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生态学杂志 ›› 2021, Vol. 40 ›› Issue (9): 3017-3024.doi: 10.13292/j.1000-4890.202109.030

• 技术与方法 • 上一篇    下一篇

基于数字图像技术的马铃薯氮素营养估测及验证

魏全全1,李飞2,张萌1,陈龙1,芶久兰1*   

  1. 1贵州省农业科学院土壤肥料研究所/农业部贵州耕地保育与农业环境科学观测实验站, 贵阳 550006; 2贵州省农业科学院马铃薯研究所/贵州马铃薯工程技术研究中心, 贵阳 550006)
  • 出版日期:2021-09-10 发布日期:2021-09-18

Estimation and validation of nitrogen nutrition of potato based on digital image processing technology.

WEI Quan-quan1, LI Fei2, ZHANG Meng1, CHEN Long1, GOU Jiu-lan1*   

  1. (1Institute of Soil and Fertilizer, Guizhou Academy of Agricultural Sciences/Guizhou Observation Experimental Station of Farmland Preservation and Agricultural Environmental Sciences, Ministry of Agriculture, Guiyang 550006, China; 2Potato Institute, Guizhou Academy of Agricultural Sciences/Guizhou Engineering and Research Center for Potato, Guiyang 550006, China).
  • Online:2021-09-10 Published:2021-09-18

摘要: 于2018—2019年在贵州省毕节市威宁县,以马铃薯为试验材料,连续2年开展不同氮素水平(0、120、240、300和360 kg·hm-2)田间试验。2018年采用数码相机分别在块茎形成期和块茎膨大期获取冠层图像数据,并同步采集植株,测定其氮素营养指标,分析冠层数码参数与氮素营养指标的相关性,筛选氮素营养指标估测的最优冠层数码参数,构建氮素营养指标的估测模型。利用2019年相同独立氮素水平试验,对上述方程模型精度进行验证并绘制1∶1线性关系图。结果表明:块茎形成期,冠层数码参数R/B(红光和蓝光比值)较其他冠层数码参数能更好地表征马铃薯氮素营养状况;块茎膨大期,冠层数码参数R/B、G/B(绿光和蓝光比值)和NBI(红光标准化值)均可表征马铃薯氮素营养状况,其中以R/B较好;利用2019年独立试验验证方程模型的准确性,结果表明,生物量和氮素累积量预测值和实测值的R2分别为0.911和0.888,均方根误差RMSE分别为0.685和25.115,相对误差RE分别为12.92%和23.41%,模型预测精度较好。数字图像技术可以进行马铃薯氮素营养的评估预测,评估时期为块茎形成期和块茎膨大期均可,最佳的预测参数为R/B,参数预测的最佳方程模型为直线方程。

关键词: 马铃薯, 数字图像, 氮素, 估测, 方程模型, 验证

Abstract: A field experiment was conducted with potato under different nitrogen application levels (0, 120, 240, 300 and 360 kg·hm-2) in Weining County, Bijie City, Guizhou Province from 2018 to 2019. In 2018, the canopy images of potato were obtained by digital camera at both tuber initiation stage and tuber bulking stage. The nitrogen nutrition indices of plants were measured. We analyzed the correlation between canopy digital parameters and nitrogen nutrition indices, screened the optimal canopy digital parameters for estimating nitrogen nutrition indices, and constructed the estimation model of nitrogen nutrition indices. The accuracy of the above equation model was verified and a 1∶1 linear relationship was drawn by using an independent nitrogen level experiment in 2019. The results showed that the ratio of redness intensity to blueness intensity (R/B) was better than other canopy parameters in characterizing nitrogen nutrition status of potato attuber initiation stage. R/B, the ratio of greenness intensity to blueness intensity (G/B), and the normalized blueness intensity (NBI) could characterize the nitrogen status of potato at tuber bulking stage, with R/B being the best. The correlation values (R2) between measured and estimated biomass and between measured and estimated nitrogen accumulation were 0.911 and 0.888, with RMSE being 0.685 and 25.115, and RE being 12.92% and 23.41%, respectively. The digital image processing technology can be used to evaluate and estimate nitrogen nutrition of potato. The best estimated period is tuber initiation stage and tuber bulking stage, the best estimation parameter is R/B, and the best model is linear regression equation.

Key words: potato, digital image, nitrogen, estimation, equation model, validation.