Precision Agriculture

Abstract Purpose Reducing human labor requirements through crop robots is assumed to positively affect the economy of smaller fields. Strip cropping is a mechanizable approach to creating smaller subfields and increasing biodiversity but currently suffers from economic pressures. To investigate whether robots could present a labor-saving solution in this production system, two strip cropping fiel…

Abstract Context Downy mildew, caused by Plasmopara viticola , remains one of the most damaging diseases affecting grapevines, especially in humid viticultural regions such as the “Vinhos Verdes” in northern Portugal. Traditional detection relies on visual inspection and laboratory techniques, which are subjective and reactive, often delaying effective intervention. Aims This study aims to evalua…

Abstract Background: The stink bug complex is one of the most damaging pests of soybean, reducing yield and seed quality. Genetic resistance remains the most sustainable and effective management strategy, but its quantitative inheritance and labor-intensive field phenotyping make its implementation in breeding programs challenging. Objective: This study explored high-throughput phenotyping (HTP) …

Abstract Purpose Accurate and early prediction of crop yield is essential for agricultural management, economic planning, and market stability, particularly for high-value products such as wine. This study presents a multi-temporal modeling framework to predict grapevine yield (in kilograms) in the province of Cádiz, Spain, a region with a deep-rooted winemaking heritage. Methods Using a 12-year …

Abstract This paper presents optimised web services for automatic assistance systems designed for precision pesticide application. By automating the planning, application, documentation and evaluation stages of the pesticide application process, the study seeks to ease the workload on farmers, supporting practical implementation of precision spraying workflows. Specifically, the study addresses t…

Abstract Purpose Farmers in Australia are currently facing profound challenges due to soil degradation, biodiversity loss, climate change, biosecurity threats, and difficulties in securing labour; farmers elsewhere face similar challenges. Increased use of robotics and artificial intelligence (AI) has been proposed as a possible solution to these problems. These technologies have the potential to…

Abstract Purpose Viticulture is one of the most input-intensive agricultural sectors, in which the adoption of precision technologies could contribute significantly to reduce environmental impacts and operating costs. Previous studies have primarily focused on technical aspects, often examining individual farm operations or specific technologies using hypothetical data, rather than assessing econ…

Overcomes spectral-band limits of multisensory PLSR. Feature engineering integrates Sentinel-2 spectra, VIs, and textures for seasonal LAI. LASSO-VIF-PLSR boosts accuracy, notably spring and autumn. Universal PLSR model captures cross-seasonal LAI dynamics. The empirical retrieval of leaf area index (LAI) through multispectral remote sensing typically relies more on vegetation indices (VIs) than …

Abstract Purpose The discrimination of grapevine cultivars is an important yet underexploredtopic in precision viticulture. This study evaluated three aspects of grapevinecultivar classification and model training strategies: (1) the influence ofseasonal variability and data collection strategy; (2) model generalisabilityacross sample types; and (3) the combined impact of temporal and sample-type…

Abstract Purpose The primary goal of this research was to develop an innovative in-season nitrogen (N) recommendation strategy for corn ( Zea mays L.) using stacking ensemble machine learning (ML) and multi-source data fusion. Methods Forty-nine site-years of N rate experiments conducted across the U.S. Corn Belt were used to evaluate the performance of five individual ML algorithms (Random Fores…

Abstract Purpose Sustainable agriculture requires both high and stable crop yields. Whilegenotype-environment-management (G×E×M) interactions influence yield stability, implementingsuch understanding into practical applications demands better analytical tools. Yield StabilityZones (YSZ) effectively identify stable and unstable production areas, yet their implementationhas been constrained by data…