Meta-analysis of the relationship between crop yield and soybean rust severity

Document Type

Article

Publication Date

3-1-2015

Abstract

Meta-analytic models were used to summarize and assess the heterogeneity in the relationship between soybean yield (Y, kg/ha) and rust severity (S, %) data from uniform fungicide trials (study, k) conducted over nine growing seasons in Brazil. For each selected study, correlation (k = 231) and regression (k = 210) analysis for the Y-S relationship were conducted and three effect-sizes were obtained from these analysis: Fisher's transformation of the Pearson's correlation coefficient (Zr) and the intercept (β0) and slope (β1) coefficients. These effect-sizes were summarized through random-effect and mixed-effect models, with the latter incorporating study-specific categorical moderators such as disease onset time (DOT) (≥R1 reproductive crop stage), disease pressure (DP) (high = >70%, moderate = >40 and ≤70%, and low = ≤40% S the check treatment), and growing season. The overall mean for r¯ (back-transformed Z¯r) was -0.61, based on the random-effects model. DOT and DP explained 14 and 25%, respectively, of the variability in Z¯r. Stronger associations (r¯ = -0.87 and -0.90) were estimated by mixed-effects models for the Zr data from studies with highest DP (DP > 70%) and earliest rust onset (DOT < R1), respectively. Overall means (based on a random-effect model) for the regression coefficients β¯0 and β¯1 were 2,977 and 18 kg/ha/%-1, respectively. In other words, S as low as 3% would reduce 60 kg/ha for an expected Y of 3,000 kg/ha. In relative terms, each unitary percent increase in S would lead to a 0.6 percentage point (pp) reduction in Y. The three categorical moderator variables explained some (5 to 10%) of the heterogeneity in β¯1 but not in β¯0. The estimated relative reduction in Y was 0.41 to 0.79 pp/%-1 across seasons. Highest relative yield reductions (>0.73 pp/%-1) were estimated for studies with DOT < R1 and DP > 70%; the latter possibly due to high fungicide efficacy when DP is low, thus leading to higher yield differences between fungicide-protected and nontreated plots. The critical-point meta-analytic models can provide general estimates of yield loss based on a composite measure of disease severity. They can also be useful for crop loss assessments and economic analysis under scenarios of varying DOT and weather favorableness for epidemic development.

Publication Source (Journal or Book title)

Phytopathology

First Page

307

Last Page

315

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