Nicola Furnitto , Juan Miguel Ramírez-Cuesta , Diego S. Intrigliolo , Giuseppe Todde , Sabina Failla
{"title":"Remote sensing for pasture biomass quantity and quality assessment: Challenges and future prospects","authors":"Nicola Furnitto , Juan Miguel Ramírez-Cuesta , Diego S. Intrigliolo , Giuseppe Todde , Sabina Failla","doi":"10.1016/j.atech.2025.101057","DOIUrl":null,"url":null,"abstract":"<div><div>Optimizing pasture use through careful management is critical to ensure the economic and environmental sustainability of pasture-based agriculture. Maximizing grass utilization and accurately measuring grass quantity and quality by adopting precision agriculture technologies, including estimates from satellite or unmanned aerial vehicles (UAVs), are key aspects to improve production efficiency and reducing environmental impact. With these goals, the review explores the crucial role of biomass quality and assessment estimation in pasture-based agricultural practices, with a focus on the potential offered by remote sensing technologies. This review examined recent advances in biomass and grassland quality assessment, highlighting the most widely used methodologies, remaining challenges and future prospects. The analysis focused particularly on applications of UAV and satellite platforms, discussing the advantages and limitations of the different techniques. Their and applications including machine learning (ML) technologies. A deep analysis of the main indices, electromagnetic regions and ML approaches utilized was also addressed, distinguishing among those intended to biomass quantity and quality assessment. Through the integration of innovative technologies and improved measurement protocols, the full potential of more sustainable and productive pasture-based agriculture can be realised, ensuring improved animal productivity and economic viability for farmers. These advances will pave the way for more effective management practices and contribute significantly to the global effort toward more sustainable agricultural systems.</div></div>","PeriodicalId":74813,"journal":{"name":"Smart agricultural technology","volume":"12 ","pages":"Article 101057"},"PeriodicalIF":6.3000,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Smart agricultural technology","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2772375525002904","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"AGRICULTURAL ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
Optimizing pasture use through careful management is critical to ensure the economic and environmental sustainability of pasture-based agriculture. Maximizing grass utilization and accurately measuring grass quantity and quality by adopting precision agriculture technologies, including estimates from satellite or unmanned aerial vehicles (UAVs), are key aspects to improve production efficiency and reducing environmental impact. With these goals, the review explores the crucial role of biomass quality and assessment estimation in pasture-based agricultural practices, with a focus on the potential offered by remote sensing technologies. This review examined recent advances in biomass and grassland quality assessment, highlighting the most widely used methodologies, remaining challenges and future prospects. The analysis focused particularly on applications of UAV and satellite platforms, discussing the advantages and limitations of the different techniques. Their and applications including machine learning (ML) technologies. A deep analysis of the main indices, electromagnetic regions and ML approaches utilized was also addressed, distinguishing among those intended to biomass quantity and quality assessment. Through the integration of innovative technologies and improved measurement protocols, the full potential of more sustainable and productive pasture-based agriculture can be realised, ensuring improved animal productivity and economic viability for farmers. These advances will pave the way for more effective management practices and contribute significantly to the global effort toward more sustainable agricultural systems.