Predicting starch content in cassava fresh roots using near-infrared spectroscopy.

The cassava starch market is promising in sub-Saharan Africa and increasing rapidly due to the numerous uses of starch in food industries. More accurate, high-throughput, and cost-effective phenotyping approaches could hasten the development of cassava varieties with high starch content to meet the growing market demand. This study investigated the effectiveness of a pocket-sized SCiO™ molecular sensor (SCiO) (740-1070 nm) to predict starch content in freshly ground cassava roots. A set of 344 unique genotypes from 11 field trials were evaluated. The predictive ability of individual trials was compared using partial least squares regression (PLSR). The 11 trials were aggregated to capture more variability, and the performance of the combined data was evaluated using two additional algorithms, random forest (RF) and support vector machine (SVM). The effect of pretreatment on model performance was examined. The predictive ability of SCiO was compared to that of two commercially available near-infrared (NIR) spectrometers, the portable ASD QualitySpec® Trek (QST) (350-2500 nm) and the benchtop FOSS XDS Rapid Content™ Analyzer (BT) (400-2490 nm). The heritability of NIR spectra was investigated, and important spectral wavelengths were identified. Model performance varied across trials and was related to the amount of genetic diversity captured in the trial. Regardless of the chemometric approach, a satisfactory and consistent estimate of starch content was obtained across pretreatments with the SCiO (correlation between the predicted and the observed test set, (R2 P): 0.84-0.90; ratio of performance deviation (RPD): 2.49-3.11, ratio of performance to interquartile distance (RPIQ): 3.24-4.08, concordance correlation coefficient (CCC): 0.91-0.94). While PLSR and SVM showed comparable prediction abilities, the RF model yielded the lowest performance. The heritability of the 331 NIRS spectra varied across trials and spectral regions but was highest (H2 > 0.5) between 871-1070 nm in most trials. Important wavelengths corresponding to absorption bands associated with starch and water were identified from 815 to 980 nm. Despite its limited spectral range, SCiO provided satisfactory prediction, as did BT, whereas QST showed less optimal calibration models. The SCiO spectrometer may be a cost-effective solution for phenotyping the starch content of fresh roots in resource-limited cassava breeding programs.

Genome-wide association analysis reveals new insights into the genetic architecture of defensive, agro-morphological and quality-related traits in cassava.

KEY MESSAGE: More than 40 QTLs associated with 14 stress-related, quality and agro-morphological traits were identified. A catalogue of favourable SNP markers for MAS and a list of candidate genes are provided. Cassava (Manihot esculenta) is one of the most important starchy root crops in the tropics due to its adaptation to marginal environments. Genetic progress in this clonally propagated crop can be accelerated through the discovery of markers and candidate genes that could be used in cassava breeding programs. We carried out a genome-wide association study (GWAS) using a panel of 5130 clones developed at the International Institute of Tropical Agriculture-Nigeria. The population was genotyped at more than 100,000 SNP markers via genotyping-by-sequencing (GBS). Genomic regions underlying genetic variation for 14 traits classified broadly into four categories: biotic stress (cassava mosaic disease and cassava green mite severity); quality (dry matter content and carotenoid content) and plant agronomy (harvest index and plant type) were investigated. We also included several agro-morphological traits related to leaves, stems and roots with high heritability. In total, 41 significant associations were uncovered. While some of the identified loci matched with those previously reported, we present additional association signals for the traits. We provide a catalogue of favourable alleles at the most significant SNP for each trait-locus combination and candidate genes occurring within the GWAS hits. These resources provide a foundation for the development of markers that could be used in cassava breeding programs and candidate genes for functional validation.

High-resolution mapping of resistance to cassava mosaic geminiviruses in cassava using genotyping-by-sequencing and its implications for breeding.

Cassava mosaic disease (CMD), caused by different species of cassava mosaic geminiviruses (CMGs), is the most important disease of cassava in Africa and the Indian sub-continent. The cultivated cassava species is protected from CMD by polygenic resistance introgressed from the wild species Manihot glaziovii and a dominant monogenic type of resistance, named CMD2, discovered in African landraces. The ability of the monogenic resistance to confer high levels of resistance in different genetic backgrounds has led recently to its extensive usage in breeding across Africa as well as pre-emptive breeding in Latin America. However, most of the landraces carrying the monogenic resistance are morphologically very similar and come from a geographically restricted area of West Africa, raising the possibility that the diversity of the single-gene resistance could be very limited, or even located at a single locus. Several mapping studies, employing bulk segregant analysis, in different genetic backgrounds have reported additional molecular markers linked to supposedly new resistance genes. However, it is not possible to tell if these are indeed new genes in the absence adequate genetic map framework or allelism tests. To address this important question, a high-density single nucleotide polymorphism (SNP) map of cassava was developed through genotyping-by-sequencing a bi-parental mapping population (N=180) that segregates for the dominant monogenic resistance to CMD. Virus screening using PCR showed that CMD symptoms and presence of virus were strongly correlated (r=0.98). Genome-wide scan and high-resolution composite interval mapping using 6756 SNPs uncovered a single locus with large effect (R(2)=0.74). Projection of the previously published resistance-linked microsatellite markers showed that they co-occurred in the same chromosomal location surrounding the presently mapped resistance locus. Moreover, their relative distance to the mapped resistance locus correlated with the reported degree of linkage with the resistance phenotype. Cluster analysis of the landraces first shown to have this type of resistance revealed that they are very closely related, if not identical. These findings suggest that there is a single source of monogenic resistance in the crop's genepool tracing back to a common ancestral clone. In the absence of further resistance diversification, the long-term effectiveness of the single gene resistance is known to be precarious, given the potential to be overcome by CMGs due to their fast-paced evolutionary rate. However, combining the quantitative with the qualitative type of resistance may ensure that this resistance gene continues to offer protection to cassava, a crop that is depended upon by millions of people in Africa against the devastating onslaught of CMGs.