Survival analysis: a tool in the study of post-harvest diseases in peaches

Abstract

RESUMO Análise de sobrevivência como ferramenta no estudo de doenças na pós-colheita de pêssegosA análise de sobrevivência é aplicada quando o tempo até a ocorrência de um evento for o objeto de interesse. Em doenças de plantas, dados dessa natureza são rotineiramente coletados, embora aplicações do método sejam pouco comuns. O objetivo deste trabalho foi utilizar dois estudos de doenças em pós-colheita de pêssegos, considerando-se safras conjuntamente e a existência de efeito aleatório, compartilhado por frutos de uma mesma árvore, para descrever as principais técnicas em análise de sobrevivência. Aplicaram-se a técnica não paramétrica de Kaplan-Meier e a estatística log-rank, além do modelo semiparamétrico de riscos proporcionais, de Cox, para estimar o efeito de cultivares e do número de dias após a floração plena sobre a sobrevivência ao sintoma de podridão parda e sobre o risco instantâneo de expressá-lo, em duas safras consecutivas. A análise conjunta com efeito basal, variando entre safras, e a verificação do efeito de árvore como fator de agrupamento com efeito aleatório, mostraramse adequadas para interpretar o fenômeno avaliado (doença) e podem ser ferramentas importantes para substituir ou complementar as análises convencionais, respeitando-se as naturezas da variável e do fenômeno.Palavras-chave: tempo-ocorrência, Kaplan-Meier, regressão de Cox, pêssego.Survival analysis is applied when the time until the occurrence of an event is of interest. Such data are routinely collected in plant diseases, although applications of the method are uncommon. The objective of this study was to use two studies on post-harvest diseases of peaches, considering two harvests together and the existence of random effect shared by fruits of a same tree, in order to describe the main techniques in survival analysis. The nonparametric Kaplan-Meier method, the log-rank test and the semi-parametric Cox's proportional hazards model were used to estimate the effect of cultivars and the number of days after full bloom on the survival to the brown rot symptom and the instantaneous risk of expressing it in two consecutive harvests. The joint analysis with baseline effect, varying between harvests, and the confirmation of the tree effect as a grouping factor with random effect were appropriate to interpret the phenomenon (disease) evaluated and can be important tools to replace or complement the conventional analysis, respecting the nature of the variable and the phenomenon.

Modelling Survival Time to Symptom Expression and Death Among Sweet Potato Crosses Inoculated with Fusarium oxysporum f.sp. batatas

“…These values were underestimates because the Kaplan-Meier nonparametric estimation method was restricted to the largest time to symptom expression while in reality there were censored individuals. Nesi et al, (2015) also reported having encountered limitations of the Kaplan-Meier test when analysing post-harvest diseases of peaches.…”

“…These results confirm the nonparametric results that the two types of crosses belong to different distributions. The likelihood ratio tests (Giroux et al, 2016) compared parametric fits of the simpler, or restricted, models with the more complicated, or unrestricted Generalized gamma model (Nesi et al, 2015). The hypothesis tested was equality of restricted and unrestricted models.…”

“…Survival models have been formulated using nonparametric and parametric survival and hazard analysis techniques (Nesi et al, 2015;Minzat et al, 2018;Rathod et al, 2020;Mills et al, 2021). Survival and hazard functions have also previously been described by Benali et al, (2015) and Nsobinenyui et al, (2022) as an effort to analyse survival times using assumed distributions.…”

“…Survival analysis, has so far, been rarely used to examine time-to-event data generated by plant pathologists (Nesi et al, 2015) and in agriculture generally (Singh and Dlamini, 2021). This scenario is more pronounced in food crops as evidenced by the dearth of literature involving survival analysis of events in crop plants.…”