摘要
高效、精准的产量预测对于优化芹菜(Apium graveolens L.)产量管理和指导后期农业决策具有重要意义。为建立一种实时、准确的芹菜当季产量预测方法,采用田间试验方法,对2年不同品种和不同施氮处理芹菜进行田间试验,以GreenSeeker冠层光谱仪为例,获取芹菜冠层植被归一化指数(NDVI)及产量等,通过建模和验证分析,探明冠层光谱仪对芹菜当季产量潜力预测的可行性与准确性。相关分析结果表明,冠层NDVI测定值与2种芹菜产量显著相关,相关系数分别为0.583~0.805(西芹,XQ)和0.256~0.922(药芹,YQ)。回归分析结果表明,移栽后30~70 d测定的冠层NDVI值可预测芹菜当季产量,模型类型对预测结果准确性无显著影响,R^(2)值为0.51~0.85。综合不同品种结果,冠层NDVI值可准确预测XQ和YQ两品种芹菜当季产量,R^(2)值和RMSE值分别为0.66~0.84和7.40~10.72。经验证,移栽后60和70 d时,验证方程的斜率分别为0.95和1.05,预测产量和实测产量数据点均匀分布在1∶1线附近。因此,外叶生长盛期是利用冠层光谱仪进行芹菜产量预测的最早时期。研究表明,构建基于NDVI值的产量预测模型可准确预测芹菜的当季产量,也为芹菜作物和其他蔬菜作物的产量预测和养分管理提供理论依据和技术支撑。
Efficient and precise yield prediction is critical to optimize celery(Apium graveolens L.)yield and guide successful agricultural decision making.In this study,a two-year field experiment was conducted to establish an in-season and accurate yield prediction model for celery by using the GreenSeeker hand-hold optical sensor.Two different cultivars Xiqing(XQ)and Yaoqing(YQ)were selected.Normalized difference vegetation index(NDVI)was measured at different stages with the model establishing and validating to test the feasibility and accuracy of GreenSeeker sensor-based yield prediction model.Pearson correlation analysis was performed to identify the relationship between the NDVI measurements and the harvested yield of celery,and the correlation coefficient was observed from 0.583 to 0.805 for XQ and from 0.256 to 0.922 for YQ.Regression analysis showed that the NDVI measurements at 30~70 d after transplanting could predict in-season yield of celery accurately,with R^(2) values ranged from 0.51 to 0.85,and no significant difference existed between different predict models.Combining the results of different cultivars,the canopy NDVI measurements could predict the in-season yield of XQ and YQ,and the R^(2) and RMSE values were ranged from 0.66 to 0.84 and from 7.40 to 10.72,respectively.It was verified that the slopes of the validation equations were 0.95 and 1.05 at 60 and 70 d after transplanting,respectively.The data points of predicted yield and measured yield were evenly distributed around the 1∶1 line,indicating that the outer leaf flourish stage was the earliest stage for yield prediction with the canopy sensor.Therefore,establishing a yield prediction model based on NDVI measurements can accurately reflect the in-season yield of celery and provide theoretical basis for the yield prediction and precise nutrient management of celery and other vegetable crops.
作者
纪荣婷
王远
闵炬
施卫明
徐丽萍
张龙江
JI Rong-ting;WANG Yuan;MIN Ju;SHI Wei-ming;XU Li-ping;ZHANG Long-jiang(Nanjing Institute of Environmental Sciences,Ministry of Ecology and Environment,Nanjing Jiangsu 210042;State Key Laboratory of Soil and Sustainable Agriculture,Institute of Soil Science,Chinese Academy of Sciences,Nanjing Jiangsu 210008;Cultivated Land Quality Protection Station of Agricultural Technology Extension Center in Liuhe District,Nanjing Jiangsu 211500)
出处
《中国土壤与肥料》
CAS
CSCD
北大核心
2021年第6期319-327,共9页
Soil and Fertilizer Sciences in China
基金
国家重点研发计划项目(2017YFD0800404)
国家自然科学基金(31701994)
江苏省农业科技自主创新资金项目[CX(18)1005]
山东省重大科技创新工程项目(2019JZZY010701)。
关键词
芹菜
冠层光谱仪
产量预测
归一化植被指数
精度分析
celery(Apium graveolens L.)
canopy sensor
yield prediction
normalized difference vegetation index
accuracy analysis
