Estimation model of canopy stratification porosity based on morphological characteristics: A case study of cotton. (May 2020)

• Record Type: Journal Article
• Authors: Liu, Xinghua; Liu, Xuemei; Li, Yang; Yuan, Jin; Song, Laiqi; Li, Huan; Wu, Minqing
• Is Part Of: Biosystems engineering. Volume 193(2020)
• Page Start: 174
• Page End: 186
• Publication Date: 2020-05
• Subjects: Estimation model -- Foliage distribution -- Stratification porosity -- Cotton morphology -- Pesticide spraying; Bioengineering -- Periodicals; Agricultural engineering -- Periodicals; Biological systems -- Periodicals; Génie rural -- Périodiques; Systèmes biologiques -- Périodiques; 631
• DOI: 10.1016/j.biosystemseng.2020.02.018
• Languages: English
• ISSNs: 1537-5110

Abstract

Abstract : Foliage density and spatial distribution affect droplet dispersion and deposition inside the plant canopy in pesticide spraying. Quantitative expression of foliage density and spatial distribution would contribute to improving pesticide spraying effect. Stratification porosity was proposed to describe density and spatial distribution of cotton foliage in this paper, and an estimation model of stratification porosity for cotton canopy based on morphological characteristics was put forward. Besides the randomness of local branches and leaves resulting from competitive growth, there was traceable statistical regularity about density and spatial distribution of cotton foliage based on growth law and morphological characteristics. Accordingly, an estimation model of stratification porosity was presented, which was mainly driven by growing-degree days (GDD), incorporating row spacing, plant spacing and the randomness of crop azimuth. To validate the model, a laser ranging bench was designed to measure stratification porosity. The cotton canopy was stratified into three layers in the vertical direction. Estimated stratification porosity of each layer was compared with measured values. For flowering stage, the root mean square errors (RMSE) of lower layer, middle layer and upper layer were 3.97%, 2.08% and 6.50% respectively. The mean relative errors (MRE) were 5.6%, 5.3% and 10.9% respectively. For bud stage, RMSE and MRE were 9.2% and 12.6% respectively. The estimation model was considered to be an acceptable approach for porosity acquisition with adequate accuracy. Spatial variation of stratification porosity indicated inhomogeneity of foliage distribution. Therefore, the model could provide quantitative information of cotton foliage density and spatial distribution, which would be helpful for pesticide spraying. Highlights: An estimation model of stratification porosity for cotton canopy is proposed. The model relies on morphological characteristics and growth law of cotton plant. The model provides quantitative data of cotton foliage for pesticide spraying. The spatial variation of stratification porosity shows distinct inhomogeneity.