摘要
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。
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.
作者
王敬云
胡晓航
董心久
马亚怀
李彦丽
WANG Jingyun;HU Xiaohang;DONG Xinjiu;MA Yahuai;LI Yanli(College of Modern Agriculture and Ecological Environment,Heilongjiang University,Harbin 150008;Institute of Cash Crops,Xinjiang Academy of Agricultural Sciences,Urumqi 830000)
出处
《中国农学通报》
2024年第10期132-139,共8页
Chinese Agricultural Science Bulletin
基金
黑龙江省省属高等学校基本科研业务费项目“DSSAT-CERES-BEET模型在东北寒地甜菜生产中的适用性评价”(2020-KYYWF-1025)
国家糖料产业技术体系分解项目“基于无人机遥感技术的糖用甜菜施肥决策模型研究”(CARS-170202)
黑龙江省生态环境厅项目“农业废弃物糖厂滤泥还田在黑土区土壤改良及碳排放研究”(HST2022TR003)。
关键词
甜菜
多光谱
氮肥推荐
植被指数
无人机遥感
sugar beet
multispectral
nitrogen fertilizer recommendation
vegetation index
UAV remote sensing
