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Soil bulk density (g cm −3 ) at 0−30 and 30-60 cm for the high yield stable zone (HYZ, blue bar), medium yield stable zone (MYZ, green bar), low yield stable zone (LYZ, yellow bar), and unstable yield zone (UYZ, red bar). The error bars represent the standard deviations of the transects within each zone.
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Nitrogen fertilization is the most critical agronomic input affecting barley production and farm profitability. The strict quality requirements for malting barley are challenging to achieve for farmers. In addition, soil variability and weather conditions can affect barley yield and quality. Thus, the objectives of this study are to (a) quantify th...
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Context 1
... flowering, the LYZ had the greatest soil mineral N content (109 kg N ha −1 ) at 0−30 cm depth (Figure 4a), while at 30-60 cm, the UYZ had the most soil mineral N content (180 kg N ha −1 ) (Figure 4b). The soil bulk density differed between the management zones, with average values ranging between 1.65 g cm −3 for the UYZ and 1.72 g cm −3 for the LYZ for the first 30 cm ( Figure 5). The mean values increased for all the zones for the 30-60 cm depth interval, and the LYZ had the greatest bulk density (1.79 g cm −3 ; Figure 5). ...
Context 2
... soil bulk density differed between the management zones, with average values ranging between 1.65 g cm −3 for the UYZ and 1.72 g cm −3 for the LYZ for the first 30 cm ( Figure 5). The mean values increased for all the zones for the 30-60 cm depth interval, and the LYZ had the greatest bulk density (1.79 g cm −3 ; Figure 5). The results of the other soil chemical analyses were less variable. ...
Citations
... Permanent grassland represents around 70% of all agricultural land And, in comparison with other agroecosystems, grasslands are more sensitive to climate change. However, digital and precision agriculture as well as crop simulation models can help farmers to adopt adaptation strategies suitable to reduce the negative impacts related to climate change [49,50]. ...
Permanent grasslands represent the main terrestrial ecosystem and serve as an important global reservoir of biodiversity, providing a wide range of benefits to humans and ecosystems. The effects of environment on permanent meadows (in our survey, they were centuries-old meadows that had not been plowed, mowed, or fertilized with manure) production have been adequately investigated in literature. However, plant species composition impact on potential feed value of first cut has still to be understood, in particular regarding different agronomic management. Our field trial was carried out in five farms, in a territory involved in the value chain of the Parmigiano Reggiano PDO (Val d'Enza, Northern Italy), over a two-year period (2017-2018). Differences in botanical composition, biomass, and Pastoral Value index (PV), which synthesizes grassland yield and nutritional parameters, were investigated in depth. The herbage dry matter (DM) yield was affected by year, farm, and their interaction factors. Its highest value across the two years was recorded in farm 5 (11.7 tons of DM ha −1), which applied the highest rate of nitrogen fertilization. The botanical composition of the first cut has favored the presence of both Poaceae and 'other species' (each one around 40 plants per transect) compared to Fabaceae (seven plants per transect). However, higher numbers of Fabaceae plants (13 and 10) plausibly determined increases in PV in farms 3 and 5 (56.4 and 58.7, respectively). Although differences were observed among the most important nutritional parameters of grassland (crude protein, digestible and undigested neutral detergent fiber contents), suitable net energy for lactation (NE L) values for feeding lactating cows were always recorded during the two years of survey. The present study provides a contribution of knowledge on how the botanical composition of permanent meadows may affect their potential nutritive value as fresh herbage for feeding dairy cows. Considering these results, the agronomic management should seek a level of plant biodiversity that at the same time might guarantee satisfactory yield and feed value, also in a context of climate change.
... Photoperiod and rising global temperature influence the phenological growth of barley crops. Duration of specified phenological phases was reduced, due to which the growing period was shorter, and lower yield (Cammarano et al., 2020). Barley grain production declined 6-11% due to an increase in 2-8°C of air ambient temperature. ...
... Finally, the relative change of yield, water and nitrogen respect to the baseline was done. The analysis and the indexes were calculated as reported by Cammarano et al. (2020). The box and whiskers plots were used to plot the relative changes and the horizontal line in the box represented the median, the box was the 25 th and the 75 th percentiles, the whiskers the 10 th and 90 th percentiles. ...
... Additional factors relating to economic feasibility and machinery capability may be considered to define zone classes and size. Management zoning based on yield maps (Basso et al. 2011;Cammarano et al. 2020), multispectral images (Karydas et al. 2020), and soil proximal sensing (Davatgar et al. 2012;Peralta et al. 2015) have been previously explored in major cereal crops that are predominantly grown in sole stands to improve nutrient use efficiency. For diversified cropping systems at the landscape scale, Donat et al. (2022) applied a cluster analysis methodology using yield maps and proximal sensed soil characteristics to delineate "patch" units (~0.5 ha patch units, restricted to current machinery size) and classify patches into high and low yield potential zones, to design diversified cropping systems with smaller spatial arrangements to improve the agroecosystem functionality. ...
Intensive agriculture in Germany is not only highly productive but has also led to detrimental effects in the environment. Crop diversification together with new field arrangements considering soil heterogeneities can be an alternative to improve resource use efficiency (RUE), ecosystem services (ESS), and biodiversity. Agroecosystem models are tools that help us to understand and design diversified new field arrangements. The main goal of this study was to review the extent to which agroecosystem models have been used for crop diversification design at field and landscape scale by considering soil heterogeneities and to understand the model requirements for this purpose. We found several agroecosystem models available for simulating spatiotemporal crop diversification at the field scale. For spatial crop diversification, simplified modelling approaches consider crop interactions for light, water, and nutrients, but they offer restricted crop combinations. For temporal crop diversification, agroecosystem models include the major crops (e.g., cereals, legumes, and tuber crops). However, crop parameterization is limited for marginal crops and soil carbon and nitrogen (N). At the landscape scale, decision-making frameworks are commonly used to design diversified cropping systems. Within-field soil heterogeneities are rarely considered in field or landscape design studies. Combining static frameworks with dynamic agroecosystems models can be useful for the design and evaluation of trade-offs for ESS delivery and biodiversity. To enhance modeling capabilities to simulate diversified cropping systems in new field arrangements, it will be necessary to improve the representation of crop interactions, the inclusion of more crop species options, soil legacy effects, and biodiversity estimations. Newly diversified field arrangement design also requires higher data resolution, which can be generated via remote sensing and field sensors. We propose the implementation of a framework that combines static approaches and process-based models for new optimized field arrangement design and propose respective experiments for testing the combined framework.
... An accurate and timely forecast of yields during the vegetation season is the basis for estimating production volumes during the harvest. Moreover, early information on the future allows farmers to plan and organize their purchases, storage, and processing of agricultural crops [8,9,11,[13][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28]. ...
... One of the most important factors affecting plant development is weather, which it is why the constructed models should take into account meteorological data (e.g., air temperature, rainfall, insolation) [8,15,24,[29][30][31][32]. Moreover, the second group of traits influencing plant development is connected with the soil and they should be taken into account in the models under construction: pH, structure, organic material content, and nutrient levels [11,23,25,[33][34][35][36]. Proper management, including fertilization, harvesting technology, and tillage technologies, of crop rotation has a positive effect on soil structure and the availability of water for plants. ...
... It was possible to conclude that for the AGRO-SBY model for Polish conditions, under moderate input management, the level of N + P + K fertilization negatively influenced the final yield, but N fertilization significantly positively affected the yield. This element is im-portant because the fertilization, as a part of the crop management, can be properly planned and farmers can prevent the negative impact of over-fertilization by N and N + P + K on the soil, which is as important part of the environment [11,23,33,34,36]. ...
In recent years, forecasting has become particularly important as all areas of economic life are subject to very dynamic changes. In the case of agriculture, forecasting is an essential element of effective and efficient farm management. Factors affecting crop yields, such as soil, weather, and farm management, are complex and investigations into the relation between these variables are crucial for agricultural studies and decision-making related to crop monitoring, with special emphasis for climate change. Because of this, the aim of this study was to create a spring barley yield prediction model, as a part of the Advisory Support platform in the form of application for Polish agriculture under a moderate input management system. As a representative sample, 20 barley varieties, evaluated under 13 environments representative for Polish conditions, were used. To create yield potential model data for the genotype (G), environment (E), and management (M) were collected over 3 years. The model developed using Multiple Linear Regression (MLR) simulated barley yields with high goodness of fit to the measured data across three years of evaluation. On average, the precision of the cultivar yielding forecast (expressed as a percentage), based on the independent traits, was 78.60% (Model F-statistic: 102.55***) and the range, depending of the variety, was 89.10% (Model F-statistic: 19.26***)–74.60% (Model F-statistic: 6.88***). The model developed using Multiple Linear Regression (MLR) simulated barley yields with high goodness of fit to the measured data across three years of evaluation. It was possible to observe a large differentiation for the response to agroclimatic or soil factors. Under Polish conditions, ten traits have a similar effect (in the prediction model, they have the same sign: + or -) on the yield of almost all varieties (from 17 to 20). Traits that negatively affected final yield were: lodging tendency for 18 varieties (18-), sum of rainfall in January for 19 varieties (19-), and April for 17 varieties (17-). However, the sum of rainfall in February positively affected the final yield for 20 varieties (20+). Average monthly ground temperature in March positively affected final yield for 17 varieties (17+). The average air temperature in March negatively affected final yield for 18 varieties (18-) and for 17 varieties in June (17-). In total, the level of N + P + K fertilization negatively affected the final yield for 15 varieties (15-), but N sum fertilization significantly positively affected final yield for 15 varieties (15+). Soil complex positively influenced the final yield of this crop. In the group of diseases, resistance to powdery mildew and rhynchosporium significantly decreased the final yield. For Polish conditions, it is a complex model for prediction of variety in the yield, including its genetic potential.
... Additional factors relating to economic feasibility and machinery capability may be considered to define zone classes and size. Management zoning based on yield maps (Basso et al. 2011;Cammarano et al. 2020), multispectral images (Karydas et al. 2020), and soil proximal sensing (Davatgar et al. 2012;Peralta et al. 2015) have been previously explored in major cereal crops that are predominantly grown in sole stands to improve nutrient use efficiency. For diversified cropping systems at the landscape scale, Donat et al. (2022) applied a cluster analysis methodology using yield maps and proximal sensed soil characteristics to delineate "patch" units (~0.5 ha patch units, restricted to current machinery size) and classify patches into high and low yield potential zones, to design diversified cropping systems with smaller spatial arrangements to improve the agroecosystem functionality. ...
... In general, the soil pH values were within the optimal range for barley production, with average values ranging between 6.0 and 6.6 [26]; however, it was confirmed that the pH of reclaimed soil in our study was 7.41-7.84, which was higher than the mean values. ...
This research was conducted to select the most suitable winter forage crop varieties for silage in reclaimed land located in the Midwest of Korea by investigating the soil environment, crop growth characteristics, dry weight, and forage value according to growth stage. The slightly alkalescent soil was characterized by a pH of 7.41–7.84, by an electrical conductivity (EC) of 1–2.5 dS/m, and by 440–934 mg/kg of available phosphate. Barley showed the highest chlorophyll content in the heading stage and milk stages, while oats and triticale reached the highest content in the milk and dough stage. In both years, triticale achieved the highest leaf area index (LAI), reaching 4.3–4.8. In addition, triticale showed the highest percentage of dry matter and the highest dry weight in the milk stage. Forage value was the best in the heading stage for all cereal crops; however, its quality decreased as the growth stage proceeded. This study suggests cultivating triticale, which showed high adaptability to reclaimed soil and climatic conditions, as well as good growth and dry weight when harvested between the milk and dough stages. These results indicate that triticale can be cultivated all year round in salty soil and these data can be useful to increase forage production in reclaimed soil.
... Across our models, production of arable crops (Fig. 3) agrees with that published by Defra (June Agriculture Surveys) and in the farming literature (BSPB, 2020;Cammarano et al., 2020;Nix, 2020). For wheat, spring barley, winter barley and winter OSR regional statistics for the period simulated report yields between 5.6-8.3 ...
Agriculture is challenged to produce healthy food and to contribute to cleaner energy whilst mitigating climate change and protecting ecosystems. To achieve this, policy-driven scenarios need to be evaluated with available data and models to explore trade-offs with robust accounting for the uncertainty in predictions. We developed a novel model ensemble using four complementary state-of-the-art agroecosystems models to explore the impacts of land management change. The ensemble was used to simulate key agricultural and environmental outputs under various scenarios for the upper River Taw observatory, UK. Scenarios assumed (i) reducing livestock production whilst simultaneously increasing the area of arable where it is feasible to cultivate (PG2A), (ii) reducing livestock production whilst simultaneously increasing bioenergy production in areas of the catchment that are amenable to growing bioenergy crops (PG2BE) and (iii) increasing both arable and bioenergy production (PG2A + BE). Our ensemble approach combined model uncertainty using the tower property of expectation and the law of total variance. Results show considerable uncertainty for predicted nutrient losses with different models partitioning the uncertainty into different pathways. Bioenergy crops were predicted to produce greatest yields from Miscanthus in lowland and from SRC-willow (cv. Endurance) in uplands. Each choice of management is associated with trade-offs; e.g. PG2A results in a significant increase of edible calories (6736 Mcal ha⁻¹) but reduced soil C (−4.32 t C ha⁻¹). Model ensembles in the agroecosystem context are difficult to implement due to challenges of model availability and input and output alignment. Despite these challenges, we show that ensemble modelling is a powerful approach for applications such as ours, offering benefits such as capturing structural as well as data uncertainty and allowing greater combinations of variables to be explored. Furthermore, the ensemble provides a robust means for combining uncertainty at different scales and enables us to identify weaknesses in system understanding.
... Chemical protection of crops and increased droughts and dry winds, especially in the southern regions of our country. This is not only a problem of Ukraine, but also a global problem, as evidenced by studies (Cammarano et al., 2020;Carter et al., 2019;Sallam et al., 2019;Solonechnyi et al., 2015;Toymetov and Maryina-Chermnykh, 2020;Yurkevich et al., 2011) . The increased droughts in the south of Ukraine leads to the fact that intensive varieties of spring barley cannot use their full potential, resulting in a significant yield reduction . ...
Studies were conducted in the Northern Steppe of Ukraine with the aim to increase the drought resistance of spring barley through such agrotechnical methods as: selection of new adaptive varieties, as well as improving the fertilizer system through the use of new nutrient complexes. New promising drought-resistant varieties of spring barley such as Stepovyk, Avers, Pryazovskyi 9, Chudovyi, Donetsk 14 are intended for cultivation in the Northern Steppe of Ukraine. It is established that the use of the new Nutrient Complex 3 increases the yield with the mineral fertilizer system by 1.37 t/ha, with the organo-mineral fertilizer system —by 2.08 t/ha, and Nutrient Complex 1 with the biological fertilizer system —by 1.6 t/ha,compared with control sample without the use of nutrient complexes.
... The study indicated that the negative effect of climate change in the future could be minimized by choosing different crop management practices such as timely sowing and N management. Within DSSAT-CERES-Barley, the daily crop growth rate is defined based on the amount of intercepted radiation by leaf area per area unit with the underlying mechanism of radiation use efficiency (Cammarano et al., 2020;Jamieson et al., 1995). In DSSAT-CERES-Barley, the phenological development of the plant is a function of temperature and photoperiod. ...
... In DSSAT-CERES-Barley, the phenological development of the plant is a function of temperature and photoperiod. Higher temperatures lead to a shorter duration of specific phenological phases, resulting in a shorter growing season and reduced yield (Cammarano et al., 2020). The amount of water in the soil during plant development is of critical importance for nitrogen uptake and plant water status. ...
... The model simulated the observed days to anthesis and maturity with RMSEs of 2 and 6 d, respectively, for Traveller and 2 d for EH-1493 each. Likewise, a good simulation performance of the model for anthesis and maturity was observed in previous studies on barley (Cammarano et al., 2020;Brogan, 2019;Rötter et al., 2012). In this study, the model simulated the grain yield with a RMSE of 634.6 and 508.9 kg ha −1 for EH-1493 and Traveller, respectively (Figure 2). ...
Climate change is expected to have a major effect on crop production in sub‐Saharan Africa. Crop models can help to guide crop management under future climate. The objective of the study was to investigate the possible effects of climate change on Ethiopian barley (Hordeum vulgare L.) production using the Decision Support System for Agrotechnology Transfer (DSSAT)‐Crop Environment Resource Synthesis (CERES)‐Barley model. The study included field data of two barley cultivars (Traveller and EH‐1493) and four climate study areas in Ethiopia over 5 yr. Climate change scenarios were set up over 60 yr using representative concentration pathways (RCP; RCP4.5 and RCP8.5) and five global climate models (GCM). The model results indicated that the prediction of days to anthesis and maturity, as well as final grain yield, was highly accurate for cultivar Traveller with normalized RMSE (nRMSE) of 2, 1, and 12%, respectively, and for cultivar EH‐1493 with nRMSE of 2, 4, and 11%. A consistent increase in average temperature up to 5 °C and a mixed pattern of rainfall (‐61 to +86%) were projected. Yield simulations showed a potential reduction in yield up to 98% for cultivar Traveller and 63% for cultivar EH‐1493 in the future. Within a sensitivity analysis, different sowing dates, sowing densities, and fertilizer rates were tested as potential adaptation approaches to climate change. The negative effects of climate change could be mitigated by early sowing, with an increased sowing density of 25% and fertilizer rate of 50% more than what is recommended. Overall, the results indicated the ability of the CERES‐Barley model to evaluate climate change effects and adaptation options on rainfed barley production in Ethiopia.
