Nonlinear regression and plot size to estimate green beans production

The objectives of this work were to adjust nonlinear regression models for the green beans production and to identify the plot size which provides the best explanation and adjustment to the models. The authors used two field and two protected environment (plastic tunnel) trials in the autumn-winter and spring-summer seasons. The logistic and von Bertalanffy models were adjusted for average weight of green beans accumulated after multiple harvests and with different plot sizes. The models presented similar estimates and the same parameters estimates in all the plot sizes. The logistic model provided estimates closest to the reality, showing the best description performance for the average weight of pods during the productive cycle. In the autumn-winter season, plot size of 14 basic units (28 plants in the cultivation line direction) in the field and of two basic units (four plants in the cultivation line direction) under the plastic tunnel provide a good quality in the models adjustment. In the springsummer season, the plot sizes are made of six basic units (12 plants in the cultivation line) in the field and seven basic units (14 plants in the cultivation line) under the plastic tunnel.Os objetivos do trabalho foram ajustar modelos de regressão não- -linear para a produção de feijão-de-vagem e identificar o tamanho da parcela com melhor poder de explicação e ajuste dos modelos. Foram utilizados dois ensaios a campo e dois em túnel plástico, realizados nas estações outono-inverno e primavera-verão. Os modelos ajustados foram o logístico e o de von Bertalanffy, para peso médio de vagens acumulado nas múltiplas colheitas e com diferentes tamanhos de parcela. Os modelos apresentaram estimativas semelhantes entre sí e as mesmas estimativas dos parâmetros em todas os casos de tamanho de parcela. O modelo logístico proporcionou estimativas mais próximas da realidade, apresentando melhor desempenho na descrição do comportamento do peso médio de vagens no decorrer do ciclo produtivo da cultura. Na estação sazonal outono-inverno parcelas de 14 UBs (28 plantas no sentido da linha de cultivo) a campo e de duas UBs (quatro plantas no sentido da linha de cultivo) em túnel plástico proporcionam uma boa qualidade no ajuste dos modelos. Na estação sazonal primavera-verão os tamanhos de parcela são de seis UBs (12 plantas no sentido da linha de cultivo) a campo e de sete UBs (14 plantas no sentido da linha de cultivo) em túnel plástico.The authors thank CAPES (Coordination of Improvement of Higher Education Personnel) for PhD scholarship, abroad, granted, process no BEX 1457/14-4.info:eu-repo/semantics/publishedVersio

Relations between zero-inflated variables in trials with horticultural crops

Certain characteristics of some vegetable crops allow multiple harvests during the production cycle; however, to our knowledge, no study has described the behavior of fruit production with progression of the production cycle in vegetable crops with multiple harvests that present data overdispersion. We aimed to characterize the data overdispersion of zero-inflated variables and identify the behavior of these variables during the production cycle of several vegetable crops with multiple harvests. Data from 11 uniformity trials were used without applying treatments; these comprise the database from the Experimental Plants Group at the Federal University of Santa Maria, Brazil. The trials were conducted using four horticultural species grown during different cultivation seasons, cultivation environments, and experimental structures. Although at each harvest, a larger number of basic units with harvest fruit was observed than units without harvest fruit, the basic unit percentage without fruit was high, generating an overdispersion within each individual harvest. The variability within each harvest was high and increased with the evolution of the production cycle of Capsicum annuum, Solanum lycopersicum var. cerasiforme, Phaseolus vulgaris, and Cucurbita pepo species. However, the correlation coefficient between the mean weight and number of harvest fruits tended to remain constant during the crop production cycle. These behaviors show that harvest management should be done individually, at each harvest, such that data overdispersion is reduced