A Bayesian approach to the analysis of dose-response data: estimating natural survivorship without Abbott's correction and inclusion of overdispersion estimates.

We assessed the utility of a Bayesian analysis of dose-mortality curves using probit analysis. A Bayesian equivalent of a conventional single population probit analysis using Abbott's correction demonstrated the ability of the Bayesian model to recover parameters from generative data. We then developed a model that removed Abbott's correction and estimated natural survivorship as part of the overall model fitting process.

Multispectral Images for Drought Stress Evaluation of Arabica Coffee Genotypes Under Different Irrigation Regimes.

The advancement of digital agriculture combined with computational tools and Unmanned Aerial Vehicles (UAVs) has opened the way to large-scale data collection for the calculation of vegetation indices (VIs). These vegetation indexes (VIs) are useful for agricultural monitoring, as they highlight the inherent characteristics of vegetation and optimize the spatial and temporal evaluation of different crops. The experiment tested three coffee genotypes (Catuaí 62, E237 and Iapar 59) under five water regimes: (1) FI 100 (year-round irrigation with 100% replacement of evapotranspiration), (2) FI 50 (year-round irrigation with 50% evapotranspiration replacement), (3) WD 100 (no irrigation from June to September (dry season) and, thereafter, 100% evapotranspiration replacement), (4) WD 50 (no irrigation from June to September (water stress) and, thereafter, 50% evapotranspiration replacement) and (5) rainfed (no irrigation during the year).

Exploring the impact of cover crops in integrated pest management: pest and natural enemies population dynamics in no-tillage cotton production.

Conservation agriculture plays an important role in the sustainability of production systems, notably for globally significant crops such as cotton. This study explores the integration of the no-tillage system (NTS) with integrated pest management (IPM) by incorporating cover crops. The aim is to assess the impact of these living or dead covers on the management of insect populations, the indices diversity of phytophagous insects and natural enemies, and to investigate the population fluctuation of these arthropods, considering a variety of crops in the NTS before and after cotton planting.

Estimation of predation rate and handling time of boll weevil larvae by Marava arachidis (Dermaptera: Labiidae) using different mathematical methods.

Anthonomus grandis grandis (Coleoptera: Curculionidae) is a pest with a large potential for destruction in cotton crops, causing damage to the cotton reproductive structures. The earwig Marava arachidis (Dermaptera: Labiidae), is an important reference as a predator in several crops and being easy to rear in the laboratory. To analyze the potential biocontrol of M.