Xinjiang Agricultural Sciences ›› 2024, Vol. 61 ›› Issue (4): 845-851.DOI: 10.6048/j.issn.1001-4330.2024.04.007
• Crop Genetics and Breeding·Germplasm Resources·Molecular Genetics·Physiology and Biochemistry • Previous Articles Next Articles
ZHANG Lei1,2(), YAO Mengyao2,3, LIU Zhigang2, LI Juan2, YANG Yang2, CAI Darun2, CHEN Guo2, LI Bo2, LI Xiaorong2, CHEN Xunji2, ZHAI Yunlong1(
)
Received:
2023-09-11
Online:
2024-04-20
Published:
2024-05-31
Correspondence author:
ZHAI Yunlong
Supported by:
张磊1,2(), 姚梦瑶2,3, 刘志刚2, 李娟2, 杨洋2, 蔡大润2, 陈果2, 李波2, 李晓荣2, 陈勋基2, 翟云龙1(
)
通讯作者:
翟云龙
作者简介:
张磊(1999-),男,甘肃武威人,硕士研究生,研究方向为玉米遗传育种,(E-mail)1822835613@qq.com
基金资助:
CLC Number:
ZHANG Lei, YAO Mengyao, LIU Zhigang, LI Juan, YANG Yang, CAI Darun, CHEN Guo, LI Bo, LI Xiaorong, CHEN Xunji, ZHAI Yunlong. Research of maize yield estimation based on unmanned aerial vehicle multispectral NDVI[J]. Xinjiang Agricultural Sciences, 2024, 61(4): 845-851.
张磊, 姚梦瑶, 刘志刚, 李娟, 杨洋, 蔡大润, 陈果, 李波, 李晓荣, 陈勋基, 翟云龙. 基于无人机多光谱NDVI值估测玉米产量[J]. 新疆农业科学, 2024, 61(4): 845-851.
玉米种质名称 Corn germplasm name | NDVI | 实测产量 Measured yield (kg/hm2) |
---|---|---|
20HN009×16F | 0.746 771 | 6 309.52 |
20HN064×DB614 | 0.781 470 | 7 261.90 |
20HN068×DB614 | 0.634 637 | 4 404.76 |
20HN069×DB614 | 0.663 515 | 5 595.23 |
20HN070×DB614 | 0.792 066 | 11 666.66 |
20HN084×DB614 | 0.672 930 | 6 071.42 |
20HN086×DB614 | 0.781 432 | 9 880.95 |
20HN096×DB614 | 0.565 060 | 5 476.19 |
20HN102×DB614 | 0.603 867 | 5 833.33 |
20HN104×DB614 | 0.743 107 | 9 523.80 |
20HN142×DB614 | 0.728 815 | 7 142.85 |
20HN152×DB614 | 0.748 561 | 6 666.66 |
20HN094×1487F | 0.719 880 | 10 476.19 |
20HN095×1487F | 0.794 545 | 11 071.42 |
20HN098×1487F | 0.793 120 | 10 833.34 |
20HN107×1487F | 0.740 062 | 9 523.80 |
20HN153×K487F | 0.728 140 | 9 880.95 |
20HN326×A55 | 0.756 129 | 7 023.80 |
Tab.1 18 corn material yields correspond to NDVI tables
玉米种质名称 Corn germplasm name | NDVI | 实测产量 Measured yield (kg/hm2) |
---|---|---|
20HN009×16F | 0.746 771 | 6 309.52 |
20HN064×DB614 | 0.781 470 | 7 261.90 |
20HN068×DB614 | 0.634 637 | 4 404.76 |
20HN069×DB614 | 0.663 515 | 5 595.23 |
20HN070×DB614 | 0.792 066 | 11 666.66 |
20HN084×DB614 | 0.672 930 | 6 071.42 |
20HN086×DB614 | 0.781 432 | 9 880.95 |
20HN096×DB614 | 0.565 060 | 5 476.19 |
20HN102×DB614 | 0.603 867 | 5 833.33 |
20HN104×DB614 | 0.743 107 | 9 523.80 |
20HN142×DB614 | 0.728 815 | 7 142.85 |
20HN152×DB614 | 0.748 561 | 6 666.66 |
20HN094×1487F | 0.719 880 | 10 476.19 |
20HN095×1487F | 0.794 545 | 11 071.42 |
20HN098×1487F | 0.793 120 | 10 833.34 |
20HN107×1487F | 0.740 062 | 9 523.80 |
20HN153×K487F | 0.728 140 | 9 880.95 |
20HN326×A55 | 0.756 129 | 7 023.80 |
名称 Name | 无人机 Unmanned aerial vehicle | 多光谱相机 Multispectral camera |
---|---|---|
型号Model | EcoDrone® UAS-8 | MicaSense Red Edge-MTM |
尺寸Size | 1 632 mm × 1 632 mm × 650 mm(螺旋桨、GPS支架均展开) | 94 mm × 63 mm× 46 mm |
重量 Weight | 10 kg(最大载荷6 kg) | 170 g (包括DLS) |
焦距 Focal length | 35 mm | |
最大分辨率 Maximum resolution | 1 280 × 960 | |
光谱带 Spectval band | R、G、B、NIR、Red edge | |
作业时间 Operation time | 30 min | 30 min |
最大可承受风速 Maximum tolerable wind speed | 10 m/s(5级风可安全飞行)、 瞬间可承受13 m/s (6级风) | 10 m/s(5级风可安全飞行)、 瞬间可承受13 m/s (6级风) |
Tab.2 Parameter of UAV remote sensing platform
名称 Name | 无人机 Unmanned aerial vehicle | 多光谱相机 Multispectral camera |
---|---|---|
型号Model | EcoDrone® UAS-8 | MicaSense Red Edge-MTM |
尺寸Size | 1 632 mm × 1 632 mm × 650 mm(螺旋桨、GPS支架均展开) | 94 mm × 63 mm× 46 mm |
重量 Weight | 10 kg(最大载荷6 kg) | 170 g (包括DLS) |
焦距 Focal length | 35 mm | |
最大分辨率 Maximum resolution | 1 280 × 960 | |
光谱带 Spectval band | R、G、B、NIR、Red edge | |
作业时间 Operation time | 30 min | 30 min |
最大可承受风速 Maximum tolerable wind speed | 10 m/s(5级风可安全飞行)、 瞬间可承受13 m/s (6级风) | 10 m/s(5级风可安全飞行)、 瞬间可承受13 m/s (6级风) |
影像号顺序 Image number order | 波段 Band (nm) | 波段类型 Band type | 波段宽度 Band width (nm) |
---|---|---|---|
1 | 475 | Blue | 20 |
2 | 560 | Green | 20 |
3 | 668 | Red | 10 |
4 | 840 | NIR | 40 |
5 | 717 | Red Edge | 10 |
Tab.3 The order of images of multispectral cameras and the corresponding band type and width
影像号顺序 Image number order | 波段 Band (nm) | 波段类型 Band type | 波段宽度 Band width (nm) |
---|---|---|---|
1 | 475 | Blue | 20 |
2 | 560 | Green | 20 |
3 | 668 | Red | 10 |
4 | 840 | NIR | 40 |
5 | 717 | Red Edge | 10 |
估产模型Estimation Model | 表达式Expression | R2 |
---|---|---|
二次函数Quadratic Function | Y1 = 103 130 X2-117 963 X+39 003 | 0.562 |
正反比函数Inverse Proportional Function | Y2 = 2 840.5 X/(1-X) | 0.495 |
线性函数 Linear Function | Y3 = 24 458 X-9 621 | 0.521 |
幂函数Power Function | Y4 = 23 412-10 998/ X | 0.489 |
Tab.4 Four production estimation models
估产模型Estimation Model | 表达式Expression | R2 |
---|---|---|
二次函数Quadratic Function | Y1 = 103 130 X2-117 963 X+39 003 | 0.562 |
正反比函数Inverse Proportional Function | Y2 = 2 840.5 X/(1-X) | 0.495 |
线性函数 Linear Function | Y3 = 24 458 X-9 621 | 0.521 |
幂函数Power Function | Y4 = 23 412-10 998/ X | 0.489 |
估产模型 Estimation model | 绝对误差Absolute error(kg/hm2 ) | 相对误差Relative error(%) | ||||
---|---|---|---|---|---|---|
最大值 Max | 最小值 Min | 均值 Mean | 最大值 Max | 最小值 Min | 均值 Mean | |
二次函数 Quadratic Functions | 2 947.50 | 83.00 | 1 216.86 | 28.13 | 0.84 | 15.79 |
正反比函数 Inverse Proportional Function | 3 176.39 | 5.94 | 1 251.98 | 30.32 | 0.10 | 16.63 |
线性函数 Linear functions | 2 489.75 | 389.07 | 1 419.35 | 23.76 | 3.93 | 19.02 |
幂函数 Power function | 2 374.54 | 543.65 | 1 493.19 | 37.63 | 5.50 | 20.14 |
Tab.5 Accuracy analysis of different yield forecast models
估产模型 Estimation model | 绝对误差Absolute error(kg/hm2 ) | 相对误差Relative error(%) | ||||
---|---|---|---|---|---|---|
最大值 Max | 最小值 Min | 均值 Mean | 最大值 Max | 最小值 Min | 均值 Mean | |
二次函数 Quadratic Functions | 2 947.50 | 83.00 | 1 216.86 | 28.13 | 0.84 | 15.79 |
正反比函数 Inverse Proportional Function | 3 176.39 | 5.94 | 1 251.98 | 30.32 | 0.10 | 16.63 |
线性函数 Linear functions | 2 489.75 | 389.07 | 1 419.35 | 23.76 | 3.93 | 19.02 |
幂函数 Power function | 2 374.54 | 543.65 | 1 493.19 | 37.63 | 5.50 | 20.14 |
估产模型 Estimation model | ME | RMSE (kg/hm2 ) | SD |
---|---|---|---|
二次函数 Quadratic Functions | 1 374.70 | 443.12 | 1 716.21 |
正反比函数 Inverse Proportional Function | 1 791.36 | 536.10 | 2 274.49 |
线性函数 Linear functions | 1 285.96 | 390.41 | 1 656.41 |
幂函数 power function | 1 227.69 | 539.59 | 2 224.78 |
Tab.6 Statistical analysis of the error between actual output and predicted output
估产模型 Estimation model | ME | RMSE (kg/hm2 ) | SD |
---|---|---|---|
二次函数 Quadratic Functions | 1 374.70 | 443.12 | 1 716.21 |
正反比函数 Inverse Proportional Function | 1 791.36 | 536.10 | 2 274.49 |
线性函数 Linear functions | 1 285.96 | 390.41 | 1 656.41 |
幂函数 power function | 1 227.69 | 539.59 | 2 224.78 |
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