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Selection of Agronomic Parameters and Construction of Prediction Models for Oleic Acid Contents in Rapeseed Using Hyperspectral Data

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成果类型:
期刊论文
作者:
Lu, Junwei;Tian, Rongcai;Wen, Shuangya;Guan, Chunyun
通讯作者:
Guan, CY
作者机构:
[Guan, Chunyun; Wen, Shuangya; Lu, Junwei] Hunan Agr Univ, Coll Agron, Changsha 410128, Peoples R China.
[Lu, Junwei] Hunan Agr Univ, Orient Sci & Technol Coll, Changsha 410128, Peoples R China.
[Tian, Rongcai] Cent South Univ, Sch Geosci & InfoPhys, Changsha 410083, Peoples R China.
通讯机构:
[Guan, CY ] H
Hunan Agr Univ, Coll Agron, Changsha 410128, Peoples R China.
语种:
英文
关键词:
Brassica napus L.;oleic acid content;hyperspectral;model construction;grey correlation analysis;integrated learning
期刊:
Agronomy
ISSN:
2073-4395
年:
2023
卷:
13
期:
9
页码:
2233-
基金类别:
Data curation, R.T.; funding acquisition, C.G.; investigation and validation, S.W.; soft, J.L.; writing—review and editing, J.L. and C.G. All authors have read and agreed to the published version of the manuscript. China Agriculture Research System of MOF and MARA (CARS-13).
机构署名:
本校为第一且通讯机构
院系归属:
农学院
东方科技学院
摘要:
High oleic acid oilseed rape is a hot research area in the development of functional oilseed rape. At present, the model of predicting the oleic acid content in rapeseed at the early growth stage based on hyperspectral technology lacks a mechanistic explanation. In this study, based on the data collected at the 5–6 leaf stage of oilseed rape, a one-dimensional linear regression prediction model of the oleic acid content in leaves (x) and the oleic acid content in rapeseed (y) was constructed with the regression equation y = 1.83x + 75.26, and ...

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