Estimates for heritability and consumer-validation of a penetrometer method for phenotyping softness of cooked cassava roots

Abstract

Although breeders have made significant progress in the genetic improvement of cassava (Manihot esculenta Crantz) for agronomic traits, lack of information on heritability and limited testing of highthroughput phenotyping methods are major limitations to improving root quality traits, such as softness after cooking, which rank high among Ugandan consumers. The objectives of this study were to determine heritability for softness of cooked cassava roots, and quantify the relationship between penetrometer and consumer testing methods for phenotyping softness of cassava roots. Softness defined as the maximum force (N) needed to penetrate cooked root samples using a penetrometer, was evaluated at four cooking time intervals: 15, 30, 45, and 60 min on 268 cassava genotypes. Estimates of broad-sense heritability (repeatability) ranged from 0.17 to 0.37, with the highest value observed at 45 min of cooking time interval. In the second study involving 135 cassava consumers from Kibaale district in Uganda, penetrometer measurements of cooked roots from six cassava varieties were found to be in strong agreement (r 2 = 0.91; P-value = 0.003) with ordinal scores of root softness from consumer testing. These results suggest that: (a) softness of cooked cassava roots is a trait amenable for evaluation and selection; and (b) a penetrometer can readily be used for assessment of cooked root softness. These findings form the basis for operationalising the routine assessment of root softness in cassava breeding trials, an output that will enhance ongoing efforts to breed for desired end-user root quality traits.

Identification of cassava quality attributes preferred by Ugandan users along the food chain

“…Currently, efforts are devoted towards development of reproducible methods for measuring attributes with appreciable genetic variation in our cassava breeding populations. The first priority is softness of boiled roots that we propose to measure using near infra‐red spectroscopy (NIRS), all leveraging on previous work (Iragaba et al ., 2019).…”

“…Subsequently, the developed descriptors could be used in developing more robust and high‐throughput phenotyping technologies such as use of near infra‐red spectroscopy (NIRS). Previous studies have indicated that consumer‐testing and sensory evaluation results can have high correlations with instrument characterisation (Padonou et al ., 2005; Iragaba et al ., 2019). Additionally, sensory descriptors developed in this study could be used by breeders in assessing the quality of the cassava breeding lines before they are released to the end users.…”

Correlation of cooking time with water absorption and changes in relative density during boiling of cassava roots

“…Large variation in the time required for roots to get soft in response to boiling has been reported and linked to genetic and environmental factors (Pereira et al ., 1985; Fukuda & Borges, 1988; Borges et al ., 2002; Beleia et al ., 2004; Azevedo Miranda et al ., 2008; Sajeev et al ., 2010; Talma et al ., 2013; Iragaba et al ., 2019). Cooking time (CT) tends to be shorter in plants harvested at a younger age (Lorenzi, 1994; Ngeve, 2003; Chirif, 2013).…”

“…Routine assessment of cooking quality, including CT, should be performed in breeding for varieties targeting the market for boiled cassava (Dixon et al ., 1994; Iragaba et al ., 2019). This is a requirement to increase the likelihood of adoption of improved genotypes.…”

Genomic characterization of Ugandan smallholder farmer‐preferred cassava varieties

“…Genotype discovery and calling was done jointly on 1,530 samples: in addition to the 556 new samples collected for this study, 624 samples described by Iragaba et al. (2019) were included as well as a random set of 350 samples that were selected from a diverse panel of breeding lines at NaCRRI (Kayondo et al., 2018). The single‐end raw reads of 150 bp were processed through the TASSEL GBS v2 production pipeline (Glaubitz et al., 2014).…”