Estimation of Winter Wheat Tiller Number Based on Optimization of Gradient Vegetation Characteristics
Abstract
:1. Introduction
2. Materials and Methods
2.1. Field Experiments
2.2. Data Acquisition
2.2.1. Multispectral UAV Image Acquisition and Processing
2.2.2. Determination of Winter Wheat Tiller Number
2.2.3. Feature Extraction
- (1)
- Data acquisition and preprocessing: a UAV obtained multispectral orthophoto images of the test site, and the images were then corrected and spliced.
- (2)
- Selection and structure of vegetation index: vegetation indices sensitive to tiller number were identified, the UAV multispectral range was selected to obtain images, and coverage and gradient characteristics were determined.
- (3)
- Analysis and comparison: vegetation indices and coverage were analyzed with wheat tiller number and results were compared after optimization of gradient special diagnosis.
- (4)
- Estimation of wheat tiller number in the whole field: models that provided good estimations were used to predict wheat tiller number in the whole field.
2.2.4. Analysis of Characteristics
2.2.5. Selection of Vegetation Indices
2.3. Gradient Feature
2.4. Modeling
2.4.1. Linear Regression Model
2.4.2. Gradient Feature Optimization Model
2.5. Statistical Analysis
3. Results
3.1. Estimation of Tiller Number in Wheat
3.1.1. Unitary Linear Regression Analysis
3.1.2. Multiple Linear Regression Analysis
3.1.3. Estimation of Wheat Tiller Number after Optimization with Gradient Characteristics
3.2. Estimation of Wheat Tiller Number in the Whole Field
4. Discussion
5. Conclusions
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Experiment | Varieties | Nitrogen Fertilizer | Density | Replicates |
---|---|---|---|---|
1 | Zhenmai12 (P1) | 0 kg/ha (N1) | 150 × 104 ha−1 (M1) | 3 |
125 kg/ha (N2) | 225 × 104 ha−1 (M2) | |||
225 kg/ha (N3) | 300 × 104 ha−1 (M3) | |||
375 kg/ha (N4) | ||||
2 | Yangmai16 (P2) | 0 kg/ha (N1) | 150 × 104 ha−1 (M1) | 3 |
125 kg/ha (N2) | 225 × 104 ha−1 (M2) | |||
225 kg/ha (N3) | 300 × 104 ha−1 (M3) | |||
375 kg/ha (N4) | ||||
3 | Ningmai13 (P3) | 0 kg/ha (N1) | 150 × 104 ha−1 (M1) | 3 |
125 kg/ha (N2) | 225 × 104 ha−1 (M2) | |||
225 kg/ha (N3) | 300 × 104 ha−1 (M3) | |||
375 kg/ha (N4) |
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Wu, F.; Wang, J.; Zhou, Y.; Song, X.; Ju, C.; Sun, C.; Liu, T. Estimation of Winter Wheat Tiller Number Based on Optimization of Gradient Vegetation Characteristics. Remote Sens. 2022, 14, 1338. https://doi.org/10.3390/rs14061338
Wu F, Wang J, Zhou Y, Song X, Ju C, Sun C, Liu T. Estimation of Winter Wheat Tiller Number Based on Optimization of Gradient Vegetation Characteristics. Remote Sensing. 2022; 14(6):1338. https://doi.org/10.3390/rs14061338
Chicago/Turabian StyleWu, Fei, Junchan Wang, Yuzhuang Zhou, Xiaoxin Song, Chengxin Ju, Chengming Sun, and Tao Liu. 2022. "Estimation of Winter Wheat Tiller Number Based on Optimization of Gradient Vegetation Characteristics" Remote Sensing 14, no. 6: 1338. https://doi.org/10.3390/rs14061338