Evaluation of Weed Emergence Model AlertInf for Maize in Soybean

Abstract

AlertInf is a recently developed model to predict the daily emergence of three important weed species in maize cropped in northern Italy (common lambsquarters, johnsongrass, and velvetleaf). Its use can improve the effectiveness and sustainability of weed control, and there has been growing interest from farmers and advisors. However, there are two important limits to its use: the low number of weed species included and its applicability only to maize. Consequently, the aim of this study was to expand the AlertInf weed list and extend its use to soybean. The first objective was to add another two important weed species for spring-summer crops in Italy, barnyardgrass and large crabgrass. Given that maize and soybean have different canopy architectures that can influence the interrow microclimate, the second objective was to compare weed emergence in maize and soybean sown on the same date. The third objective was to evaluate if AlertInf was transferable to soybean without recalibration, thus saving time and money. Results showed that predictions made by AlertInf for all five species simulated in soybean were satisfactory, as shown by the high efficiency index (EF) values, and acceptable from a practical point of view. The fact that the algorithm used for estimating weed emergence in maize was also efficient for soybean, at least for crops grown in northeastern Italy with standard cultural practices, encourages further development of AlertInf and the spread of its use.

A comparative study between nonlinear regression and nonparametric approaches for modelling Phalaris paradoxa seedling emergence

“…Timing optimisation can be facilitated by the development of more efficient predictive weed emergence models (Masin et al, 2014). Parametric nonlinear regression models may not be accurate if environmental conditions vary significantly from the original conditions in which the experiment was conducted (e.g.…”

Variability in seedling emergence for European and North American populations ofAbutilon theophrasti

“…is an important weed spreading worldwide in spring–summer crops with a relevant economic impact in many European countries (Recasens et al ., ). Several studies have been conducted on different aspects of A. theophrasti biology and ecology, such as germination (Dorado et al ., ; Masin et al ., ), seedling emergence (Dorado et al ., ; Masin et al ., , ), seedbank dynamics (Liebman et al ., ) and competition (Vrbnicanin et al ., ). Contrasting information has been reported about the intra‐specific variability of A. theophrasti germination and seedling emergence.…”

Modelagem matemática do fluxo de emergência de plantas daninhas: ferramenta para decisão no manejo de cultivos

“…A obtenção dos parâmetros a campo pode ser determinada de várias formas, como o monitoramento por datalogger (Roman et al, 2000;Masin et al, 2012Masin et al, , 2014, estações meteorológicas (Roman et al, 2000;Spokas e Forcella, 2009;Werle et al, 2014a) e por informações de satélites. Entretanto, a maneira de obtenção de cada parâmetro necessita processos de correlações e calibração.…”

“…Entretanto, o maior fluxo de emergência de plantas daninhas ocorre aproximadamente um mês após a semeadura (Masin et al, 2012) e, o mesmo modelo utilizado para prever emergência de plantas daninhas na cultura do milho pode ser utilizado para a cultura da soja (Masin et al, 2014).…”