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Productivity of low and high productivity subpopulations of samples of sugar cane (Saccharum officinarum).
Source publication
The use of accuracy measures for modeling the formulas of the Comprehensive Diagnosis and Recommendation System (DRIS), can improve the efficiency of the method in assessing the nutritional status in sugarcane. Therefore, the objective was to use the accuracy measures proposed by Wadt and Lemos for the modeling of DRIS formulas in sugarcane, based...
Contexts in source publication
Context 1
... separate the high and low productivity subpopulations, the criterion of using high-productivity units as above-average was used (Table 2). The total data for the sugarcane population in the agricultural year of 2013 and 2014 was 720 and 504 samples respectively. ...Context 2
... low productivity subpopulation was made up of 33% of the samples. In the 2014 agricultural year, the high productivity subpopulation represented 18% and the low productivity subpopulation comprised 82% of the samples (Table 2). Similar results were reported by Morais et al. (2019) and Villase~ nor et al. (2020) in the species of Eucalyptus spp and Musa spp respectively. ...Similar publications
The Plant Response Potential to Fertilization (RPF) method, as it has been interpreted, may result in nutritional diagnoses with low efficiency. In this regard, this work aimed to validate the RPF criterion and determine the percent value to be considered as culm yield increase based on the accuracy of nutritional diagnoses for nutrient P in sugarc...
Citations
... The ACEQ measurement, in this study, reflects that about 50% of the diagnoses of N and K were correct as for nutritional balance, a fact Silva et al. 25 also reported. Wadt and Lemos 17 adds that true diagnoses for nutritional balance are important to avoid environmental impacts due to excessive use of fertilizers. ...
... Regarding the ACEx accuracy measurement, the values above 60% for N and K indicate the degree of correctness of the diagnosis of nutritional excess (Table 6). This result is possibly due to the use of a reduced number of samples, which favors false diagnoses because of nutritional excess 25 . ...
... A low accuracy of DRIS norms has also been found in other species, although the number of crops is very small, such as sugarcane (Saccharum officinarum L.) 20,25,27 and mango (Mangifera indica L.) 28 . Therefore, this issue has to be well discussed in order to take actions to reverse the low precision of diagnoses generated, thus aiming to induce direct benefits in the valuation of the use of leaf analysis in technique-intense crops, favoring www.nature.com/scientificreports/ ...
DRIS (Diagnosis Recommendation Integrated System) is a tool used in the interpretation of leaf analyses that values the balance of nutrients, an important fact for a better assessment of the nutritional status of banana plants. Its usefulness depends on the ability to identify the nutrients that limit productivity in order to correct possible nutritional imbalances, but there is a lack of research in all crops, including bananas, to assess the accuracy of these diagnoses, which have a worrying global implication. To this end, this study evaluates DRIS norms for banana cultivation in Ecuador and the use of accuracy measurements for nutritional diagnosis, verifying the capacity of DRIS to detect true nutritional status based on plant response. The database created here contains 233 results referring to productivity and leaf contents of N, P, K, Ca, Mg, S, Cl, Fe, Mn, Cu, B, and Zn for banana trees in 2018, 2019, and 2020. Then, a field experiment evaluated doses of nitrogen and potassium and the accuracy of DRIS norms for N and K. The results show that the DRIS of banana produced in Ecuador depends on the nutrient being variable according to the crop nutritional status. The DRIS norms for diagnosis of N and K result in an acceptable accuracy to identify only deficiencies and toxicities, respectively, indicating the need for adjustments in these standards for later use in the field. Thus, there is a need for more research aiming to adopt calibrated DRIS diagnostic norms to assess the nutritional status of bananas in Ecuador.
... Traditional methods of interpreting chemical analyses of soils and leaves such as the methods using critical levels (CL) and/or sufficiency ranges (SR) only consider nutrients in isolation (univariate analysis), not considering possible interactions that exist between nutrients both in the soil and in the plant (Calheiros et al. 2018;Morais et al. 2019;Silva et al. 2021a). These methods also have disadvantages for ignoring uncontrolled factors, such as the rate of biomass accumulation of leaf tissue, light, temperature, and water regime (Wadt 2011;Ribeiro et al. 2020;Silva and Chiaia 2021). ...
This study aimed to determine DRIS standards and indices in commercial sugarcane plantations through soil, leaf, and stem samples collected in the southern region of the state of Goiás, Brazil. The experiment was arranged in a 2 × 2 factorial design with two cultivation systems (with or without vinasse application) and two sugarcane varieties (CTC 4 and RB 867515), both with 50 sampling points. The database was created using the total amount of soil samples collected at a depth of 0–0.20 m for chemical analysis, leaves collected in the period of greatest vegetative development of the crop (240 days after ratoon sprouting) for chemical analysis and the yield of stems for the industry. It was found that fertigation with vinasse can promote increases in the yield of cane stalks for the industry in the order of 35 t ha−1 for the variety CTC 4. The DRIS indices for the soil enabled to diagnose limitations caused by nutritional deficiencies regarding the available contents of P and Zn for areas cultivated with CTC 4 and the available contents of K, Cu, Fe, and Mg for areas cultivated with RB 867515. The nutritional diagnosis carried out using the DRIS method for the chemical analysis of leaves showed greater sensitivity for detecting nutritional limitations of Ca, Cu, and Mn compared to traditional methods of interpretation by critical levels. The nutritional balance index (NBI) is an efficient tool for the proper diagnosis of nutritional balance, since the lowest NBI indices were the ones that provided the highest stalk yields of ratoon cane for the industry.
... The ACEQ measurement, in this study, re ects that about 50% of the diagnoses of N and K were correct as for nutritional balance, a fact Silva et al. 25 also reported. Wadt and Lemos 17 adds that true diagnoses for nutritional balance are important to avoid environmental impacts due to excessive use of fertilizers. ...
... Regarding the ACEx accuracy measurement, the values above 60% for N and K indicate the degree of correctness of the diagnosis of nutritional excess (Table 6). This result is possibly due to the use of a reduced number of samples, which favors false diagnoses because of nutritional excess 25 . ...
... A low accuracy of DRIS norms has also been found in other species, although the number of crops is very small, such as sugarcane (Saccharum o cinarum L.) 20,25,27 and mango (Mangifera indica L.) 28 . Therefore, this issue has to be well discussed in order to take actions to reverse the low precision of diagnoses generated, thus aiming to induce direct bene ts in the valuation of the use of leaf analysis in techniqueintense crops, favoring sustainability by optimizing the use of most non-renewable fertilizers. ...
DRIS (Diagnosis Recommendation Integrated System) is a tool used in the interpretation of leaf analyses that values the balance of nutrients, an important fact for a better assessment of the nutritional status of banana plants. Its usefulness depends on the ability to identify the nutrients that limit productivity in order to correct possible nutritional imbalances, but there is a lack of research in all crops, including bananas, to assess the accuracy of these diagnoses, which have a worrying global implication. To this end, this study evaluates DRIS norms for banana cultivation in Ecuador and the use of accuracy measurements for nutritional diagnosis, verifying the capacity of DRIS to detect true nutritional status based on plant response. The database created here contains 233 results referring to productivity and leaf contents of N, P, K, Ca, Mg, S, Cl, Fe, Mn, Cu, B, and Zn for banana trees in 2018, 2019, and 2020. Then, a eld experiment evaluated doses of nitrogen and potassium and the accuracy of DRIS norms for N and K. The results show that the DRIS of banana produced in Ecuador depends on the nutrient being variable according to the crop nutritional status. The DRIS norms for diagnosis of N and K result in an acceptable accuracy to identify only de ciencies and toxicities, respectively, indicating the need for adjustments in these standards for later use in the eld. Thus, there is a need for more research aiming to adopt calibrated DRIS diagnostic norms to assess the nutritional status of bananas in Ecuador.
