烟草(nicotiana tabacum L.)高光谱多元线性预测模型叶片含氮量

Pub Date : 2023-08-31 DOI:10.3329/bjb.v52i20.68227
Ting Guo, Wen Li, Liangyong Li, Ximing Zou
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引用次数: 0

摘要

为了准确有效地获取烟草全生育期叶片氮含量,本研究采用烟草莲座期、旺盛期和打顶期三个关键时期的大田冠层光谱。逐一对田间冠层光谱、一阶导数光谱、高光谱参数和植被指数与烟叶含氮量进行相关性分析,并利用相关系数最佳的变量进行多元线性回归建立预测模型。结果表明,一阶导数谱、EVI II和绿峰位置具有较强的相关性,适合作为自变量引入多元方程。最后,建模决定系数(R2)为0.66,RMSE为0.40,MAPE为11%。验证结果表明,R2为0.73,RMSE为0.38,MAPE为8.33%,证明该模型能够准确预测烟叶氮素含量,能够满足田间烟叶质量指标大规模统计监测的要求。[j] .植物学报,52(2):575-584,2023(6):特刊
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Hyperspectral multivariate linear prediction model of tobacco (nicotiana tabacum L.) Leaf nitrogen content
In order to accurately and effectively obtain the nitrogen content of tobacco leaves during the whole growth period, in the present study the field canopy spectrum of the three critical periods of tobacco rosette stage, vigorous growth stage and topping stage were used. The correlation analysis of field canopy spectrum, first derivative spectrum, hyperspectral parameters and vegetation index with the nitrogen content of tobacco leaves was carried out one by one, and the prediction model was established by multiple linear regression using the variables with the best correlation coefficient. Results showed that the first derivative spectrum, EVI II and green peak position had strong correlation, which is suitable for introducing multivariate equations as independent variables. Finally, the modeling determination coefficient (R2) was 0.66, RMSE was 0.40, and MAPE was 11%. The validation results showed that R2 was 0.73, RMSE was 0.38, and MAPE was 8.33%, which proved that this model could accurately predict the nitrogen content of tobacco leaves and could meet the requirements of large-scale statistical monitoring of tobacco quality indicators in the field. Bangladesh J. Bot. 52(2): 575-584, 2023 (June) Special
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