Comparison of DRIS and alternative nutrient diagnostic methods for soybean

Abstract

The Diagnosis and Recommendation Integrated System (DRIS) provides advantages over the Sufficiency Range (SR) approach to diagnosing the nutrient status of soybean (Glycine max L.).However, a number of modifications to DRIS have been proposed, including the use of only one method for calculating nutrient indices, and incorporating nutrient concentrations. In previous research, the author found that derivation and interpretation of DRIS diagnoses could be simplified by: 1) using a logarithmic transformation of nutrient ratio data; 2) using population parameters rather than high-yield subpopulation values; 3) using a single index calculation method; and, 4) incorporating a measure of 901 902 BEVERLY the probability of yield response to a treatment. Diagnoses by the SR approach, DRIS, three revisions of DRIS, and two new concentration-based diagnostic methods were compared using diagnostic norms derived from a data base of over 4000 soybean tissue analyses and yield observations. Virtually all diagnoses of the most limiting nutrient were the same, except that the SR method did not make diagnoses on 5 week-old samples. Traditional DRIS diagnoses were the least conservative, indicating only the order in which N, P and K would likely limit yield. Revised methods, particularly the concentration-based methods, indicated fewer limiting nutrients, and agreed well with the SR method. Yields in the test data set increased with nearly every nutrient application, so the least conservative DRIS showed the greatest yield advantage.No diagnostic method consistently identified the nutrient causing the greatest yield response as most limiting.

DRIS standard and normal ranges of foliar nutrients for the culture of ‘Thompson’ atemoya

“…Populations revealed normality in the data through the ShapiroWilk test (W=0.91468; P=0.0152). Dual relations were transformed to the required logarithmic scale of the DRIS standard of BEVERLY (1987) to eliminate the degree of flattening the distribution of values in relation to the normal curve (kurtosis effect) in the coefficient of variation. Table 1 lists the averages of the bivariate relations and their respective standard deviations, used to establish the norm.…”

“…According to the levels of the macronutrients (g kg -1 ) and micronutrients (mg kg -1 ) present in the foliar tissue, as well as the Atemoyas yield (t ha -1 ) estimated for the agricultural crops, the DRIS standard was established by implementing the bivariate relationships of the log-transformed models, as suggested by BEVERLY (1987).…”

Acurácia do diagnóstico nutricional de pomares de mangueiras obtido por três fórmulas DRIS

“…O uso de relações bivariadas transformadas logaritmicamente foi proposto para corrigir os desvios observados na distribuição normal entre as formas diretas e inversas de expressão de uma mesma relação (Beverly, 1987 Wadt et al (2007). A fórmula de Parent & Dafir (1992) adota, originalmente, a transformação logarítmica.…”

Foliar Nutrient Balance Standards for Maize (<i>Zea mays</i> L.) at High-Yield Level

“…[45] proposed to log transform dual ratios to reduce variance in DRIS standards and produce variances and means independent of dual ratio expression. Nutrient log ratio standards for maize have been further rectified using the clr transformation [46].…”