Data/hora: 30/05/2024 04:39:09

Biblioteca(s): 	Embrapa Soja.	
Data corrente: 	21/07/2015	
Data da última atualização: 	04/08/2017	
Autoria: 	DALLA LANA, F.; ZIEGELMANN, P. K.; MAIA, A. de H. N.; GODOY, C. V.; PONTE, E. M. D.	
Afiliação: 	FELIPE DALLA LANA, UFRGS; PATRICIA K. ZIEGELMANN, UFRGS; ALINE DE HOLANDA NUNES MAIA, CNPMA; CLAUDIA VIEIRA GODOY, CNPSO; EMERSON M. DEL PONTE, UFV.	
Título: 	Meta-analysis of the relationship between crop yield And soybean rust severity.	
Ano de publicação: 	2015	
Fonte/Imprenta: 	Phytopathology, v. 105, n. 3, p. 307-315, 2015.	
ISSN: 	0031-949X	
DOI: 	10.1094/PHYTO-06-14-0157-R	
Idioma: 	Português	
Conteúdo: 	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 ( &#61666;&#61472;0) and slope ( &#61666;1) 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 or &#8805;R1 reproductive crop stage), disease pressure (DP) (high = >70%, moderate = >40 and &#8804;70%, and low = &#8804;40% S the check treatment), and growing season. The overall mean for &#1050446;&#773; (backtransformed &#1050428;&#773; r) was ?0.61, based on the random-effects model. DOT and DP explained 14 and 25%, respectively, of the variability in &#1050428;&#773; r. Stronger associations (&#1050446;&#773; = ?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 &#1050586;&#1051444; &#1051940;&#1051940;&#1051940; and &#1050586;&#1051445; &#1051940;&#1051940;&#1051940; 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 &#1050586;&#1051445; &#1051940;&#1051940;&#1051940; but not in &#1050586;&#1051444; &#1051940;&#1051940;&#1051940;. 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 beuseful for crop loss assessments and economic analysis under scenarios of varying DOT and weather favorableness for epidemic development.	
Palavras-Chave: 	Soybean.	
Categoria do assunto: 	--	
Registro original: 	Embrapa Soja (CNPSO)	
Exemplares: 	CNPSO - (36113-1) - UPC - AP - DD -  -  -  - DIS