Advancement in artificial intelligence for on-farm fruit sorting and transportation

Abstract

On-farm sorting and transportation of postharvest fruit include sorting out defective products, grading them into categories based on quality, distributing them into bins, and carrying bins to field collecting stations. Advances in artificial intelligence (AI) can speed up on-farm sorting and transportation with high accuracy and robustness and significantly reduce postharvest losses. The primary objective of this literature review is to provide an overview to present a critical analysis and identify the challenges and opportunities of AI applications for on-farm sorting and transportation, with a focus on fruit. The challenges of on-farm sorting and transportation were discussed to specify the role of AI. Sensors and techniques for data acquisition were investigated to illustrate the tasks that AI models have addressed for on-farm sorting and transportation. AI models proposed in previous studies were compared to investigate the adequate approaches for on-farm sorting and transportation. Finally, the advantages and limitations of utilizing AI have been discussed, and in-depth analysis has been provided to identify future research directions. We anticipate that this survey will pave the way for further studies on the implementation of automated systems for on-farm fruit sorting and transportation.

Tecnologías innovadoras para el manejo de frutales, énfasis en caducifolios, aguacate y frutas tropicales

“…Los algoritmos analizan datos de sensores y factores ambientales para ofrecer recomendaciones sobre el manejo y la distribución, minimizando pérdidas y garantizando que las frutas lleguen a los consumidores en su mejor estado. En una investigación desarrollada recientemente por (Zhou et al, 2023) se revisaron una serie de aplicaciones de la inteligencia artificial (IA) en la clasificación y el transporte de frutas en la explotación agrícola, además, se analizaron los desafíos que enfrentan los métodos manuales tradicionales, como los altos costos de mano de obra y la menor eficiencia. Finalmente, se destacan los beneficios de los sistemas basados en IA, incluida una mayor eficiencia de producción, menores pérdidas postcosecha y mejores instalaciones y niveles de seguridad para las tareas humanas.…”

Advancing sustainability in the food and nutrition system: a review of artificial intelligence applications

“…AI technologies, encompassing computer vision, machine learning, and robotics, have helped to automate and enhancing this process. By enabling real-time inspection, classification, and sorting of food products, AI minimizes human errors, reduces labor costs, curbs wastage, and concurrently boosts productivity, profitability, and customer satisfaction ( 54–56 ).…”

Rating Pome Fruit Quality Traits Using Deep Learning and Image Processing

“…Computer vision is already used in the agriculture sector and specifically the pome fruit industry. Notably, applications include the development of image based fruit sorting machines (Rehkugler & Throop, 1986; Wen & Tao, 1999), hyperspectral imaging for fruit quality (Çetin et al, 2022; Nicolaï et al, 2006), robotic harvesting equipment (Bu et al, 2022; Davidson et al, 2016; Hua et al, 2023), and more (Lorente et al, 2013; Pu et al, 2015; Zhou et al, 2023). Importantly, early detection of issues that affect fruit quality is critical for management strategies and minimizing food waste throughout the pre- and postharvest supply chain.…”