首页|基于多光谱技术的甜菜块根糖分增长期施氮决策模型

基于多光谱技术的甜菜块根糖分增长期施氮决策模型

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为快速准确地获取甜菜的生长状况,在东北寒区对糖用甜菜精准施肥,达到高质高产的目地.2022年在黑龙江省哈尔滨市黑龙江大学呼兰校区试验基地,以糖用甜菜'KWS7748'为参试材料,获取甜菜块根糖分增长期不同施氮水平下的多光谱影像和田间实测数据,选出能反映甜菜此时期冠层生理生化的最优植被指数构建甜菜施氮决策模型.结果表明,甜菜的产量随着施氮水平的增加呈现先增加后减少的趋势,而含糖率随施氮水平的增加而显著下降;将各植被指数与甜菜SPAD进行回归分析,优选最优植被指数为LCI,不同施氮水平下LCI变化与根产量高度相关,与含糖率呈负相关关系;根据小区的最佳施氮量,生成试验区甜菜氮肥变量施肥图,与实际情况具有一致性.无人机遥感技术对甜菜氮素营养诊断,指导精准施用氮肥,实现高质高产具有重要的理论意义.
Nitrogen Fertilization Decision-Making Model During Sugar Growth Period of Sugar Beet Roots Based on Multispectral Technology
To obtain fast and accurate information of the growth of sugar beet and to achieve high quality and high yield by precise fertilization of sugar beet in the cold region of Northeast China,the multi-spectral images and field measurements of sugar beet'KWS7748'were obtained at the experimental site of Hulan Campus of Heilongjiang University in Harbin,Heilongjiang Province in 2022.The optimum vegetation index reflecting the physiology and biochemistry of sugar beet during this period was selected,and a decision-making model for sugar beet N application was constructed.The results showed that the sugar beet yield increased and gradually decreased,while the sugar content significantly reduced with the increase of N-fertilizer application.Based on the optimum N application rate of the plot,it generated a fertilizer map of N fertilizer variables used for sugar beet in the experimental area,which was consistent with the actual situation.UAV remote sensing technology is of theoretical importance in diagnosing nitrogen nutrition in sugar beet and guiding the precise application of nitrogen fertilizer to achieve high quality and yield.

sugar beetmultispectralnitrogen fertilizer recommendationvegetation indexUAV remote sensing

王敬云、胡晓航、董心久、马亚怀、李彦丽

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黑龙江大学现代农业与生态环境学院,哈尔滨 150008

新疆农业科学院经济作物研究所,乌鲁木齐 830000

甜菜 多光谱 氮肥推荐 植被指数 无人机遥感

黑龙江省省属高等学校基本科研业务费项目国家糖料产业技术体系分解项目黑龙江省生态环境厅项目

2020-KYYWF-1025CARS-170202HST2022TR003

2024

中国农学通报
中国农学会

中国农学通报

CSTPCD
影响因子:0.891
ISSN:1000-6850
年,卷(期):2024.40(10)
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