Electronic Resource
Multiscale assessment of ground, aerial and satellite spectral data for monitoring wheat grain nitrogen content
| العنوان: | Multiscale assessment of ground, aerial and satellite spectral data for monitoring wheat grain nitrogen content |
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| المؤلفون: | Agencia Estatal de Investigación (España), Ministerio de Ciencia, Innovación y Universidades (España), Diputación Foral de Navarra, Generalitat de Catalunya, European Commission, Segarra, Joel, Rezzouk, Fatima Zahra, Aparicio, Nieves, González-Torralba, Jon, Aranjuelo, Iker, Gracia-Romero, Adrian, Araus, Jose Luis, Kefauver, Shawn C. |
| بيانات النشر: | Elsevier 2023-12-01 |
| نوع الوثيقة: | Electronic Resource |
| مستخلص: | Wheat grain quality characteristics have experienced increasing attention as a central factor affecting wheat end-use products quality and human health. Nonetheless, in the last decades a reduction in grain quality has been observed. Therefore, it is central to develop efficient quality-related phenotyping tools. In this sense, one of the most relevant wheat features related to grain quality traits is grain nitrogen content, which is directly linked to grain protein content and monitorable with remote sensing approaches. Moreover, the relation between nitrogen fertilization and grain nitrogen content (protein) plays a central role in the sustainability of agriculture. Both aiming to develop efficient phenotyping tools using remote sensing instruments and to advance towards a field-level efficient and sustainable monitoring of grain nitrogen status, this paper studies the efficacy of various sensors, multispectral and visible red–greenblue (RGB), at different scales, ground and unmanned aerial vehicle (UAV), and phenological stages (anthesis and grain filling) to estimate grain nitrogen content. Linear models were calculated using vegetation indices at each sensing level, sensor type and phenological stage. Furthermore, this study explores the up-scalability of the best performing model to satellite level Sentinel-2 equivalent data. We found that models built at the phenological stage of anthesis with UAV-level multispectral cameras using red-edge bands outperformed grain nitrogen content estimation (R2 = 0.42, RMSE = 0.18%) in comparison with those models built with RGB imagery at ground and aerial level, as well as with those built with widely used ground-level multispectral sensors. We also demonstrated the possibility to use UAV-built multispectral linear models at the satellite scale to determine grain nitrogen content effectively (R2 = 0.40, RMSE = 0.29%) at actual wheat fields. |
| مصطلحات الفهرس: | Grain nitrogen content, Phenotyping, Remote sensing, Sentinel-2, Wheat, artículo |
| URL: | Publisher's version The underlying dataset has been published as supplementary material of the article in the publisher platform at https://doi.org/10.1016/j.inpa.2022.05.004 Sí info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2019-106650RB-C21/ES/FENOTIPEADO DE TRIGO A DIFERENTES ESCALAS: DEL IDEOTIPO A LA ADAPTACION REGIONAL: RENDIMIENTO Y ESTABILIDAD info:eu-repo/grantAgreement/AEI//RYC-2019-027818-I |
| الاتاحة: | Open access content. Open access content https://creativecommons.org/licenses/by/4.0 openAccess |
| ملاحظة: | English |
| Other Numbers: | CTK oai:digital.csic.es:10261/347117 Information Processing in Agriculture 10(4): 504-522 (2023) 2214-3173 10.1016/j.inpa.2022.05.004 2-s2.0-85131147172 1431962241 |
| المصدر المساهم: | CSIC From OAIster®, provided by the OCLC Cooperative. |
| رقم الانضمام: | edsoai.on1431962241 |
| قاعدة البيانات: | OAIster |
| الوصف غير متاح. |