基于无人机高光谱特征参数和株高估算马铃薯地上生物量

doi:10.3964/j.issn.1000-0593(2021)03-0903-09

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Abstract Above-ground biomass (AGB) is an important index to evaluate crop growth and yield estimation, and plays an important role in guiding agricultural management. Therefore, the rapid and accurate acquisition of biomass information is of great significance for monitoring the growth status of potato and improving the yield. The hyperspectral images, measured plant height (H), above-ground biomass and three-dimensional coordinates of ground control point (GCP) were obtained in budding potato period, tuber formation period, tuber growth period, starch accumulation period and mature period. Firstly, based on UAV hyperspectral image and GCP to generate the DSM of the experimental field, the plant height (H_dsm) of potato was extracted by DSM. Then the first-order differential spectrum, vegetation index and green edge parameters are calculated using UAV hyperspectral images. Furthermore, the correlation between hyperspectral characteristic parameter (HCPs), green edge parameter (GEPs) and potato AGB was analyzed. The first seven hyperspectral characteristic parameters and the optimal green edge parameter (OGEPs) with good correlation with AGB were selected for each growth period. Finally, the AGB of different growth period was estimated by partial least square regression (PLSR) and random forest (RF) based on the combination of HCPs, HCPs and OGEPs, HCPs and OGEPs and H_dsm. The results show that: (1) the H_dsm is highly fitted to H (R²=0.84，RMSE=6.85 cm，NRMSE=15.67%). (2) The optimal green edge parameters obtained in each growth period are not completely the same. The OGEPs of the budding period, the tuber growth period and the starch accumulation period are R_sum, and the OGEPs of the tuber formation period and the mature period are Dr_minand SDr, respectively. (3) Compared with HCPs, the accuracy of AGB estimation could be improved by adding OGEPs to HCPs, OGEPs and H_dsm to HCPs at different growth period of potato, and the latter improved the accuracy more greatly. (4) The R² of AGB modeling and verification estimated by PLSR and RF showed an upward trend from budding period to tuber growth period and then began to decrease. On the whole, R² decreased after increased. The estimation of AGB by PLSR is better than RF in each growth period，among which the AGB estimation of tuber growth period was the best. Therefore, the estimation accuracy of potato AGB can be improved by combining the OGEPs and plant height in HCPs and using PLSR method.

Key words：Potato; Above-ground biomass; Hyperspectral characteristic parameter; Green edge parameter; Plant height

Received: 2020-07-21 Accepted: 2020-11-06

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S25

Corresponding Authors: FENG Hai-kuan E-mail: fenghaikuan123@163.com

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https://www.gpxygpfx.com/EN/10.3964/j.issn.1000-0593(2021)03-0903-09 OR https://www.gpxygpfx.com/EN/Y2021/V41/I03/903

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