leaf thickness obtained were modified by solar radiation levels during the period of leaf development. Differences in radiation distribution seemed to accentuate differences among leaves in 1976 studies and reduce differences in 1977.
Due to the large nitrogen requirement by soybeans ( Glycine max L. Merr.), efficient N utilization might conserve plant energy for other metabolic processes. One method of improving efficiency of N utilization would be to have a high total N content in the seeds vs. that in the above‐ground portion of the plant (i.e. a high N index). The objective of this field study was to evaluate a diverse group of 32 nonnodulating lines and nodulating and non‐nodulating near isogenic lines of ‘Clark’ and ‘Harosoy’ for genetic variability in harvest nitrogen index when grown at three N fertilizer rates. In a second year's experiments lines representing extremes in harvest N index were sampled throughout reproductive development and quantity of N in leaflets, petioles, stems and pods was determined. Harvest indices for grain yield and N varied among the genotypes tested. Harvest indices and harvest nitrogen indices were positively correlated with seed yield. A significant positive correlation between harvest and harvest nitrogen indices suggested that certain genotypes are efficient in mobilizing both N and dry matter to the developing seed. Differences in harvest nitrogen index at maturity resulted from differential N mobilization from leaflets, petioles and stems of efficient (high harvest N index) as compared to inefficient (low harvest N index) genotypes. In general stem N characteristics were most diagnostic of harvest N index. At maturity harvest N index was statistically correlated with grams of N in stems, percent N in stems, and percent of maximum N accumulated that was translocated from the stems. Averaged across genotypes adding N fertilizer increased the quantity of whole plant N, grain yield and percent protein in the seed. However harvest N indices were not significantly affected by N fertilization. The ranking of genotypes for harvest and harvest N indices were consistent in different environments, but the inclusion of abscised leaflets and petioles caused some differences in ranking. Of the genotypes evaluated noduating Harosoy had the greatest grain yield and was among the highest in N index.
Solar radiation interception and dry matter production were studied in soybeans ( Glycine max (L.) Merr.) grown in various planting patterns (4 populations of 26, 52, 104, and 209 thousand plants per acre within each of 4 row widths – 5, 10, 20, and 40 inches).
Increased population resulted in increased leaf area index (LAI) and a reduction in the number of days from emergance to 95% (daily basis) solar radiation interception (D 95 ). At corresponding populations of 52,000 or above, D 95 was considerably higher for the 40‐inch row pattern than for the other spatial arrangements, which differed in reaching D 95 by only a few days.
Dry matter production was a functin of percent solar radiation interception regardless of planting pattern. However, the efficiency of utilization of intercepted energy differed between years for the mean of all treatments, and was significantly lower for the 208,000 plant population in 1962. These differences were attributed to a limitation imposed by moisture stress.
Seed yield was not correlated with total dry matter produced, dry matter produced during seed formation, or solar radiation intercepted. As determined by differences in harvest index, seed yield was a function of differential utilization of photosynthate between vegetative and seed production. In general, high population or close plant spacing in any one direction tended to result in a low harvest index. Thus, while full interception during seed formation is required for maximum seed yield, conditions resulting in a high seasonal interception may not result in highest seed yield.
Leaf area is critical for crop light interception, and thereby has a substantial influence on crop yield. In this research an attempt was made to characterize the development of soybean [Glycine max (L.) Merr.] leaf area by examining the process in two phases. First, the rate of increase of plastochron index as a function of temperature was evaluated under field conditions. A total of seven cultivars was studied during three cropping seasons on Arredondo fine sand (loamy siliceous hyperthermic Grossarenic Paleudalf). A linear response was confirmed in the rate of increase in plastochron index to temperature with a base temperature of 9 to 11°C for most cultivars. Second, an allometric model for predicting plant leaf area from plastochron index was developed. The same medel with differing coefficients was found to work well for all cultivars. A simplified procedure for estimating the coefficients of the model was developed and found to result in good predictions of leaf area from plastochron index.
Please view the pdf by using the Full Text (PDF) link under 'View' to the left. Copyright © . .
High variability in acetylene reduction rates within cultivars and treatments has been a problem in evaluating treatment and cultivar effects. This study examined the sources of such variability, using field-grown soybean [Glycinee max (L.) Merr.] plants. Acetylene reduction rate per plant was measured in situ for thinned and unthinned ‘Chippewa 64’ soybean near Ithaca, NY for well-watered and drought-stressed ‘Biloxi’ soybean in Gainesville, FL and for ‘Guelph’ soybean subject to extended photoperiods in Gainesville, FL. A number of morphological traits, including leaf weight per plant and nodule weight per plant, were measured for each plant assayed. In addition, the nodule gas conductance (permeability ✕ surface area) was computed for each plant. Correlations between these characteristics and acetylene reduction rate per plant were used to assess their relative importance. Acetylene reduction rate was consistently more closely correlated with nodule weight than with shoot characteristics. The highest correlation with acetylene reduction rate was, however, with nodule gas conductance. This correlation was highly significant across all treatments, cultivars, and maturity stage. Nodule gas conductance was concluded to play an important role in determining acetylene reduction rates in field-grown plants.
Please view the pdf by using the Full Text (PDF) link under 'View' to the left. Copyright © . .
Seventy-five per cent of the N2-fixing activity (measured as the reduction of C2H2 to C2H4) and 50 per cent of the respiratory activity of detached soybean root nodules was lost when the water potential (Φ) of the
nodules was lowered from approximately −1 × 105 Pa (turgid nodules) to −9 × 105 Pa (moderately stressed nodules). Severely
stressed nodules (Φ = −1.8 × 106 Pa) showed almost total loss of N2-fixing activity and up to 80 per cent loss of respiratory activity. Increasing the oxygen partial pressure (PO2) from 104 to 105 Pa completely restored both N2-fixation and respiration in moderately stressed nodules, but only partial recovery was possible in severely stressed nodules.
The activity of the stressed nodules was very low at low PO2 (5 × 103 and 104 Pa). The C2H2-reducing activity of nodule slices, nodule breis, and bacteroids from turgid and moderately stressed nodules was almost identical
but some activity was lost in the breis and bacteroids from severely stressed nodules. Calculations showed that at low PO2 (104 and 2 × 104 Pa), the rate of O2 diffusion into severely stressed nodules was ten times lower than that for turgid nodules, but only four times lower at a
higher PO2 (4 × 104 Pa). Carbon monoxide inhibition of C2H2 reduction was slower in stressed nodules than in turgid nodules. The results are discussed in view of the possible development
of a physical barrier to gaseous diffusion and/or the possible altered affinity of the nodule leghaemoglobin for O2 in the water-stressed nodules.
The efficiency of crop production is defined in thermodynamic terms as
the ratio of energy output (carbohydrate) to energy input (solar
radiation). Temperature and water supply are the main climatic
constraints on efficiency. Over most of Britain, the radiation and
thermal climates are uniform and rainfall is the main discriminant of
yield between regions. Total production of dry matter by barley,
potatoes, sugar beet, and apples is strongly correlated with intercepted
radiation and these crops form carbohydrate at about 1.4 g per MJ solar
energy, equivalent to 2.4% efficiency. Crop growth in Britain may
therefore be analysed in terms of (a) the amount of light intercepted
during the growing season and (b) the efficiency with which intercepted
light is used. The amount intercepted depends on the seasonal
distribution of leaf area which, in turn, depends on temperature and
soil water supply. These variables are discussed in terms of the rate
and duration of development phases. A factorial analysis of efficiency
shows that the major arable crops in Britain intercept only about 40% of
annual solar radiation and their efficiency for supplying energy through
economic yield is only about 0.3%. Some of the factors responsible for
this figure are well understood and some are immutable. More work is
needed to identify the factors responsible for the large differences
between average commercial and record yields.
The redistribution of N from the vegetative plant parts and pod walls to the seed of soybeans [ Glycine max (L.) Merr.] during reproductive growth can be a major source of N for the developing seed. It has been suggested that the redistribution of N may be associated with leaf senescence. Experiments were conducted to evaluate the redistribution of N and the changes in photosynthesis in two soybean cultivars that differed in the duration of seed fill. ‘Williams’ and ‘Lincoln’ were grown in the field using conventional cultural practices for 2 years and total N, protein (1 N NaOH extractable), and CO 2 uptake rate (measured with a ¹⁴ CO 2 technique) were determined for two leaf positions (last fully expanded and 10th node) during reproductive growth. Total N (mgdm ‐2 ) in the last fully expanded leaves began to decline at growth stage R6 and declined steadily until leaf abscission occurred. Total N in the leaves from the 10th node began to decline sooner but the levels in the leaves at abscission were the same as in the last fully expanded leaves. The decline in protein generally followed a pattern similar to total N. The CO 2 uptake rate increased to a maximum during the beginning of seed fill (growth stage R5) and started to decline early in growth stage R6. There was no difference between cultivars in the relationship between CO 2 uptake rate and the levels of leaf protein. The earlier senescence of the short filling period cultivar (Lincoln) was associated with more rapid decline in CO 2 uptake rate compared with Williams.
Changes in photosynthesis, rlbulose bisphosphate carboxylase (RuBPCase), and proteolytic activity were followed in the leaves of field‐grown soybeans [ Glycine max (L.) Merr. cv. Kent] from flowering through senescence. These parameters were followed in relation to changes in leaf resistance, chlorophyll, protein, starch, total N levels, and seed development. In addition, changes in leaf ultrastructure were observed. The initial symptoms of senescence (evident 3 to 4 weeks after flowering) were a decline in photosynthesis, chlorophyll, and total leaf N and an increase in proteolytic activity. Preceding these changes there was a swelling of the chloroplasts and a disorientation of the chloroplast lamellae, possibly resulting from the apparent increase in starch deposition. Also, large numbers of osmiophilic granules appeared within the chloroplasts. These changes were evident prior to the time the seed entered its most rapid period of growth which was 4 to 7 weeks after flowering, The initial decline in photosynthesis did not appear to be due to an increase in leaf resistance or a decline in RuBPCase activity or level. The decline in protein levels began between 5 and 6 weeks after flowering and was paralleled by the decline in carboxylase activity and level. Associated with these changes were an increase in the size of the osmiophilic granules within the chloroplasts, a decrease in the number of chloroplasts with a corresponding increase in the apparent cellular breakdown products, and a dissolution of the vacuoles. No large increase in leaf resistance or change in specific activity of carboxylase was observed until late in senescence.
Grain-to-stover ratio and harvest index (the ratio of seed mass to total aboveground mass) were studied during soybean [Glycine max (L.) Merr.] seed-filling to determine the potential for using these normalized expressions of yield to improve measurements of the seed-filling period. For example, if either grain-to-stover ratio or harvest index increased linearly during seed-filling, it could be used to calculate an effective filling period. However, calculation of an effective filling period requires a linear approximation. Thus, the specific objective was to determine whether grain-to-stover ratio or harvest index increased as a linear function of time for various genotypes and environments. First, C and N assimilation and distribution rates within plants were simulated. Simulations predicted that harvest index increased linearly throughout seed filling, while grain-tostover ratio increased curvilinearly. Next, simulations were compared with data from field-grown plants at three northern locations. Cultivars included determinate and indeterminate types, and a range from early to late maturities. To a good approximation, harvest index increased linearly during the seed-filling period for all but the early cultivars. The early cultivars approached maximum values of harvest index curvilinearly. Therefore, harvest index has potential for use in calculations which require linear approximations.
Please view the pdf by using the Full Text (PDF) link under 'View' to the left. Copyright © . .
One explanation for the rapid decline in N fixation of soybeans [Glycine max (L.) Merr.] during pod-fill, is that deveioping seeds compete so strongly for photosynthate that inadequate amounts are available to nodules. Nitrogen fixation by nodulated legumes may be enhanced during the pod-filling period by increased photosynthate supply to the root system. A reduced number of pod sinks presumably would allow more of the available photosynthate to be translocated to the root system and nodules. In the field, genetic male-sterile (ms1) soybean plants naturally produce between 80% and 90% fewer pods than their fertile siblings. In addition, their leaves remain green until a killing frost which occurs usually well after their fertile siblings have completey matured. The objective of this study was to determine if these secondary effects of male sterility are also associated with dry matter and N accumulation patterns which are different from those of male-fertile plants.
Sterile and fertile plants from a population of the male-sterile (ms1) maintainer line, N69-2774, were sampled in a replicated experiment at 10day intervals from flowering to maturity. Dry weights and Kjeldahl N determinations were made on stems plus petioles, leaf blades, and pods.
We found patterns of dry matter and N accumulation in sterile plants indicating that with reduced pod set, leaves, stems, and roots were sinks for N and photosynthate during the pod-filling period. At peak N accumulation, 130 days after emergence (DAE), 70y0 of the total N in the aboveground portion of fertile plants was in the pods, 8% in stems plus petioles, and 22y0 in leaf blades. In sterile plants at 130 DAE, 11% of the N was in pods, 390/, in stems plus petioles, and 50y0 in leaf blades.
Although the sterile plants had 87% fewer pods per plant than the fertile plants and did not show leaf yellowing, sterile and fertile plants showed little difference in the rate of dry matter accumuation per pod or in the total accumulation of plant dry matter. These genotypes also contained similar amounts of total N throughout the pod-filling period. The results suggest that the retention of green leaves and increased carbohydrate supply to the roots may not increase N2 fixation in the absence of a strong seed sink.
Please view the pdf by using the Full Text (PDF) link under 'View' to the left. Copyright © . .
Data were collected during two seasons on the nitrogen accumulation and distribution in various soybean (Glycine max (L.) Merr.) cultivars. In the 1st season, 121 cultivars were surveyed for variation in nitrogen concentrations and quantities in the vegetative parts and seeds at two stages of development, just before the beginning of seed development and prior to physiological maturity. Nitrogen concentrations varied substantially among cultivars, as did total nitrogen uptake, which depended on plant biomass. Rates of nitrogen accumulation in both seed and whole plant (above ground) varied among cultivars, and indicated differing rates of nitrogen translocation from the vegetative tissue to the seed.In the 2nd year, ten cultivars were sampled at weekly intervals during seed development and analyzed for nitrogen. Three cultivars illustrate the substantial variation among cultivars. Nitrogen accumulation in the whole plant of the early maturing cultivar ‘827-4’ declined rapidly after the beginning of rapid linear pod fill, most of the nitrogen for seed development was translocated from the vegetative organs. Nitrogen accumulation in the whole plant of the later maturing and indeterminate variety, ‘Amsoy’, continued at a high constant rate throughout pod fill, but vegetative material which grew during pod fill retained much of this nitrogen so it was not available for seed development. In the cultivar ‘Corsoy’ most of the nitrogen accumulated during pod fill was used for seed development.
Leaf net CO 2 exchange of 20 varieties of soybeans ( Glycine max (L.) Merr.) was measured by infrared gas analysis. The varieties differed significantly in net photosynthesis at 100, 200, 300, and 400 ppm CO 2 . Both stomatal resistance and mesophyll resistance to diffusion of CO 2 were different among genotypes. No genotypic differences were found in CO 2 evolution into CO 2 ‐free air in light, or in CO 2 compensation concentration. Density‐thickness (leaf weight to leaf area ratio), on both dry‐ and fresh‐weight bases, was highly correlated with net photosynthesis. The evidence suggests that varietal differences in net photosynthesis were mainly a result of differences in diffusive resistances.
Net photosynthesis of most varieties began to increase around Aug. 4, at the approximate beginning of seed filling. A linear trend in increasing leaf density‐thickness occurred from beginning of testing. The increase in net photosynthesis is postulated a result of (a) decreased CO 2 diffusion resistance within the leaf, and/or (b) increased demandfo r photosynthate for seed formation.
Differences in growth of soybean (Glycine max cvs. Buchanan and Durack), green gram (Vigna radiata cvs. Berken and CES-ID-21), black gram (V. mungo cv. Regur), cowpea (V. unguiculata cv. Red Caloona), lablab bean (Lablab purpureus cv. Highworth) and pigeon pea (Cajanus cajan cvs. Royes and insensitive ICP 7179) in response to water deficits were analysed in terms of the amount of photosynthetically active radiation intercepted (I) and its efficiency of use in the production of above-ground dry matter (Ec). When water deficits developed slowly from seedling establishment and were unrelieved to maturity, reductions in I were more important than those in Ec until at least 42 days after sowing. Thereafter reductions in Ec were of greater significance than reductions in I. Integrated over the whole life cycle, the relative reductions in I tended to be greater than the reductions in Ec although some grain legumes showed similar reductions in I and Ec. In contrast, when water deficits developed rapidly when irrigation was terminated 6 weeks after sowing, the relative reductions in I were generally smaller than the reductions in Ec.
Soybeans are hypothesized to be “self-destructive” since they apparently need to translocate large amounts of nitrogen from vegetative tissues during seed-fill to sustain seed growth. To assess the possible limitations of this characteristic on soybean seed yield, a simple, dynamic simulation model is developed which accounts for the availability of nitrogen and photosynthate within the plant. The simulations show that the duration of seedfill and seed yield is clearly limited by the self-destructive characteristic. Increased availability of nitrogen within the plant is required for significant increases in soybean yields. Possible alterations of the model required to mimic actual soybean seed growth are presented.
Erickson and Michelini (1957) derived the plastochron index (PI) and a term sometimes referred to as the plastochron ratio (PR), as quantitative expressions of the vegetative development of plants. With the stable plant growth in environmental chambers and glasshouses, the assumptions used to derive these terms have been validated. However, more recently these expressions are being used to characterize growth under the unstable conditions resulting from the imposition of stress. This study examines the validity of the assumptions used to derive PI and PR for field-grown soya beans [ Glycine max (L.) Merrill] subjected to drought stress. Under stress conditions, the assumptions were not satisfied. In fact, observing change in PR appeared to be a good method for detecting drought stress in these plants. An alternate method for calculating PI based on a single, young leaf was developed. This alternate method appeared to be a more sensitive indicator of changes in leaf emergence rate under unstable conditions.
The effects of drought stress on soybean nodule conductance and the maximum rate of acetylene reduction were studied with in situ experiments performed during two seasons and under differing field conditions. In both years drought resulted in decreased nodule conductances which could be detected as early as three days after water was withheld. The maximum rate of acetylene reduction was also decreased by drought and was highly correlated with nodule conductance (r = 0.95). Since nodule conductance is equal to the nodule surface area times the permeability, the relationship of these variables to both whole-plant and unit-nodule nitrogenase activity was explored. Drought stress resulted in a decrease in nodule gas permeability followed by decreases in nodule surface area when drought was prolonged. Under all conditions studied acetylene reduction on a unit-nodule surface area basis was highly correlated with nodule gas permeability (r = 0.92). A short-term oxygen enrichment study demonstrated nodule gas permeability may limit oxygen flux into both drought-stressed and well-watered nodules of these field-grown soybeans.
Temperature and radiation influ-ences on physiological determinants of high soybean yields. Field Crops Res
- S C Spaeth
- T R Sinclair
- T Onuma
- S Konno
Spaeth, S.C., Sinclair, T.R., Onuma, T. and Konno, S., 1987. Temperature and radiation influ-ences on physiological determinants of high soybean yields. Field Crops Res. (In Review).
Temperature and radiation influences on physiological determinants of high soybean yields
- Spaeth