Nutrient inversion and hyperspectral feature extraction of sea rice at diff erent growth stages

Shuwen Wang, Ronghua Wen, Ming Li, Xiping Lu

Abstract


Nitrogen is a large amount of essential elements for the growth and development of sea rice. Monitoring the nitrogen
nutrition status of sea rice timely and accurately, and rational fertilization of sea rice is of great signifi cance for increasing yield, optimizing
quality and reducing water pollution. The remote sensing diagnosis technology of sea rice nutrition has the characteristics of simple, non_x005fdestructive and rapid, and has been widely studied and applied by experts in various countries. In this experiment, the sea red rice varieties
were taken as an example. Through field experiment, the leaves of sea rice in four growth stages were collected by using chlorophyll
analyzer and near infrared spectrometer, and the chlorophyll value and spectral refl ectance of sea rice leaves were determined. The results
showed that the spectral refl ectance of sea rice leaves in diff erent growth stages had obvious changes. The sensitive band of sea rice leaves
was further found by combining the spectral curve, which laid the foundation for the future nitrogen nutrition diagnosis of sea rice.

Keywords


sea rice; Nutrient; Hyperspectral; Spectral refl ectance; Sensitive bands

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References


[1] Fengcheng Guo. Research on countermeasures and Suggestions for the development of rice industry in Zhanjianghai [D]. Guangdong Ocean

University,2019. (in Chinese)

[2] Ruijing Fang. Diffi culties and countermeasures of Marine rice industry development in China [J]. Journal of Agricultural Economics,2023(01):31-32. (in

Chinese)

[3] Lixia Tian,Ning Chen,Yusheng Chen. Development trend and prospect of sea rice industry [J]. Agricultural Outlook, 2019,16(10):49-54.

[4] Minmin Su,Shanyu Huang,Guangming Zhao,Quanying Zhao,Yinkun Yao,Yuxin Miao. Rice management status and countermeasures of farmers in

Heilongjiang Reclamation area [J]. Northern Rice,2012,42(02):28-33.

[5]Samborski S M, Tremblay N, Fallon E.Strategies to Make Use of Plant Sensors –Based Diagnostic Information for Nitrogen Recommendations[J].

Agronomy Journal, 2009, 101(4):800-816.

[6]Li H.Y., Pan S.J., Qian Y.D., Ma Y., Si Y., Gao S., Zheng G.P., Jiang Y.W., and Zhou J. Eff ects of mixed saline alkali stress on yield and quality of rice in

cold region, Nanfang Nongye Xuebao (Journal of Southern Agriculture), 2015,46(12):2100-2105.

[7]W. Xiao, J. Yang, H. Fang, J. Zhuang, Y. Ku, A robust classifi fi cation algorithm for separation of construction waste using NIR hyperspectral system[J].

Waste Manage,2019 (90):1–9.

[8]Yao Liu, Lele Xu, Shaogeng Zeng, Fu Qiao, Wei Jiang, Zhen Xu. Rapid detection of mussels contaminated by heavy metals using nearinfrared

reflflectance spectroscopy and a constrained difference extreme learning machine[J].Spectrochimica Acta Part A: Molecular and Biomolecular

Spectroscopy,2022(269):1-10.

[9]Nicolsas Tremblay, Zhijie Wang, Zoran G.Cerovic. Sensing crop nitrogen status with fl uorescence indicators[J].Agronomy for Sustainable Development,

2012, 32 (2) : 451-464.




DOI: https://doi.org/10.18686/esta.v10i3.440

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