Deployment and Analysis of Instance Segmentation Algorithm for In-field Grade Estimation of Sweetpotatoes

Shape estimation of sweetpotato (SP) storage roots is inherently challenging due to their varied size and shape characteristics. Even measuring "simple" metrics, such as length and width, requires significant time investments either directly in-field or afterward using automated graders. In this paper, we present the results of a model that can perform grading and provide yield estimates directly in the field quicker than manual measurements. Detectron2, a library consisting of deep-learning object detection algorithms, was used to implement Mask R-CNN, an instance segmentation model. This model was deployed for in-field grade estimation of SPs and evaluated against an optical sorter. Storage roots from various clones imaged with a cellphone during trials between 2019 and 2020, were used in the model's training and validation to fine-tune a model to detect SPs. Our results showed that the model could distinguish individual SPs in various environmental conditions including variations in lighting and soil characteristics. RMSE for length, width, and weight, from the model compared to a commercial optical sorter, were 0.66 cm, 1.22 cm, and 74.73 g, respectively, while the RMSE of root counts per plot was 5.27 roots, with r^2 = 0.8. This phenotyping strategy has the potential enable rapid yield estimates in the field without the need for sophisticated and costly optical sorters and may be more readily deployed in environments with limited access to these kinds of resources or facilities.Comment: 21 pages, 11 figure

Genetic Diversity and Population Structure of the USDA Sweetpotato (Ipomoea batatas) Germplasm Collections Using GBSpoly

Sweetpotato (Ipomoea batatas) plays a critical role in food security and is the most important root crop worldwide following potatoes and cassava. In the United States (US), it is valued at over $700 million USD. There are two sweetpotato germplasm collections (Plant Genetic Resources Conservation Unit and US Vegetable Laboratory) maintained by the USDA, ARS for sweetpotato crop improvement. To date, no genome-wide assessment of genetic diversity within these collections has been reported in the published literature. In our study, population structure and genetic diversity of 417 USDA sweetpotato accessions originating from 8 broad geographical regions (Africa, Australia, Caribbean, Central America, Far East, North America, Pacific Islands, and South America) were determined using single nucleotide polymorphisms (SNPs) identified with a genotyping-by-sequencing (GBS) protocol, GBSpoly, optimized for highly heterozygous and polyploid species. Population structure using Bayesian clustering analyses (STRUCTURE) with 32,784 segregating SNPs grouped the accessions into four genetic groups and indicated a high degree of mixed ancestry. A neighbor-joining cladogram and principal components analysis based on a pairwise genetic distance matrix of the accessions supported the population structure analysis. Pairwise FST values between broad geographical regions based on the origin of accessions ranged from 0.017 (Far East – Pacific Islands) to 0.110 (Australia – South America) and supported the clustering of accessions based on genetic distance. The markers developed for use with this collection of accessions provide an important genomic resource for the sweetpotato community, and contribute to our understanding of the genetic diversity present within the US sweetpotato collection and the species

Identification of simple sequence repeat markers for sweetpotato weevil resistance

The development of sweetpotato [Ipomoea batatas (L.) Lam] germplasm with resistance to sweetpotato weevil (SPW) requires an understanding of the biochemical and genetic mechanisms of resistance to optimize crop resistance. The African sweetpotato landrace, ‘New Kawogo’, was reported to be moderately resistant to two species of SPW, Cylas puncticollis and Cylas brunneus. Resistance has been associated with the presence of hydroxycinnamic acids esters (HCAs), but the underlying genetic basis remains unknown. To determine the genetic basis of this resistance, a bi-parental sweetpotato population from a cross between the moderately resistant, white-fleshed ‘New Kawogo’ and the highly susceptible, orange-fleshed North American variety ‘Beauregard’ was evaluated for SPW resistance and genotyped with simple sequence repeat (SSR) markers to identify weevil resistance loci. SPW resistance was measured on the basis of field storage root SPW damage severity and total HCA ester concentrations. Moderate broad sense heritability (H2 = 0.49) was observed for weevil resistance in the population. Mean genotype SPW severity scores ranged from 1.0 to 9.0 and 25 progeny exhibited transgressive segregation for SPW resistance. Mean genotype total HCA ester concentrations were significantly different (P < 0.0001). A weak but significant correlation (r = 0.103, P = 0.015) was observed between total HCA ester concentration and SPW severity. A total of five and seven SSR markers were associated with field SPW severity and total HCA ester concentration, respectively. Markers IBS11, IbE5 and IbJ544b showed significant association with both field and HCA-based resistance, representing potential markers for the development of SPW resistant sweetpotato cultivars

Internal defect scanning of sweetpotatoes using interactance spectroscopy.

While standard visible-light imaging offers a fast and inexpensive means of quality analysis of horticultural products, it is generally limited to measuring superficial (surface) defects. Using light at longer (near-infrared) or shorter (X-ray) wavelengths enables the detection of superficial tissue bruising and density defects, respectively; however, it does not enable the optical absorption and scattering properties of sub-dermal tissue to be quantified. This paper applies visible and near-infrared interactance spectroscopy to detect internal necrosis in sweetpotatoes and develops a Zemax scattering simulation that models the measured optical signatures for both healthy and necrotic tissue. This study demonstrates that interactance spectroscopy can detect the unique near-infrared optical signatures of necrotic tissues in sweetpotatoes down to a depth of approximately 5±0.5 mm. We anticipate that light scattering measurement methods will represent a significant improvement over the current destructive analysis methods used to assay for internal defects in sweetpotatoes

2014b. Phytochemical changes in phenolics, anthocyanins, ascorbic acid, and carotenoids associated with sweetpotato storage and impacts on bioactive properties. Food Chem

a b s t r a c t Sweetpotato phytochemical content was evaluated in four genotypes (NCPUR06-020, Covington, Yellow Covington, and NC07-847) at harvest and after curing/storage for 4 or 8 months. Curing and storage for up to 8 months did not significantly affect total phenolic content in Covington, Yellow Covington, and NC07-847, however for NCPUR06-020, a purple-fleshed selection, total phenolic content declined mainly due to anthocyanin degradation during storage. Covington had the highest carotenoid content at harvest time (281.9 lg/g DM), followed by NC07-847 (26.2 lg/g DM), and after 8 months, total carotenoids had increased by 25% and 50%, respectively. Antioxidant activity gradually declined during storage, and freshly harvested sweetpotatoes also demonstrated higher anti-inflammatory capacity as gauged by inhibition of lipopolysaccharide-induced reactive oxygen species (ROS) in SH-SY5Y cells. Gradual changes in sweetpotato phytochemical content and antioxidant and anti-inflammatory capacity were noted during normal long-term storage, but the specific effects were genotype-dependent

Discovery of a major QTL for root-knot nematode (Meloidogyne incognita) resistance in cultivated sweetpotato (Ipomoea batatas)

The root-knot nematode [Meloidogyne incognita (Kofoid & White) Chitwood] (RKN) causes significant storage root quality reduction and yields losses in cultivated sweetpotato [Ipomoea batatas (L.) Lam.]. In this study, resistance to RKN was examined in a mapping population consisting of 244 progenies derived from a cross (TB) between ‘Tanzania,’ a predominant African landrace cultivar with resistance to RKN, and ‘Beauregard,’ an RKN susceptible major cultivar in the USA. We performed quantitative trait loci (QTL) analysis using a random-effect QTL mapping model on the TB genetic map. An RKN bioassay incorporating potted cuttings of each genotype was conducted in the greenhouse and replicated five times over a period of 10 weeks. For each replication, each genotype was inoculated with ca. 20,000 RKN eggs, and root-knot galls were counted ~62 days after inoculation. Resistance to RKN in the progeny was highly skewed toward the resistant parent, exhibiting medium to high levels of resistance. We identified one major QTL on linkage group 7, dominant in nature, which explained 58.3% of the phenotypic variation in RKN counts. This work represents a significant step forward in our understanding of the genetic architecture of RKN resistance and sets the stage for future utilization of genomics-assisted breeding in sweetpotato breeding programs

Linkage analysis and QTL mapping in a tetraploid russet mapping population of potato

Abstract Background Genome-wide single nucleotide polymorphism (SNP) markers coupled with allele dosage information has emerged as a powerful tool for studying complex traits in cultivated autotetraploid potato (Solanum tuberosum L., 2n = 4× = 48). To date, this approach has been effectively applied to the identification of quantitative trait loci (QTLs) underlying highly heritable traits such as disease resistance, but largely unexplored for traits with complex patterns of inheritance. Results In this study, an F1 tetraploid russet mapping population (162 individuals) was evaluated for multiple quantitative traits over two years and two locations to identify QTLs associated with tuber sugar concentration, processing quality, vine maturity, and other high-value agronomic traits. We report the linkage maps for the 12 potato chromosomes and the QTL location with corresponding genetic models and candidate SNPs explaining the highest phenotypic variation for tuber quality and maturity related traits. Significant QTLs for tuber glucose concentration and tuber fry color were detected on chromosomes 4, 5, 6, 10, and 11. Collectively, these QTLs explained between 24 and 46% of the total phenotypic variation for tuber glucose and fry color, respectively. The QTL on chromosome 10 was associated with apoplastic invertases, with ‘Premier Russet’ contributing the favorable allele for fry processing quality. On chromosome 5, minor-effect QTLs for tuber glucose concentration and fry color co-localized with various major-effect QTLs, including vine maturity, growth habit, tuber shape, early blight (Altenaria tenuis), and Verticillium wilt (Verticillium spp.). Conclusions Linkage analysis and QTL mapping in a russet mapping population (A05141) using SNP dosage information successfully identified favorable alleles and candidate SNPs for resistance to the accumulation of tuber reducing sugars. These novel markers have a high potential for the improvement of tuber processing quality. Moreover, the discovery of different genetic models for traits with overlapping QTLs at the maturity locus clearly suggests an independent genetic control