Remote Sensing Applications and Decision Support

Varietal discrimination of common dry bean (Phaseolus vulgaris L.) grown under different watering regimes using multitemporal hyperspectral data

[+] Author Affiliations
Perushan Rajah, John Odindi, Onisimo Mutanga

University of KwaZulu-Natal, Discipline of Geography, School of Agricultural, Earth & Environmental Sciences, Private Bag X01, Scottsville, Pietermaritzburg 3209, South Africa

Elfatih M. Abdel-Rahman

University of KwaZulu-Natal, Discipline of Geography, School of Agricultural, Earth & Environmental Sciences, Private Bag X01, Scottsville, Pietermaritzburg 3209, South Africa

University of Khartoum, Faculty of Agriculture, Department of Agronomy, Khartoum North 13144, Sudan

Albert Modi

University of KwaZulu-Natal, School of Agricultural Earth & Environmental Sciences, Discipline of Crop Science, Private Bag X01, Scottsville 3209, Pietermaritzburg, South Africa

J. Appl. Remote Sens. 9(1), 096050 (May 20, 2015). doi:10.1117/1.JRS.9.096050
History: Received March 14, 2015; Accepted April 22, 2015
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Abstract.  Globally, the common dry bean varieties (Phaseolus vulgaris L.) are regarded as valuable food crops. Due to diversion-farm and postharvest management requirements, quick, reliable, and cost-effective varietal discrimination is critical for optimal management during growth and after harvesting. The large number of valuable wavelengths that characterize hyperspectral remotely sensed datasets in concert with emerging robust discriminant analysis techniques offers great potential for on-farm dry bean varietal discrimination. In this study, an integrated approach of partial least-squares discriminant analysis (PLS-DA) on hyperspectral data was used to determine the bean’s optimal timing for on-farm varietal discrimination. Based on experimental plots underirrigated and rain-fed watering regimes, hyperspectral data were collected at three major phenological stages. Data at each stage were first used to generate PLS-DA models to determine variable (wavebands) importance in the projection (VIP) and the VIP bands used to generate VIP conditioned PLS-DA models. The study identified 6 weeks (branching and rapid vegetative growth) and 10 weeks (flowering and pod development) after seed sowing as optimal stages for varietal discrimination. The study offers insight into the optimal period to discriminate dry bean varieties using spectroscopy, valuable for on-farm and after-farm management and crop monitoring sensor development.

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© 2015 Society of Photo-Optical Instrumentation Engineers

Citation

Perushan Rajah ; John Odindi ; Elfatih M. Abdel-Rahman ; Onisimo Mutanga and Albert Modi
"Varietal discrimination of common dry bean (Phaseolus vulgaris L.) grown under different watering regimes using multitemporal hyperspectral data", J. Appl. Remote Sens. 9(1), 096050 (May 20, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.096050


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