基于直方图的手机玉米冠层数字图像氮素诊断方法

doi:10.3864/j.issn.0578-1752.2024.20.014

Abstract

Abstract:

【Objective】Convenient and accurate diagnosis of crop nitrogen (N) status is the key to achieve precise crop fertilization and rational utilization of N resources. In recent years, the application of digital cameras and other tools in crop nutrition diagnosis has attracted wide attention. In this study, the smart phone cameras were used to obtain maize canopy images, and nitrogen nutrition diagnosis technology based on mobile phone cameras was established and improved. The reliability of traditional image mean method and histogram method for nitrogen nutrition diagnosis was compared to find out the best model for nitrogen nutrition diagnosis of summer maize. 【Method】Based on the experiment of N fertilizer amount in the field, the canopy image of summer maize at jointing stage was obtained by smartphone camera. Six color indices, including G/R, G/B, NRI [R/(R+G+B)], NGI [G/(R+G+B)], NBI [B/(R+G+B)] and (G-R)/(R+G+B), were extracted from summer maize canopy images, and the histogram sensitive interval were established, respectively, to analyze their relationship with leaf N content and yield of maize. The determination coefficient (R²) and root mean square error (RMSE) were used to determine the relationship between the mean color index model and the histogram model. Mean absolute percentage error (MAPE) was used to simulate and estimate the stability and accuracy of leaf N content and yield in maize compared with different index models. Then, the N nutrition diagnosis model based on mobile phone camera acquisition of summer maize canopy images was established. 【Result】N application significantly affected leaf N content, yield, canopy image hue and vegetation coverage of maize. The peak b of the histogram changes with the increase of leaf N content. Compared with the mean color index method in canopy images, the index histogram method was suitable for N diagnosis among different varieties. The color index (G-R)/(R+G+B) histogram could better reflect crop coverage and overall color information. The index histogram also showed a good correlation with leaf N content and yield. Based on the neural network model to validate the accuracy evaluation indicators of the dataset, the MAPE and RMSE values of leaf N content and yield in maize in the exponential histogram model were lower than those in the exponential mean model, and the R² reached 0.753, which was greater than that in the exponential mean model. The validation results of the exponential histogram model showed a MAPE value of 5.80% and an RMSE value of 0.07, indicating high estimation accuracy and strong generalization ability. The results indicated that the color parameter index histogram of canopy images had higher accuracy and stronger robustness in estimating leaf N content and yield, and could effectively utilize the characteristics of maize leaf coverage, color, etc., with good stability.【Conclusion】Therefore, the neural network model established by using smartphones to obtain digital images of maize canopy and combining them with the color index histogram method of canopy images has good application effects and improves estimation accuracy. As a new method, it has good potential in rapid and non-destructive diagnosis of maize N nutrition and precise fertilization.

Key words: nitrogen nutrition diagnosis, mobile phone camera, summer maize, canopy, neural network model, digital image technology

QI Xin, WANG Yang, HUANG YuFang, YE YouLiang, GUO YuLong, ZHAO YaNan. Nitrogen Nutrition Diagnosis Method Based on Mobile Phone Image of Summer Maize Canopy[J].Scientia Agricultura Sinica, 2024, 57(20): 4094-4106.

Figures/Tables 10

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References 35

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品种 Cultivar	氮水平 Nitrogen level	叶片含氮量 Leaf N content (%)	产量 Yield (kg·hm^-2)
登海605 Denghai 605，DH605	N0	0.77±0.14b	5766±1817b
	N120	0.86±0.03b	8612±738a
	N180	1.07±0.04a	9469±772a
	N240	0.98±0.12ab	8499±522a
	N360	0.86±0.15b	6297±591b
	平均Mean	0.91	7729
	CV (%)	12.24	12.76
科玉188 Keyu 188，KY188	N0	0.57±0.02b	7202±1642a
	N120	0.89±0.08a	8131±200a
	N180	0.92±0.07a	8956±1418a
	N240	0.84±0.10a	8592±1022a
	N360	0.97±0.11a	9037±987a
	平均Mean	0.84	8384
	CV(%)	8.51	12.79

品种 Cultivar	氮水平 Nitrogen level	色彩参数 Color parameter
品种 Cultivar	氮水平 Nitrogen level	G/R	G/B	NRI	NGI	NBI	(G-R)/(R+G+B)
登海605 Denghai 605，DH605	N0	0.93±0.24a	1.55±0.26a	0.25±0.04a	0.31±0.07a	0.16±0.04a	0.07±0.02a
	N120	0.99±0.22a	1.61±0.22a	0.26±0.03a	0.33±0.06a	0.18±0.04a	0.07±0.03a
	N180	1.07±0.15a	1.59±0.36a	0.28±0.05a	0.36±0.06a	0.21±0.03a	0.07±0.01a
	N240	1.10±0.09a	1.66±0.12a	0.27±0.01a	0.36±0.02a	0.20±0.01a	0.09±0.01a
	N360	1.01±0.04a	1.60±0.02a	0.27±0.00a	0.34±0.01a	0.19±0.01a	0.07±0.01a
	平均Mean	0.15	0.20	0.03	0.04	0.03	0.02
	CV(%)	14.90	12.44	10.51	12.98	13.89	24.31
科玉188 Keyu 188，KY188	N0	0.97±0.03a	2.15±0.28a	0.32±0.03a	0.38±0.03a	0.18±0.02ab	0.05±0.02a
	N120	0.95±0.02a	1.54±0.34b	0.27±0.02bc	0.34±0.03a	0.20±0.02a	0.05±0.01a
	N180	0.93±0.12a	1.54±0.21b	0.25±0.02c	0.34±0.04a	0.21±0.03a	0.05±0.01a
	N240	0.89±0.30a	1.47±0.43b	0.19±0.04d	0.29±0.10a	0.13±0.08b	0.07±0.03a
	N360	0.97±0.02a	1.85±0.18ab	0.31±0.01ab	0.37±0.02a	0.20±0.01a	0.05±0.01a
	平均Mean	0.10	0.29	0.02	0.05	0.03	0.02
	CV(%)	10.68	17.50	9.94	14.073	18.902	28.69

品种 Cultivar	色彩参数 Color parameter	叶片含氮量 Leaf N content (%)	产量 Yield (kg·hm^-2)
登海605 Denghai 605， DH605	G/R	0.334	0.563
	G/B	0.166	0.406
	NRI	0.256	0.568
	NGI	0.301	0.560
	NBI	0.368	0.632
	(G-R)/(R+G+B)	0.299	0.392
科玉188 Keyu 188，KY188	G/R	0.159	-0.460
	G/B	-0.237	-0.610
	NRI	-0.193	-0.326
	NGI	0.082	-0.530
	NBI	0.417	-0.166
	(G-R)/(R+G+B)	-0.017	-0.244

品种 Cultivar	色彩参数 Color parameter	叶片含氮量 Leaf N content (%)	产量 Yield (kg·hm^-2)
登海605 Denghai 605， DH605	G/R	0.456	0.345
	G/B	-0.342	-0.416
	NRI	0.588	0.689
	NGI	-0.070	-0.031
	NBI	0.432	0.526
	(G-R)/(R+G+B)	-0.633	-0.588
科玉188 Keyu 188， KY188	G/R	0.493	0.660
	G/B	-0.121	-0.667
	NRI	0.796	0.250
	NGI	0.394	0.625
	NBI	0.244	-0.257
	(G-R)/(R+G+B)	-0.550	-0.590

模型 Model	指标 Indicators	训练数据集 Training dataset		验证数据集 Validation dataset		R²
模型 Model	指标 Indicators	MAPE (%)	RMSE	MAPE (%)	RMSE	R²
指数均值 Color parameter mean	叶片含氮量 Leaf N content	20.48	0.211	14.60	0.223	0.265
指数均值 Color parameter mean	产量 Yield	12.97	1362.953	15.56	1481.131	0.435
指数直方图 Color parameter histogram	叶片含氮量 Leaf N content	10.92	0.126	5.80	0.070	0.753
指数直方图 Color parameter histogram	产量 Yield	10.42	1177.432	9.20	918.267	0.653

Nitrogen Nutrition Diagnosis Method Based on Mobile Phone Image of Summer Maize Canopy

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