Physico-mechanical measurements, functional properties, proximate composition of newly developed climate-resilient cowpea (Vigna unguiculata) varieties and their classification with near-infrared spectroscopy

Abstract Cowpea is an important staple in Ghana and many tropical and subtropicalregions. Improving food security and agricultural sustainability for these crops requires the development of climate-resilient varieties.This study aimed to classify five newly developed climate-resilient cowpea varieties— Bawutawuta , SAMPEA 14 , SARI-tuya , IT13K-1070–2 , and IT07K-299–6— using Near Infrared Spectroscopy (NIRS) for classification, while standard methods were used to evaluate their composition, functional and physico-mechanical properties. Proximate composition, including moisture, protein, ash, fat, crude fiber, and carbohydrates, was determined according to Association of Official Analytical Chemists methods. NIRS data was processed within the 950–1650 nm range to reduce spectral noise, employing Savitzky-Golay smoothing for baseline correction. Linear Discriminant Analysis facilitated multi-class classification, with cross-validation performed using a leave-one-sample-out method to evaluate recognition and prediction accuracy. The cowpea varieties exhibited significant differences in their chemical and physico-mechanical properties. Moisture content ranged from 7.21% to 10.88%, protein from 22.84% to 32.53%, ash from 0.90% to 1.81%, fat from 2.56% to 9.13%, crude fiber from 2.90% to 4.78%, and carbohydrates from 47.43% to 53.85%. NIRS analysis demonstrated high sensitivity, achieving a recognition accuracy of 98.08% and a prediction accuracy of 96.19%. Bawutawuta and SARI-tuya presented distinct spectral profiles, while SAMPEA 14 , IT13K-1070–2 , and IT07K-299–6 showed overlapping spectra. These findings provide valuable insights into the unique attributes of each cowpea variety, which can be leveraged to optimize agricultural practices, processing, and storage of these climate-resilient varieties.