Precision Agriculture最新文献

{"title":"A growing challenge: stakeholder perceptions of AI and ML applications in U.S. agriculture","authors":"J. Koch,A. S. Fox,R. Bhattarai,H. Jenkins-Smith,J. McFadden,A. Reinert,J. Sesmero,M. Z. Walkup,W. Jentner,D. Ebert","doi":"10.1007/s11119-026-10459-x","DOIUrl":"https://doi.org/10.1007/s11119-026-10459-x","url":null,"abstract":"Abstract Context The global population is expected to exceed ten billion by 2050 and food demand is projected to increase by up to 100% in the same timeframe. Agricultural management must adapt to meet the increasing global demands. Artificial intelligence (AI) and machine learning (ML) technologies can help the agricultural community respond to these needs. Aims An online survey and follow-up interviews were conducted to examine patterns of use, perceptions, and barriers among early adopting stakeholders regarding AI and ML. Methods The online survey with agricultural stakeholders (n=129) included questions regarding the participants’ views on incorporating AI and ML techniques into farming practices and individual follow-up interviews with agricultural stakeholders (n=10) were conducted to better understand their concerns toward technology use and adoption of AI-enabled tools and technologies. Key results Using a mixed-methods approach, four challenges to establishing AI-/ML-enabled technology in agriculture were identified. Namely, challenges related to (1) systems of systems (SoS), (2) sub-seasonal to seasonal weather (S2S) forecasts, (3) precision soil management, and (4) policy and economics. Each challenge was discussed in the context of recent literature. Conclusion Concerns were voiced clustered around four broad research themes. This brief communication brings the perspective of agricultural stakeholders to the discussion of the potential of AI/ML-enabled technology and the direction of their development in the agricultural sector. Implications Data collected in 2021, establish an important baseline for the early phase of AI/ML use in U.S. agriculture, enabling comparison of future perceptions and developments in the sector. Impact This brief communication describes a survey and follow-up interviews conducted with agricultural stakeholders on factors influencing their willingness and reluctance to incorporate AI and ML techniques into farming practices. The findings, summarized and discussed as four key challenges for AI and ML in the agricultural sector, have the potential to streamline research activities.","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"11 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149209313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhancing seeding efficiency using a computer vision system to monitor furrow quality in real-time","authors":"Sidharth Rai,Riley Sleichter,Aryan Singh Dalal,Rahul Harsha Cheppally,Ajay Sharda","doi":"10.1007/s11119-026-10461-3","DOIUrl":"https://doi.org/10.1007/s11119-026-10461-3","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"5 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149210429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AutoPlot grid: development and quantitative evaluation of an RTK-GNSS-based tool for automated breeding-plot delineation and UAV phenotyping data extraction","authors":"Aashvi Dua,Ajay Sharda","doi":"10.1007/s11119-026-10457-z","DOIUrl":"https://doi.org/10.1007/s11119-026-10457-z","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"32 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149209314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Barley head detection using UAV imagery and YOLOv10","authors":"Ameer Tamoor Khan,Saiful Azim,Signe Marie Jensen","doi":"10.1007/s11119-026-10468-w","DOIUrl":"https://doi.org/10.1007/s11119-026-10468-w","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"160 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149209316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reconstruction of within-field spatio-temporal variability from fixed and on-board proximal sensors: application to simulated leaf area data in viticulture","authors":"Vu Hoang Ha Pham,Florian Rançon,Jean-Pierre Da Costa","doi":"10.1007/s11119-026-10426-6","DOIUrl":"https://doi.org/10.1007/s11119-026-10426-6","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"14 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149210427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: MS-R outperforms RGB: Lightweight CYOLO-BiCNet enables efficient detection and storage optimization of cotton flowers","authors":"Mian Chen, Kai Ma, Xiaoli Geng, Daowu Hu, ShuaiPeng Fei, Shoupu He, Xiongming Du, Meiyan Shu, Shunfu Xiao, Rui Zhang, Yuntao Ma","doi":"10.1007/s11119-026-10450-6","DOIUrl":"https://doi.org/10.1007/s11119-026-10450-6","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"10 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149150542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multisensor data fusion from uav platforms: a robust approach for estimating photosynthetic capacity across vertical leaf layers in winter wheat","authors":"Dongwei Han, Shaolong Zhu, Muhammad Zain, Weijun Zhang, Zhaokai Ma, Xintong Lu, Jianliang Wang, Yuanyuan Zhao, Tao Liu, Chengming Sun","doi":"10.1007/s11119-026-10452-4","DOIUrl":"https://doi.org/10.1007/s11119-026-10452-4","url":null,"abstract":"Accurate assessment of photosynthetic capacity is essential for monitoring wheat growth and physiological processes, yet there is limited research on estimating the photosynthetic capacity at each leaf layer of winter wheat.","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"16 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086488","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The nexus of formulation, application and digital technologies: very-low volume formulations as an enabler for future small, automated, precision application vehicles","authors":"Malcolm A. Faers, Emilia Hilz, Sybille Lamprecht, Xu Wang, Feng Qi, Santiago Molinari","doi":"10.1007/s11119-026-10460-4","DOIUrl":"https://doi.org/10.1007/s11119-026-10460-4","url":null,"abstract":"Precision agriculture (PA) utilises data to enable more accurate application of agricultural inputs such as plant protection products (PPP) with precision and variable rate application (VRA) equipment. New evolving application technologies offer the ability to downsize this to small, automated vehicles with many advantages concerning cost, efficiency, sustainability, safety, and operator requirements. A new and important component of precision agriculture is the design of formulations: current generation PPP formulations were not designed for very-low volume application (VLV, 5–50 L/ha for 2D crops) and can lose performance at VLV. Formulations designed to perform at VLV have the potential to maintain or in some cases even increase performance at VLV and enable the application equipment to be downsized to small, automated vehicles such as unmanned ground vehicles (UGV) and unmanned aerial vehicles (UAV). This work investigates the performance of VLV optimised formulations from lab-scale to field-scale and how this may enable future VLV precision application of PPPs.","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"170 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149086489","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving field phenotyping accuracy in rice: a comparative study of smartphone image analysis and manual measurement","authors":"Jae-Ryoung Park, Hyeok-Jin Bak, Jung-Pil Suh, Mina Jin, Su-Kyung Ha, Gileung Lee, Kyeong Min Kang, Seung Young Lee, Hyun-Su Park, Woon-Ha Hwang, Wan-Gyu Sang, Hyun-Sook Lee","doi":"10.1007/s11119-026-10439-1","DOIUrl":"https://doi.org/10.1007/s11119-026-10439-1","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"6 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149130421","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Correction to: Using planetscope imagery to evaluate herbicide efficacy in maize (Zea mays) through post-application weed detection","authors":"Shlomi Aharon,Ran Lati,Hanan Eizenberg,Yafit Cohen","doi":"10.1007/s11119-026-10435-5","DOIUrl":"https://doi.org/10.1007/s11119-026-10435-5","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"61 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-10-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149090530","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}