Agricultural Engineering Papers
A SAFER model for accurately estimating actual evapotranspiration in sugarcane using Sentinel-2
Last Updated: junio 11, 2025Accurate estimation of actual evapotranspiration (ETa) is essential for sustainable water management. This study was conducted from 2022 to 2024 in the Cauca River Valley of Colombia, over one sugarcane growing cycle, using Sentinel-2 satellite images to estimate ETa with the SAFER (Simple Algorithm for Evapotranspiration Retrieving) model.
Actual harvester extractor cane loss: the elephant we can no longer ignore
Last Updated: junio 11, 2025Since mechanised harvesting of sugarcane became established in the 1970s, farmers, manufacturers and researchers have been attempting to improve harvester performance and optimise harvest efficiency. The move to green-cane harvesting and the introduction of pneumatic extractor systems on sugarcane harvesters both increased cane loss significantly.
Challenges farmers face in farming with data
Last Updated: junio 11, 2025Digital agriculture (DA) is a combination of technologies spanning devices sensing the environment from a close distance or thousands of kilometres in the skies to chips monitoring crop-production systems. Underpinned by the Internet of Things (IoT), the technology is advancing traditional agriculture production systems into data-driven smart farming, promising substantive benefits regarding improving efficiency, effectiveness and productivity. DA relies heavily on the data sources and techniques used to collect it. This data is then organized and analyzed in agricultural data warehouses.
Chopping quality in harvesting: its relationship with sucrose loss and operational efficiency
Last Updated: junio 11, 2025In the last decade, green-cane harvesting in Colombia has significantly increased, reaching 75% in 2023. This growth has emphasized the need to monitor its impact on sucrose losses and operational efficiency. A key factor in harvesting quality is the condition of the billets, which are classified into sound, damaged, and mutilated.
Climate change and adaptation in the sugar agroindustry: 17 case studies of best practices from Latin America
Last Updated: junio 11, 2025The Latin American sugar agroindustry plays a crucial role in economic development of member countries, yet its sustainability challenges need ongoing improvements in environmental management, resource efficiency, and innovation. This paper documents and analyzes 17 case studies of best practices implemented by the members of the Association of Latin American Sugar Producers (UNALA), focusing on environmental and economic sustainability within the framework of the Sustainable Development Goals (SDGs).
Data-driven agricultural management and technology use for risk assessment in sugarcane crop management
Last Updated: junio 11, 2025The objective of this paper was to describe the integration of information, algorithms, and technologies for quantitative risk assessment through forecasts, with the aim of optimizing agricultural management and achieving productivity and unit cost targets. Since 2022, at Azucarera Nacional, located in the central region of Panama, innovations in work planning and budgeting have been implemented, based on long-term climate and production forecasts.
Effect of soil-tillage practices on water use in irrigated sugarcane cultivation
Last Updated: junio 11, 2025In the Valle del Río Cacua, most of the sugarcane area is irrigated using surface irrigation. This is applied up to five times per crop cycle, using between 1,200 and 2,500 m³/ha, according to environmental factors, crop stage, soil characteristics, and preparation practices. With the current reduction in water availability, there has been a push to find strategies to optimize the soil-water relationship and improve surface irrigation efficiency.
Integration of multispectral and SAR data with machine-learning algorithms for real-time monitoring and forecasting of sugarcane ripening
Last Updated: junio 11, 2025Efficient harvest timing is critical for optimizing sugarcane yield and resource use. This study integrates multispectral and Synthetic Aperture Radar (SAR) satellite imagery with advanced machine-learning algorithms to develop a scalable model for real-time monitoring and forecasting of sugarcane ripening. By tracking the temporal evolution of physiological phenomena measured through neural networks over satellite imaging, the NAX ripening model enables precise prediction of optimal harvest windows.
Irrigation management strategies for improving water-use efficiency in sugarcane
Last Updated: junio 11, 2025Water resources limitation is a major challenge faced by farmers in Iran. To address this issue, sugarcane industries must find ways to increase irrigation water-use efficiency. Currently, sugarcane is irrigated using a furrow irrigation system through gated pipes. A study was conducted at Karun Agro, Industry to explore different strategies for improving water-use efficiency using several experiments.
Potential for the use of machine learning in sugarcane production in Thailand: a review
Last Updated: junio 11, 2025Even though sugarcane is a major agricultural crop in Thailand, Thai sugarcane growers have recently endured high production costs with reduced income. For this reason, there have been many studies to assist farmers to achieve greater efficiencies on-farm. Recently, unmanned aerial vehicle (UAV) technology and machine learning (ML) have been introduced into agriculture.