摘要
【目的】通过优化光谱指数与叶水势(Leaf Water Potential,LWP)之间的关系,寻找不同生育时期的最佳敏感波段,提高作物水分状况的估测精度。【方法】利用布置在内蒙古武川县和察哈尔右翼前旗的多品种不同水分梯度的田间试验,基于不同生育时期采集的叶片光谱反射率和LWP,分析水分敏感波段与生育时期的关系,并探究350~2500 nm波段范围内差值、比值和归一化差异光谱指数的最佳波段组合。【结果】生育时期对光谱指数最佳敏感波段的选择对研究结果具有显著影响。单一生育时期的最佳敏感波段主要分布在红边和近红外波段,而不同生育时期合并后的最佳敏感波段则主要位于近红外波段。优化光谱指数与LWP之间呈高度线性相关性,其中优化归一化差异光谱指数(NDSI)是估测单一生育时期马铃薯LWP的最佳优化光谱指数。随着生育时期的推进,光谱指数与LWP之间的线性关系逐渐增强,在淀粉积累期估测效果最佳且具有更强的鲁棒性,训练数据的决定系数(R^(2))达到0.90,RMSE为0.07MPa,MRE为6.70%,而验证数据的R^(2)为0.87,RMSE为0.08MPa,MRE为7.41%。生育时期合并后,优化光谱指数对块茎形成期和块茎膨大期的合并生育时期的马铃薯LWP估测表现出更好的效果。训练数据和验证数据的R^(2)分别为0.64和0.53,RMSE分别为0.14 MPa和0.16 MPa,MRE分别为10.39%和12.40%。相比于现有的水分敏感光谱指数,优化光谱指数明显提高了合并生育时期估测LWP的准确性和稳定性。【结论】马铃薯生育时期对现有水分敏感光谱指数估测LWP有显著影响,基于波段优化构建的新光谱指数能够改善现有光谱指数在估测时指数敏感性低和数据离散问题,显著提高了马铃薯LWP模型估测稳定性,为优化光谱指数在马铃薯水分状况监测和精准灌溉管理提供科学指导。
【Objective】Leaf water potential(LWP)is a key physiological trait reflecting plant responses to environmental conditions.However,large-scale field measurements remain challenging.This study explores the feasibility of using spectral imaging for indirect LWP estimation.【Method】A field experiment with a soil water gradient was conducted in a potato field in Wuchuan County and Chahar Right Front Banner,Inner Mongolia.Leaf spectral reflectance and water potential were measured at different growth stages.Moisture-sensitive spectral bands were analyzed,and the optimal combination of difference,ratio,and normalized difference spectral indices was identified within the 350-2500 nm wavelength range.【Result】The selection of optimal sensitive bands varied across growth stages and significantly impacted estimation accuracy.For individual growth stages,the most sensitive bands were primarily located in the red-edge and near-infrared regions,while for combined growth stages,the most effective bands were predominantly in the near-infrared region.A strong linear correlation was observed between the optimized spectral index and LWP.The Optimized Normalized Difference Spectral Index(NDSI)was the most effective index for estimating potato LWP at a single growth stage.As growth progressed,the correlation between spectral indices and LWP improved,with the highest estimation accuracy and robustness observed during the starch accumulation stage.At this stage,the coefficient of determination(R^(2))for training data reached 0.90,with an RMSE of 0.07 MPa and an MRE of 6.70%,while for validation data,R^(2) was 0.87,RMSE was 0.08 MPa,and MRE was 7.41%.When multiple growth stages were combined,the optimized spectral index enhanced LWP estimation accuracy during the tuber formation and expansion stage.For these stages,the R^(2) values for training and validation data were 0.64 and 0.53,respectively,with RMSE values of 0.14 MPa and 0.16 MPa,and MRE values of 10.39% and 12.40%.Compared to existing moisture-sensitive spectral indices,the optimized spectral index significantly improved accuracy and stability across combined growth stages.【Conclusion】The newly developed spectral index,based on band optimization,enhances sensitivity and reduces data dispersion compared to existing spectral indices.It significantly improves the stability of the potato LWP estimation model,offering valuable insights for optimizing spectral indices in potato water status monitoring and precision irrigation management.
作者
高凯
杨海波
尹航
王伟
孙宇
赵亮
李斐
GAO Kai;YANG Haibo;YIN Hang;WANG Wei;SUN Yu;ZHAO Liang;LI Fei(College of Resources and Environmental Sciences,Inner Mongolia Agricultural University,Huhhot 010011,China;Inner Mongolia Key Laboratory of Soil Quality and Nutrient Resources/Key Laboratory of Agricultural Ecological Security and Green Development at Universities of Inner Mongolia Autonomous,Inner Mongolia Agricultural University,Huhhot 010011,China;Ulanqab Institute of Agriculture and Forestry Sciences,Ulanqab 012000,China)
出处
《灌溉排水学报》
2025年第3期1-11,共11页
Journal of Irrigation and Drainage
基金
国家自然科学基金项目(32160757)
内蒙古自治区自然科学基金项目(2024QN03012)
内蒙古自治区农牧业青年创新基金项目(2021QNJJN09)。
关键词
马铃薯
叶水势
水分指数
波段优化
高光谱
生育时期
potato
leaf water potential
water index
band optimization
hyperspectral
growth stages
