2012Mianhua xuebaoRequires access

Monitoring of Cotton Canopy Growth Status Based on Cotton Canopy APAR and FAPAR Data

MA Qin-jian

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Abstract

We cultivated two cotton cultivars in an experimental field,and recorded the photosythetically active radiation(PAR) of the cotton canopy using a linear quantum sensor at six key growth stages.The absorbed photosythetically active radiation(APAR) and fractional interception of absorbed photosythetically active radiation(FAPAR) were deduced from PAR data.The results showed that the highest APAR and FAPAR values were at the cotton flowering stage,the flowering to boll-forming stage,respectively.Their values decreased at the full boll stage and late boll stage,and reached a minimum at the boll opening stage.We used multivariate analyses for regression modeling between APAR/FAPAR,and leaf area index,ground cover,aboveground fresh biomass,and aboveground net primary production.The strongest relationship was between APAR and ground cover.Regression analyses showed that FAPAR and leaf area index were related via an exponential function.There were significant relationships between tested ground cover and estimated ground cover,and between tested LAI and estimated LAI,respectively.These results show that cotton APAR and FAPAR data can be used for real-time,nondestructive,and quantitative estimates of cotton canopy growth status parameters.These techniques will be useful for monitoring applications.

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What this paper is about

We cultivated two cotton cultivars in an experimental field,and recorded the photosythetically active radiation(PAR) of the cotton canopy using a linear quantum sensor at six key growth stages.The absorbed photosythetically active radiation(APAR) and fractional interception of absorbed photosythetically active radiation(FAPAR) were deduced from PAR data.The results showed that the highest APAR and FAPAR values were at the cotton flowering stage,the flowering to boll-forming stage,respectively.Their values decreased at the full boll stage and late boll stage,and reached a minimum at the boll opening stage.We used multivariate analyses for regression modeling between APAR/FAPAR,and leaf area index,ground cover,aboveground fresh biomass,and aboveground net primary production.The strongest relationship was between APAR and ground cover.Regression analyses showed that FAPAR and leaf area index were related via an exponential function.There were significant relationships between tested ground cover and estimated ground cover,and between tested LAI and estimated LAI,respectively.These results show that cotton APAR and FAPAR data can be used for real-time,nondestructive,and quantitative estimates of cotton canopy growth status parameters.These techniques will be useful for monitoring applications.

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Available abstract

We cultivated two cotton cultivars in an experimental field,and recorded the photosythetically active radiation(PAR) of the cotton canopy using a linear quantum sensor at six key growth stages.The absorbed photosythetically active radiation(APAR) and fractional interception of absorbed photosythetically active radiation(FAPAR) were deduced from PAR data.The results showed that the highest APAR and FAPAR values were at the cotton flowering stage,the flowering to boll-forming stage,respectively.Their values decreased at the full boll stage and late boll stage,and reached a minimum at the boll opening stage.We used multivariate analyses for regression modeling between APAR/FAPAR,and leaf area index,ground cover,aboveground fresh biomass,and aboveground net primary production.The strongest relationship was between APAR and ground cover.Regression analyses showed that FAPAR and leaf area index were related via an exponential function.There were significant relationships between tested ground cover and estimated ground cover,and between tested LAI and estimated LAI,respectively.These results show that cotton APAR and FAPAR data can be used for real-time,nondestructive,and quantitative estimates of cotton canopy growth status parameters.These techniques will be useful for monitoring applications.

Key concepts: Interception, Canopy, Photosynthetically active radiation, Leaf area index, Environmental science, Agronomy, Mathematics, Stage (stratigraphy)

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