多光谱红边指数能准确估算冬季覆盖作物氮素含量

IF 2 3区 农林科学 Q2 AGRONOMY
A. Thieme, J. Jennewein, W. D. Hively, B. T. Lamb, A. K. Whitcraft, S. B. Mirsky, S. C. Reberg-Horton, C. Justice
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引用次数: 0

摘要

冬季覆盖作物减少了农业系统的侵蚀和养分流失。尽管谷物覆盖作物可以减少田间硝酸盐淋失50%-95%,但这种减少的幅度在田间和田间之间存在差异,这使得在大空间范围内监测覆盖作物对硝酸盐淋失的影响具有挑战性。利用红边波段的卫星遥感已被证明可以有效地估算生育后期封闭冠层作物的氮素含量(kg ha - 1)。在这项研究中,我们利用2018年至2023年在马里兰州收集的1627个破坏性样本,评估了来自Sentinel-2图像的15个光谱指数,以估计谷物覆盖作物的N浓度(%)和含量(kg ha - 1)。氮含量为0.1 ~ 214.7 kg ha - 1,氮浓度为0.6% ~ 5.5%。所考虑的15个指标对N浓度的预测效果较差(相对值R2 = 0.089,均方根误差[RMSE] = 0.802%),但对N含量(生物量× N浓度)的预测效果较好。δ红边(ΔRE)是N含量的最佳预测因子(R2 = 0.748, RMSE = 13.10 kg ha - 1,交叉验证,80%训练和20%测试分割迭代100次),使用破坏性采样(N = 1110)±4天内收集的图像样本。研究结果表明,较长的红边波长(783 nm和740 nm)比较短的红边波长更适合估算谷物覆盖作物的氮含量,而较短的红边波长对生物量更敏感。离开一年的交叉验证表明,ΔRE与氮含量之间的关系在研究中包括的所有四个覆盖作物取样年都是稳健的(相对值R2 = 0.700-0.769, RMSE = 10.70-15.40 kg ha - 1)。回归模型的性能随着多个预测因子的加入而提高,这些预测因子包括生物量(由归一化植被指数估算)、天气变量(R2 = 0.765, RMSE = 12.37 kg ha - 1)、管理变量(物种、季节,R2 = 0.772, RMSE = 12.13 kg ha - 1)和生物物理变量(高度、地表覆盖度,R2 = 0.818, RMSE = 10.29 kg ha - 1)。这些发现证明了利用基于红边的光谱指数在大地理范围内量化谷物覆盖作物氮含量的可行性,并表明纳入额外的预测因子,如天气和管理数据,可以提高模型的准确性。这项工作对量化与覆盖作物相关的氮淋失减少具有重要意义,有助于政策制定和评估影响诸如切萨皮克湾等水体的保护计划。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Multispectral red-edge indices accurately estimate nitrogen content in winter cereal cover crops

Multispectral red-edge indices accurately estimate nitrogen content in winter cereal cover crops

Winter cover crops reduce erosion and nutrient runoff from agricultural systems. Although cereal cover crops can decrease field nitrate leaching by 50%–95%, the magnitude of this reduction varies within and between fields, making it challenging to monitor the impact of cover crops on nitrate leaching at large spatial extents. Satellite remote sensing using red-edge bands has been shown to effectively estimate crop nitrogen (N) content (kg ha−1) in later growth-stage crops with a closed canopy. In this study, we evaluated 15 spectral indices derived from Sentinel-2 imagery to estimate N concentration (%) and content (kg ha−1) of cereal cover crops, using 1627 destructive samples collected from 2018 to 2023 in Maryland. Observed N content ranged from 0.1 to 214.7 kg ha−1, while N concentration ranged from 0.6% to 5.5%. The 15 indices considered were poor predictors of N concentration (adj. R2 = 0.089, root mean squared error [RMSE] = 0.802%), but were more successful at measuring N content (biomass × N concentration). Delta red-edge (ΔRE) was the best predictor of N content (adj. R2 = 0.748, RMSE = 13.10 kg ha−1 from cross-validation with 80% train and 20% test splits iterated 100 times) using samples with imagery collected within ±4 days of destructive sampling (= 1110). Our findings indicate that longer red-edge wavelengths (783 and 740 nm) are more suited for estimating N content in cereal cover crops compared to shorter red-edge wavelengths, which have been shown to be more sensitive to biomass. Leave-one-year-out cross-validation demonstrated that the relationship between ΔRE and N content was robust across all four cover crop sampling years included in the study (adj. R2 = 0.700–0.769, RMSE = 10.70–15.40 kg ha−1). Regression model performance improved with the addition of multiple predictors, including biomass (estimated from Normalized Difference Vegetation Index), weather variables (adj. R= 0.765, RMSE = 12.37 kg ha−1), management variables (species, season, adj. R= 0.772, and RMSE = 12.13 kg ha−1), and biophysical variables (height, fractional ground cover, adj. R= 0.818, and RMSE = 10.29 kg ha−1). These findings demonstrate the feasibility of quantifying N content in cereal cover crops using a red-edge-based spectral index across large geographic extents and indicate the inclusion of additional predictors, such as weather and management data, improves model accuracy. This work has implications for quantifying reductions in N leaching associated with cover crops, aiding in policymaking and evaluation of conservation programs that impact water bodies such as Chesapeake Bay.

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来源期刊
Agronomy Journal
Agronomy Journal 农林科学-农艺学
CiteScore
4.70
自引率
9.50%
发文量
265
审稿时长
4.8 months
期刊介绍: After critical review and approval by the editorial board, AJ publishes articles reporting research findings in soil–plant relationships; crop science; soil science; biometry; crop, soil, pasture, and range management; crop, forage, and pasture production and utilization; turfgrass; agroclimatology; agronomic models; integrated pest management; integrated agricultural systems; and various aspects of entomology, weed science, animal science, plant pathology, and agricultural economics as applied to production agriculture. Notes are published about apparatus, observations, and experimental techniques. Observations usually are limited to studies and reports of unrepeatable phenomena or other unique circumstances. Review and interpretation papers are also published, subject to standard review. Contributions to the Forum section deal with current agronomic issues and questions in brief, thought-provoking form. Such papers are reviewed by the editor in consultation with the editorial board.
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