Precision Agriculture最新文献

{"title":"Robust identification of known and unknown weeds with crop center localization based on Open-set object detection","authors":"Lamin L. Janneh, Leilei He, Bryan Gilbert Murengam, Xiaojuan Liu, Mbemba Hydara, Man Xia, Rui Li, Yanxin Zhang, Longsheng Fu","doi":"10.1007/s11119-026-10431-9","DOIUrl":"https://doi.org/10.1007/s11119-026-10431-9","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"351 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148728731","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":"Precision monitoring of leaf area index and chlorophyll content of major field crops in Northern Europe using UAV remote sensing and radiative transfer modeling","authors":"Shangharsha Thapa, El Houssaine Bouras, Per-Ola Olsson, Erik Alexandersson, Thomas Roitsch, Johannes Albertsson, Axel Hörteborn, Lars Eklundh","doi":"10.1007/s11119-026-10403-z","DOIUrl":"https://doi.org/10.1007/s11119-026-10403-z","url":null,"abstract":"Purpose Long-term monitoring of crop biophysical and biochemical traits remains challenging in high-latitude regions due to short growing seasons, frequent cloud cover, and highly variable weather. In this context, unmanned aerial vehicles (UAVs) offer flexible, high-resolution observations, but their added value relative to low-cost proximal sensors and their effectiveness for radiative transfer model (RTM) inversion across diverse crop canopies remain insufficiently quantified. This study evaluated the potential of a two-band proximal spectral reflectance sensor (SRS) and a five-band multispectral UAV sensor for retrieving leaf area index (LAI), leaf chlorophyll content (LCC), and canopy chlorophyll content (CCC) using PROSAIL inversion across major crops in Northern Europe over two growing seasons (2023–2024). Methods and Results Two inversion approaches – look-up table (LUT) and artificial neural network (ANN) were applied to PROSAIL simulations. UAV–PROSAIL–ANN outperformed LUT-based inversion and SRS observations, achieving the highest accuracy for LAI (R <jats:sup>2</jats:sup> = 0.81–0.95; RMSE = 0.27–0.77 m <jats:sup>2</jats:sup> /m <jats:sup>2</jats:sup> ), followed by CCC (R <jats:sup>2</jats:sup> = 0.58–0.94; RMSE &lt; 60 μg/cm <jats:sup>2</jats:sup> ), while LCC remained less accurately estimated (R <jats:sup>2</jats:sup> = 0.26–0.78; RMSE &lt; 16 μg/cm <jats:sup>2</jats:sup> ). Across sensors and methods, retrieval accuracy decreased in the order of LAI, CCC, and LCC, reflecting the stronger spectral control of canopy structure compared to biochemical traits. Conclusions The UAV–PROSAIL–ANN framework effectively captured spatial and temporal variability in crop traits, producing canopy-scale maps consistent with field observations. These results demonstrate the robustness and scalability of hybrid PROSAIL–ANN inversion for high-latitude crop monitoring, while highlighting current limitations in biochemical trait retrieval using multispectral data.","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"3 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148728737","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":"Estimating height and leaf area index of ‘Tifton 85’ bermudagrass using UAV-derived vegetation indices under heterogeneous tropical field conditions","authors":"Samuel Vilela dos Santos, Ângelo Mantovani Amorim de Freitas Oliveira, Vitória Côrtes da Silva Souza de Oliveira, Júlia Ayres de Oliveira, Jéssica Mota Pimenta, Mariana de Oliveira Pereira, Ricardo Vilar Neves, Marcel Carvalho Abreu, Vinicius Nunes Henrique Silva, Anderson Gomide Costa, Gustavo Bastos Lyra","doi":"10.1007/s11119-026-10427-5","DOIUrl":"https://doi.org/10.1007/s11119-026-10427-5","url":null,"abstract":"Unmanned aerial vehicle (UAV)-based remote sensing can support non-destructive and spatial pasture monitoring, particularly in heterogeneous tropical systems. This study assessed the potential of UAV-derived vegetation indices (VIs) from the visible and near-infrared (NIR) spectrum to estimate canopy height and leaf area index (LAI) of ‘Tifton 85’ bermudagrass under conditions characterized with high spatial variability.","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"12 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148715809","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":"Dye-based field evaluation of an integrated high-precision smart sprayer for weed control in vegetables","authors":"Boyang Deng, Yuzhen Lu, Mark Siemens, Daniel Brainard","doi":"10.1007/s11119-026-10425-7","DOIUrl":"https://doi.org/10.1007/s11119-026-10425-7","url":null,"abstract":"<bold>Purpose</bold>","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"278 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148715810","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":"Image-based detection of rice straw moisture content in feed production using an attention-enhanced ResNet50 and two-stage regression","authors":"Xueru Zhu, Haojun Xie, Yongkang Luo, Chao Li, Baohua Zhang, Wenhao Tang, Hua Li","doi":"10.1007/s11119-026-10419-5","DOIUrl":"https://doi.org/10.1007/s11119-026-10419-5","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"13 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-08-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148682212","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":"A beam-informed framework for Leaf Area Density estimation from Mobile Terrestrial Laser Scanning","authors":"Harold Murcia, Simon Lacroix","doi":"10.1007/s11119-026-10406-w","DOIUrl":"https://doi.org/10.1007/s11119-026-10406-w","url":null,"abstract":"Accurate estimation of Leaf Area Density (LAD) at fine spatial scales remains challenging across a wide range of canopy architectures and foliage configurations, due to occlusion, variable sampling density, and complex laser beam–canopy interactions. This study introduces a beam-aware learning framework to enrich Mobile Terrestrial Laser Scanning (MLTS) derived point clouds point clouds with sensor-centric descriptors, enabling fine-scale canopy density characterisation.","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"18 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148682206","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":"German farmer viewpoints on field robots–an application of q methodology","authors":"Marius Michels, Oliver Mußhoff","doi":"10.1007/s11119-026-10421-x","DOIUrl":"https://doi.org/10.1007/s11119-026-10421-x","url":null,"abstract":"Context Field robots are promoted to address labour shortages and improve the sustainability and productivity of arable farming. Existing research largely frames farmer attitudes along a continuum of acceptance using predefined constructs, leaving the rationalities shaping evaluations unexplored. Aims This exploratory study identifies distinct subjective viewpoints on field robots within a purposive sample of German arable farmers and reconstructs the evaluation logics shaping their attitudes. Methods Q methodology was applied with twenty German conventional farmers who sorted 30 statements covering economic, environmental, and social dimensions in January 2026. By-person factor analysis was used to identify shared viewpoints, complemented by post-sort qualitative explanations. Key Results Three distinct viewpoints emerged: a pragmatic, integration-oriented perspective centred on economic viability and operational integration; a technology-affirmative but cost-sensitive modernization perspective emphasising demonstrable agronomic benefits and practical validation; and an ecologically selective, control-oriented perspective stressing technological understanding, operational autonomy, and conditional support for specific applications. Only two of thirty statements qualified as consensus. Conclusion Within this sample, identical evaluative dimensions (economic viability, environmental benefits, or labour effects) did not carry the same meaning across farmer groups but were embedded in different evaluation logics. These preliminary findings suggest that farmer heterogeneity cannot be reduced to differing acceptance levels alone but reflects qualitatively distinct evaluative frameworks. Implications and Impacts Policies, advisory, and innovation strategies fostering field robot adoption should reflect these distinct decision logics rather than assume a uniform user group. Given the small purposive sample, these implications are preliminary and warrant verification in larger, representative studies.","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"42 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148586787","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":"Linking organic fertilizer properties to in-season N dynamics using multispectral UAV imagery","authors":"Matthias Diener, L. Agostini, F. Argento, E. K. Bünemann, A. Walter, J. Mayer, F. Liebisch","doi":"10.1007/s11119-026-10414-w","DOIUrl":"https://doi.org/10.1007/s11119-026-10414-w","url":null,"abstract":"Purpose Alignment of crop nitrogen (N) demand with N supply is crucial to improve N use efficiency of organic fertilizers whose N is largely bound organically. This study aimed to evaluate the potential of unmanned aerial vehicle (UAV)-based multispectral imagery to monitor in-season N uptake and to assess how different organic fertilizers affect N dynamics. Methods A field trial in Wallbach, Switzerland, compared untreated cattle slurry, anaerobically digested slurry, solid digestate, a mineral N control, and a zero-N control over two winter cereal seasons. UAV-acquired multispectral data were combined with environmental data (weather, soil and fertilizer) to model dry matter, N concentration, N uptake and the nitrogen nutrition index using random forest regression. Results The random forest models combining UAV-based multispectral imagery with environmental data showed good performance in predicting in-season N uptake of winter wheat (R <jats:sup>2</jats:sup> = 0.85, RMSE = 13.9 kg N ha <jats:sup>− 1</jats:sup> ) and of winter barley (R² = 0.78, RMSE = 9.3 kg N ha <jats:sup>− 1</jats:sup> ). Predicted N dynamics revealed transient N uptake maxima in organic treatments before fertilization, likely due to legacy fertilizer effects. Post-fertilization, N uptake increased most under mineral fertilization. N uptake dynamics were affected by fertilizer properties, with low C/N ratio and high NH <jats:sub>4</jats:sub> -N proportion showing stronger effects. Conclusion Highly temporal UAV-based multispectral imagery captures in-season N uptake dynamic and reveals differences in fertilizer N release caused by quality differences of organic fertilizers. These insights support optimized fertilizer application for better synchronization of N mineralization with crop demand.","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"34 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148586788","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":"A dual-driven framework integrating remote sensing and spatial interpolation for mapping soil organic matter under straw cover","authors":"Xuzhou Qu, Zhitong Zhang, Jianwei Wu, Xiaohe Gu, Jingping Zhou, Chunjiang Zhao, Yanglin Cui, Dongfang Shan","doi":"10.1007/s11119-026-10417-7","DOIUrl":"https://doi.org/10.1007/s11119-026-10417-7","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"15 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148586789","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":"Evaluating three cameras for cotton plant height estimation using UAS-derived point clouds","authors":"Chenghai Yang, Charles P.-C. Suh, Bradley K. Fritz","doi":"10.1007/s11119-026-10418-6","DOIUrl":"https://doi.org/10.1007/s11119-026-10418-6","url":null,"abstract":"","PeriodicalId":20423,"journal":{"name":"Precision Agriculture","volume":"37 1","pages":""},"PeriodicalIF":6.2,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148538166","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}