Browsing by Author "Enoch Wembabazi"

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Development and validation of near-infraredspectroscopy procedures for prediction ofcassava root dry matter and amylose contentsin Ugandan cassava germplasm
(Journal of The Science of Food and Agriculture, 2023-11-23) Ephraim Nuwamanya; Enoch Wembabazi; Michael Kanaabi; Fatumah Babirye Namakula; Arnold Katungisa; Ivan Lyatumi; Williams Esuma; Emmanuel Oladeji Alamu; Dominique Dufour; Robert Kawuki; Fabrice Davrieux
BACKGROUND: Cassava utilization for food and/or industrial products depends on inherent properties of root dry matter con- tent (DMC) and the starch fraction of amylose content (AC). Accordingly, in the present study, near-infrared reflectance spectroscopy (NIRS) models were developed to aid breeding and selection of DMC and AC as critical industrial traits taking care of root sample preparation and cassava germplasm diversity available in Uganda. RESULTS: Upon undertaking calibrations and cross-validations, best models were adopted for validation. DMC in calibration samples ranged from 20 to 45 g 100g−1, whereas, for amylose content, it ranged from 14 to 33 g 100g−1. In the validation set, average DMC was 29.5 g 100g−1, whereas, for amylose content, it was 24.64 g 100g−1. For DMC, a modified partial least square regression model had regression coefficients (R2) of 0.98 and 0.96, respectively, in the calibration and validation set. These were also associated with low bias (−0.018) and ratio of performance deviation that ranged from 4.7 to 5.0. In addition, standard error of prediction values ranged from 0.9 g 100g−1 to 1.06 g 100g−1. For AC, the regression coefficient was 0.91 for the calibration set and 0.94 for the validation set. A bias equivalent to −0.03 and a ratio of performance deviation of 4.23 were observed. CONCLUSION: These findings confirm the robustness of NIRS in the estimation of dry matter content and amylose content in cassava roots and thus justify its use in routine cassava breeding operations.
NIRS Predictions, Phenotypic Variability and Optimization of Cooking Time for Evaluation of the Root Softness of Boiled Cassava
(National Agricultural Research Organisation, 2023-09-01) Babirye Fatumah Namakula; Ephraim Nuwamanya; Michael Kanaabi; Paul Gibson; Enoch Wembabazi; Iragaba Paula; Robert Sezi Kawuki
This study aimed at quantifying the extent of genetic variability of softness in cassava germplasm across varied cooking times and root sections. It also examined the possibility of using Near Infrared Spectroscopy (NIRS) for measurement of cassava root softness. Softness was evaluated using a penetrometer. This was done at 15, 30 and 45minutes cooking time, all across proximal, middle and distal root sections. These measurements were done on 57 accessions. For each sample, spectra were acquired using NIRS Benchtop (FOSS DS2500) on a composite of each root section of mashed fresh cassava sample. Modified Partial Least Squares regression (MPLS) was used for NIRS calibration development using WINISI software. Significant (P < 0.001) variability in softness was established. Cooking time significantly influenced softness and there were significant accession and root part interaction (P < 0.001). Wide variability and high heritability (H = 0.8) were found for softness at 30 minutes cooking time. Highest association was found with 30- and 45-minutes cooking time (r = 0.58). Strong association was observed between middle root section with distal (r = 0.74) and proximal (r = 0.73). NIRS softness calibration (R2c) were 0.445, 0.413 and 0.521 for 15-, 30-, and 45-minutes cooking time respectively. NIRS prediction (R2p) were 0.322, 0.192, and 0.390 for 15-, 30-, and 45-minutes cooking time respectively. These results suggest that 30 minutes cooking time and middle root section are optimum for softness phenotyping.