ABSTRACT
Agronomy research traditionally relies on small, controlled trial plots, which may not accurately represent the complexities and variabilities found in larger, real-world settings. To address this gap, we introduce a Bayesian methodology for the analysis of yield monitor data, systematically collected across extensive agricultural landscapes during the 2020/21 and 2021/22 growing seasons. Utilizing advanced yield monitoring equipment, our method provides a detailed examination of the effects of green manure on wheat yields in a real-world context. The results from this comprehensive analysis reveal significant insights into the impact of green manure application on wheat production, demonstrating enhanced yield outcomes across varied landscapes. This evidence suggests that the Bayesian approach to analyzing yield monitor data can offer more precise and contextually relevant information than traditional experimental designs. This research underscores the value of integrating large-scale data analysis techniques in agronomy, moving beyond small-scale trials to offer a broader, more accurate perspective on agricultural practices. The adoption of such methodologies promises to refine farming strategies and policies, ultimately leading to more effective and sustainable agricultural outcomes. The inclusion of a Python script in the appendix illustrates our analytical process, providing a tangible resource for replicating and extending this research within the agronomic community.
ABSTRACT
BACKGROUND: Rape stem weevil (Ceutorhynchus napi Gyll.) and cabbage stem weevil (C. pallidactylus Marsh.) can cause significant yield losses to oilseed rape (Brassica napus L.), and chemical control is often needed to protect crops from these pests. The efficacy of six insecticides, chlorpyriphos + cypermethrin, bifenthrin, alpha-cypermethrin, pirimiphos-methyl, thiacloprid and tau-fluvalinate, was tested in a 4 year field trial. Besides the standard efficacy analysis expressed through the number of larvae per stem, a damage rating scale was introduced and modelled using a regression model for ordinal categorical data. RESULTS: Compared with the control, expressed through damage rating and larval number, treatments with chlorpyriphos + cypermethrin and bifenthrin, showed higher efficacy in the control of stem weevils compared with alpha-cypermethrin and pirimiphos-methyl. The lowest efficacy was observed in treatments with tau-fluvalinate and thiacloprid. CONCLUSION: This study showed that a combined efficacy evaluation expressed through both damage rating scale and the count of larvae, supported by an ordinal regression model for data analysis, is indispensable for obtaining accurate results. © 2017 Society of Chemical Industry.
