Most Recent

Accurate seed singulation is critical for uniform crop establishment and yield optimization in precision agriculture. This study presents the development and evaluation of a Hall sensor-based Seed Miss Prevention System (SMPS) integrated into a long-...

The coffee leaf miner (Leucoptera coffeella) is a major pest of coffee crops and can cause significant economic losses. Early monitoring is essential to support decision-making for its control. This study aimed to evaluate the potential of fuzzy logi...

Monitoring groundcover diversity in vineyards is a complex task, often limited by the time and expertise required for accurate botanical identification. Remote sensing technologies and AI-based tools are still underutilized in this context, particula...

This study investigates the performance of unit-element heat exchangers. Particularly, it focuses on the characteristics of the local air temperature profiles and heat transfer performance of serpentine copper pipe heat exchangers with different diam...

Plant diseases are currently a major threat to agricultural economies and food availability, having a negative environmental impact. Despite being a promising line of research, current approaches struggle with poor cross-site generalization, limited...

Unmanned Aerial Vehicles (UAVs) have become essential instruments for precision agriculture and forest monitoring, offering rapid, high-resolution data collection over wide areas. This review synthesizes global advances (2015–2024) in UAV-deriv...

Agriculture faces growing pressure to optimize water use, particularly in woody perennial crops where irrigation systems are installed once and seldom redesigned despite changes in canopy structure, soil conditions, or plant mortality. Such static la...

The article presents a method for determining the irrigation requirements of crops based on soil moisture. The proposed approach enables scheduling irrigation at the most appropriate time of day by combining current soil moisture measurements with fo...

This study explores the potential of hyperspectral imaging combined with machine learning techniques to provide accurate and non-invasive methods for analyzing soil nutrient content in precision agriculture. Data were collected from agricultural regi...

Livestock farming represents one of the primary sources of ammonia (NH3) and greenhouse gas (GHG) emissions, including methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2), having a significant environmental impact. Reducing emissions and rec...