SweetGAINS: Genetics Advances and Innovative Seed Systems for Sweet Potato

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Color and Grey-Level Co-Occurrence Matrix Analysis for Predicting Sensory and Biochemical Traits in Sweet Potato and Potato
(Journal Article, 2024-10-30) Nantongo, J.S.; Serunkuma, E.; Nakitto, M.; Kitalikyawe, J.; Mendes, T.; Davrieux, F.; Ssali, R.T.
In sweet potato and potato, sensory traits are critical for acceptance by consumers, growers, and traders, hence underpinning the success or failure of a new cultivar. A quick analytical method for the sensory traits could expedite the selection process in breeding programs. In this paper, the relationship between sensory panel and instrumental color plus texture features was evaluated. Results have shown a high correlation between the sensory panel and instrumental color in both sweet potato (up to r = 0.84) and potato (r > 0.78), implying that imaging is a potential alternative to the sensory panel for color scoring. High correlations between sensory panel aroma and flavor with instrumental color were detected (up to r = 0.66), although the validity of these correlations needs to be tested. With instrumental color and texture parameters as predictors, low to moderate accuracy was detected in the machine learning models developed to predict sensory panel traits. Overall, the performance of the eXtreme Gradient Boosting (XGboost) was comparable to the radial-based support vector machine (NL-SVM) algorithm, and these could be used for the initial selection of genotypes for aromas and flavors (r2 = 0.64–0.72) and texture attributes like moisture or mealiness (r2 > 50). Among the chemical properties screened in sweet potato, only starch showed a moderate correlation with sensory features like mealiness (r = 0.54) and instrumental color (r = 0.65). From the results, we can conclude that the instrumental scores of color are equivalent to those scored by the sensory panel, and the former could be adopted for quick analysis. Further investigations may be required to understand the association between color and aroma or flavor.
Near infrared spectroscopy models to predict sensory and texture traits of sweetpotato roots
(Journal Article, 2024-06-14) Nantongo, J.S.; Serunkuma, E.; Davrieux, F.; Nakitto, M.; Burgos, G.; Thomas, Z.F.; Eduardo, P.; Carey, T.; Swankaert, J.; Mwanga, R.O.M.; Alamu, E.O.; Ssali, R.T.
High-throughput phenotyping technologies successfully employed in plant breeding and precision agriculture could facilitate the screening process for developing consumer-preferred traits. The current study evaluated the potential of near infrared (NIR) spectroscopy to predict visual, aromatic, flavor, taste and texture traits of sweetpotatoes. The focus was to develop predicting models that would be cost-effective, efficient and high throughput. The roots of 207 sweetpotato genotypes from six agroecological zones of Uganda were collected from breeding trials. The spectra were collected in the wavelengths of 400 – 2500 nm at 2 nm intervals. Using the plsR package, the calibrations were carried out using external validation models. The best calibration equation between the sensory and texture reference values (10-point scales) and spectral data was identified based on the highest coefficient of determination (R2) and smallest RMSE in calibration and validation. Of the visual traits, orange color intensity was well calibrated using NIR spectroscopy (R2val = 0.92, SEP = 0.92), and the model is sufficient for field application. Pumpkin aroma (R2val = 0.67, SEP = 0.33) was the highest predicted among the aromas. The pumpkin flavour model exhibited the highest coefficient of determination in the calibration (R2val = 0.52, SEP = 0.45) for the traits considered under flavor and taste. Different models for textural traits exhibited moderate calibration coefficients: mealiness (chalky/floury) by hand (R2val = 0.75; SEP = 1.31), crumbliness (R2val = 0.73, SEP = 1.21), moisture in mass (R2val = 0.73, SEP = 1.26), fracturability (R2val = 0.60, SEP = 1.52), hardness by hand (R2val = 0.61, SEP = 1.27) and dry matter (R2val = 0.70, SEP = 3.10). The range error ratio (RER) values were mostly >6.0. These models could be used for preliminary screening. The predictability of the traits varied among different modes of samples. Models could be improved with an increased range of reference values and/or exploiting the correlations between chemical compounds and sensory traits.
Gender-differentiated preference for sweetpotato traits and their drivers among smallholder farmers: Implications for breeding
(Journal Article, 2024-02) Namirimu, J.; Okello, J.J.; Kizito, A.M.; Ssekiboobo, A.
To improve sweetpotato (Ipomoea batatas L.) productivity, several improved high-yielding varieties have been developed by breeders. However, many farmers still grow low-yielding landraces. Farmers choose varieties to grow based on their preference for the attributes of those varieties. Varietal preferences have been shown to differ between males and females. This study assessed farmer preferences for sweetpotato traits and the factors that drive the choice of most preferred traits. It used a uniquely large data set collected through personal interviews with male and female sweetpotato growers. The study employed multinomial probit regression to examine the drivers of trait preference. It finds a higher preference for production-oriented traits among farmers in general and especially older ones. This is, however, lower among more educated farmers who mainly prefer risk-averting traits, and those growing local varieties who mainly prefer quality traits. Hence, alongside production-oriented traits, other traits critical for the acceptance of new varieties by farmers in their respective contexts should not be ignored.
Gender Mainstreaming in Sweetpotato Breeding in Uganda: A Case Study
(Journal Article, 2023-12-15) Ssali, R.T.; Mayanja, S.; Nakitto, M.; Mutiso, J.; Tinyiro, S.E.; Bayiyana, I.; Okello, J.J.; Forsythe, L.; Magala, D.; Yada, B.; Mwanga, Robert O.M.; Polar, Vivian
Purpose: In Uganda, sweetpotato (Ipomoea batatas (L.) Lam) is typically a "woman's crop", grown, processed, stored and also mainly consumed by smallholder farmers for food and income. Farmers value sweetpotato for its early maturity, resilience to stresses, and minimal input requirements. However, productivity remains low despite the effort of breeding programs to introduce new varieties. Low uptake of new varieties is partly attributed to previous focus by breeders on agronomic traits and much less on quality traits and the diverse preferences of men and women in sweetpotato value chains.To address this gap, breeders, food scientists, and social scientists (including gender specialists) systematically mainstreamed gender into the breeding program. This multidisciplinary approach, grounded in examining gender roles and their relationship with varietal and trait preferences, integrated important traits into product profiles.Results: Building on earlier efforts of participatory plant breeding and participatory varietal selection, new interventions showed subtle but important gender differences in preferences. For instance, in a study for the RTBFoods project, women prioritized mealiness, sweetness, firmness and non-fibrous boiled roots. These were further subjected to a rigorous gender analysis using the G+ product profile query tool. The breeding pipelines then incorporated these gender-responsive priority quality traits, prompting the development of standard operating procedures to phenotype these traits. This is a provisional file, not the final typeset article Conclusion: Following an all-inclusive approach coupled with traininig of multidisciplinary teams involving food scientists, breeders, biochemists, gender specialists and social scientists, integration into participatory variety selection in Uganda enabled accentuation of women and men's trait preferences, contributing to clearer breeding targets. The research has positioned sweetpotato breeding to better respond to the varying needs and preferences of the users.
High-throughput characterization and phenotyping of resistance and tolerance to virus infection in sweetpotato
(Journal Article, 2023-11-25) Kreuze, Jan F.; Ramírez, D.; Fuentes, S.; Loayza, H.; Ninanya, J.; Rinza, J.; David, M.; Gamboa, S.; Boeck, B. de; Díaz, F.; Pérez, A.; Silva, L.; Campos, Hugo
Breeders have made important efforts to develop genotypes able to resist virus attacks in sweetpotato, a major crop providing food security and poverty alleviation to smallholder farmers in many regions of Sub-Saharan Africa, Asia and Latin America. However, a lack of accurate objective quantitative methods for this selection target in sweetpotato prevents a consistent and extensive assessment of large breeding populations. In this study, an approach to characterize and classify resistance in sweetpotato was established by assessing total yield loss and virus load after the infection of the three most common viruses (SPFMV, SPCSV, SPLCV). Twelve sweetpotato genotypes with contrasting reactions to virus infection were grown in the field under three different treatments: pre-infected by the three viruses, un-infected and protected from re-infection, and un-infected but exposed to natural infection. Virus loads were assessed using ELISA, (RT-)qPCR, and loop-mediated isothermal amplification (LAMP) methods, and also through multispectral reflectance and canopy temperature collected using an unmanned aerial vehicle. Total yield reduction compared to control and the arithmetic sum of (RT-)qPCR relative expression ratios were used to classify genotypes into four categories: resistant, tolerant, susceptible, and sensitives. Using 14 remote sensing predictors, machine learning algorithms were trained to classify all plots under the said categories. The study found that remotely sensed predictors were effective in discriminating the different virus response categories. The results suggest that using machine learning and remotely sensed data, further complemented by fast and sensitive LAMP assays to confirm results of predicted classifications could be used as a high throughput approach to support virus resistance phenotyping in sweetpotato breeding.
Willingness to pay for quality traits and implications for sweetpotato variety breeding: case of Mozambique
(Report, 2023-02) Mulwa, C.K.; Tomo, A.; Mudema, J.; Makunde, G.S.; Andrade, M.I.; Ssali, R.T.; Abdul, N.; Campos, Hugo
Despite decades of research and dissemination of improved sweetpotato varieties, uptake at scale remains low and envisaged development goals of food security and livelihoods remain elusive. This is despite demonstrated impacts of such technologies in combating food and nutrition insecurity, amidst global challenges like climate change. Growing evidence show that end-user acceptance of improved varieties is critical in the widespread adoption of such varieties, and inclusion of the heterogenous preferences of diverse sets of end-users in the variety development process is therefore critical. With global changes in weather and consumption patterns, end-users are now demanding varieties that are more suitable to their unique consumption needs, production environments, new market demands and have desired processing characteristics. Such dynamics in demand have necessitated rethinking of breeding programs from the traditional focus on agronomic gains such as increase in yields and yield protection, to consideration of more nuanced quality-related traits that appeal to targeted populations. Against this background, this study sets out to explore the decision-making behavior of Mozambican sweetpotato producers in variety selection, and the implicit value placed on different sweetpotato traits, including the often ignored but crucial quality traits. The aim of the study is to identify the economic valuation of such traits and how they are traded off in variety selection decisions, to allow for prioritization in breeding efforts. To achieve this, an exploratory sequential design in a predominantly quantitative mixed-method design was adopted for the study. First, based on the insights from a gender disaggregated qualitative assessment among sweetpotato growers and consumers and in consultation with breeding experts from Mozambique, the most preferred sweetpotato variety traits in the regions of study were established. These traits were then utilized in the design of a choice experiment, implemented among 860 sweetpotato producers spread across four sweetpotato growing regions in the country. Finally, a generalized multinomial logit model was used to estimate implicit economic valuation of each of the considered trait, as well as heterogenous valuation of such traits across gender, education and age of respondent groups. Results from the study show that producers have a high preference for quality-related traits, with preference for Vitamin A being higher than that for drought tolerance, while dry matter content is valued about the same as drought tolerance. While scoring significantly lower than Vitamin A, drought tolerance and dry matter content, other quality-related traits like root size and sweet taste also have significant positive values implying their importance in informing sweetpotato variety choice. In terms of gender heterogeneity, flesh color is highly valued among the women sub-sample. The study identifies Vitamin A, dry matter content, sweet taste, and medium to big root size, as the key preferred quality traits in Mozambique, in that order. The results imply that these quality traits should be pursued as a suite in breeding objectives, in combination with essential agronomic traits such as high yields and drought tolerance, for higher acceptance and demand of improved sweetpotato varieties across the country.
Using machine learning for image-based analysis of sweetpotato root sensory attributes
(Journal Article, 2023-10) Nakatumba-Nabende, J.; Babirye, C.; Tusubira, J.; Mutegeki, H.; Nabiryo, A.; Murindanyi, S.; Katumba, A.; Nantongo, J.S.; Sserunkuma, E.; Nakitto, M.; Ssali, R.T.; Makunde, G.S.; Moyo, M.; Campos, Hugo
The sweetpotato breeding process involves assessing different phenotypic traits, such as the sensory attributes, to decide which varieties to progress to the next stage during the breeding cycle. Sensory attributes like appearance, taste, colour and mealiness are important for consumer acceptability and adoption of new varieties. Therefore, measuring these sensory attributes is critical to inform the selection of varieties during breeding. Current methods using a trained human panel enable screening of different sweetpotato sensory attributes. Despite this, such methods are costly and time-consuming, leading to low throughput, which remains the biggest challenge for breeders. In this paper, we describe an approach to apply machine learning techniques with image-based analysis to predict flesh-colour and mealiness sweetpotato sensory attributes. The developed models can be used as highthroughput methods to augment existing approaches for the evaluation of flesh-colour and mealiness for different sweetpotato varieties. The work involved capturing images of boiled sweetpotato cross-sections using the DigiEye imaging system, data pre-processing for background elimination and feature extraction to develop machine learning models to predict the flesh-colour and mealiness sensory attributes of different sweetpotato varieties. For flesh-colour the trained Linear Regression and Random Forest Regression models attained 𝑅2 values of 0.92 and 0.87, respectively, against the ground truth values given by a human sensory panel. In contrast, the Random Forest Regressor and Gradient Boosting model attained 𝑅2 values of 0.85 and 0.80, respectively, for the prediction of mealiness. The performance of the models matched the desirable 𝑅2 threshold of 0.80 for acceptable comparability to the human sensory panel showing that this approach can be used for the prediction of these attributes with high accuracy. The machine learning models were deployed and tested by the sweetpotato breeding team at the International Potato Center in Uganda. This solution can automate and increase throughput for analysing flesh-colour and mealiness sweetpotato sensory attributes. Using machine learning tools for analysis can inform and quicken the selection of promising varieties that can be progressed for participatory evaluation during breeding cycles and potentially lead to increased chances of adoption of the varieties by consumers.
Building sustainable business model(s) for sweetpotato Commercial Seed Producers in Tanzania and Uganda
(Brief, 2023-06) Rajendran, S.; Edson, S.; McEwan, M.
Guidelines for construction and management of mini screenhouse for sweetpotato seed production
(Manual, 2023-03) Namanda, S.; Oloka, B.M.; Rajendran, S.; McEwan, M.; Namazzi, S.; Ogero, K.; Mwanga, Robert O.M.; Low, Jan W.; Adikini, S.; Kyalo, Gerald; Talengera, D.; Mukasa, S.; Omongo, C.; Campos, Hugo; Yada, B.; Bazalaki, S.
Field production of quality sweetpotato planting material
(Brief, 2023-05) Ogero, K.; McEwan, M.; Namanda, S.
Ratooning increases production of sweetpotato seed vines multiplied in insect-proof net tunnels in Tanzania
(Journal Article, 2023) Ogero, K.; Okuku, H.S.; McEwan, M.; Almekinders, Conny J.M.; Kreuze, Jan F.; Struik, P.C.; Vlugt, R. van der.
Insect-proof net tunnels can help reduce virus infection of clean virus-tested sweetpotato seed produced by decentralized seed producers. However, optimal management is required to maintain both quality and quantity of seed produced. This study investigated the effect of the ratoon cropping technique on vine production in net tunnels and open fields. Virus-tested planting material of two varieties, Kabode and Mataya, were grown in net tunnels and open fields. Each variety had 80 plants per plot, with 40 following the ratooning technique and 40 a replanting technique. The ratooned crop was harvested six times, comprising the initial harvest and five regrowths. This covered 14 months representing six generations of vine production. The number of vines, number of nodes per vine, and vine length were recorded. The number of plants showing virus symptoms was also recorded. The ratoon cropping technique produced more vines compared with the replanting technique in both net tunnels and open fields. Cv. Kabode produced more vines in open fields compared with net tunnels regardless of cropping technique. On the other hand, cv. Mataya produced relatively equal numbers of vines in net tunnels and open fields. Despite ratooning leading to more vine production compared with replanting, the technique led to higher virus incidences on plants grown in the open. This also varied with variety with the highest virus disease incidences being recorded on cv. Mataya. We recommend the ratoon cropping technique for sweetpotato vine production in net tunnels. Replanting technique should be adopted for vine production in the open fields because it acts as a key control strategy for virus infections even for susceptible varieties.
Producing quality seed to harness sweetpotato’s productive potential
(Brief, 2023-05) International Potato Center
A farmer-participatory approach to boost adoption of new varieties
(Brief, 2023-05) International Potato Center
Promoting rapid multiplication of sweetpotato seed in Tanzania
(Brief, 2023-05) International Potato Center
Degeneration of cleaned-up, virus-tested sweetpotato seed vines in Tanzania
(Journal Article, 2023-07) Ogero, K.; Okuku, H.S.; Wanjala, Bramwel W.; McEwan, M.; Almekinders, Conny J.M.; Kreuze, Jan F.; Struik, P.C.; Vlugt, R. van der.
Viruses pose a major challenge to sweetpotato production in Tanzania. Use of cleaned-up, virus-tested seed vines distributed through a formal seed system is among the proposed strategies to address this challenge. However, virus-tested seed vines can get infected once in the field and it is not known how they will perform following several seasons of on farm propagation. We assessed the performance of virus-tested seed vines and farmer-sourced seed vines of a susceptible variety, Ejumula, and a relatively tolerant variety, Kabode, over five seasons to understand the trend in root yields, vine yields and virus incidences. The experiments were done in high and low virus pressure areas. The most prevalent viruses were sweet potato chlorotic stunt virus (SPCSV) followed by sweet potato feathery mottle virus (SPFMV) and sweet potato leaf curl virus (SPLCV), respectively. Both farmer-sourced and cleaned-up, virus-tested seed of cv. Ejumula were rapidly infected with SPCSV. The incidence of this virus on Ejumula's farmer-sourced material at the high-virus-pressure area reached 100% by the second season. The incidences for all three viruses remained stable for cv. Kabode across the five seasons. Plants generated from cleaned-up, virus-tested seed had lower incidences for all viruses compared to those from farmer-sourced planting material. Virus-tested seed produced significantly higher root yields for cv. Ejumula in the high-virus-pressure site, with a gradual drop across the seasons. The findings show that regular replenishment of clean, virus-tested seed is more economical in high-virus-pressure areas and for more susceptible varieties like cv. Ejumula. They also indicate that farmers may be reluctant to invest in cleaned-up, virus-tested seed in cases where they have virus-tolerant varieties such as cv. Kabode due to lack of obvious virus effect on yields.
Gender dynamics in seed systems: female makeover or male takeover of specialized sweetpotato seed production, in Lake Zone Tanzania?
(Journal Article, 2023-06) McEwan, M.; Matui, M.S.; Mayanja, S.; Namanda, S.; Ogero, K.
Interest is growing for the development of inclusive seed production models. However, there is limited understanding of gender-based roles and constraints and how these might influence gender relations in seed production. Through a case study on sweetpotato seed production in Lake Zone Tanzania, this article examines men’s and women’s roles in seed production with the introduction of specialized seed practices and a commercial orientation. The study uses data from 17 field-based plot observations and eight sex disaggregated focus group discussions (FGDs) with 33 (51% women and 48% men) decentralized vine multipliers (DVMs). Participatory, gender-based analytical tools were used to obtain an in-depth understanding of gender dimensions and implications of new seed production practices, the resources required and access to those resources. Our findings show that men and women have complementary roles in specialized seed production, and that men increased their involvement in production and commercialization, especially when larger monetary inputs and transactions took place. Women gained new tangible (income) and intangible (knowledge) assets, which enhanced their community status. Women’s contributions to household income became more visible. In conclusion male-takeover did not take place. There were changes in the perceptions around sweetpotato production and gender relations. As women’s contributions to household income became more visible, they were able to negotiate with their husbands on access to key resources to maintain this household revenue stream. We discuss how the new knowledge and skills related to seed production enhanced women’s status in the community. These dynamics initiated changes in gender relations and challenged prevailing community perceptions on gender roles.
Securing Sweetpotato Planting Material for Farmers in Dryland Africa: Gender-Responsive Communication Approaches to Scale Triple S
(Book Chapter, 2022) McEwan, M.; Mourik, Tom A. van; Hundayehu, M.C.; Asfaw, F.; Namanda, S.; Suleman, I.; Mayanja, S.; Imoro, S.; Etwire, P.M.
Triple S (Storage in Sand and Sprouting) is a root-based system for conserving and multiplying sweetpotato planting material at the household level. In sub-Saharan Africa, farmers predominantly source planting material by cutting vines from volunteer plants that sprout from roots left in the field from a previous crop. However, it takes 6 to 8 weeks after the rains start to produce enough vines for planting material, and normally these vines are infected by sweetpotato diseases and pests carried over from previous crops. Where rainfall is unpredictable, farmers can use Triple S to take advantage of the whole growing season, planting and harvesting early to obtain food, higher yields, and income. Triple S facilitates household retention and adoption of new sweetpotato varieties, notably the beta-carotene-rich, orange-fleshed varieties. Triple S PLUS is the combined innovation package of core Triple S components and complementary components used to scale the innovation. These included good agricultural practices, different storage containers, local multiplication and sales of planting material, and a multimedia communication strategy for training and extension to encourage the uptake of Triple S. Components were at different levels of scaling readiness. This chapter explores evidence from Ethiopia and Ghana (2018–2019) on the extent to which exposure to different communication channels and their combinations influenced the uptake of Triple S PLUS by male and female farmers, the partnering arrangements that supported this, and the resulting changes in food security. We discuss implications for future scaling initiatives.
Combining ability and heritability analysis of sweetpotato weevil resistance, root yield, and dry matter content in sweetpotato
(Journal Article, 2022-09-07) Mugisa, I.; Karungi, J.; Musana, P.; Odama, R.; Alajo, A.; Chelangat, D.M.; Anyanga, M.O.; Oloka, B.M.; Gonçalves dos Santos, I.; Talwana, Herbert A.L.; Ochwo-Ssemakula, Mildred; Edema, Richard; Gibson, P.; Ssali, R.T.; Campos, Hugo; Olukolu, B.A.; Silva Pereira, G. da; Yencho, C.; Yada, B.
Efficient breeding and selection of superior genotypes requires a comprehensive understanding of the genetics of traits. This study was aimed at establishing the general combining ability (GCA), specific combining ability (SCA), and heritability of sweetpotato weevil (Cylas spp.) resistance, storage root yield, and dry matter content in a sweetpotato multi-parental breeding population. A population of 1,896 F1 clones obtained from an 8 × 8 North Carolina II design cross was evaluated with its parents in the field at two sweetpotato weevil hotspots in Uganda, using an augmented row-column design. Clone roots were further evaluated in three rounds of a no-choice feeding laboratory bioassay. Significant GCA effects for parents and SCA effects for families were observed for most traits and all variance components were highly significant (p ≤ 0.001). Narrow-sense heritability estimates for weevil severity, storage root yield, and dry matter content were 0.35, 0.36, and 0.45, respectively. Parental genotypes with superior GCA for weevil resistance included “Mugande,” NASPOT 5, “Dimbuka-bukulula,” and “Wagabolige.” On the other hand, families that displayed the highest levels of resistance to weevils included “Wagabolige” × NASPOT 10 O, NASPOT 5 × “Dimbuka-bukulula,” “Mugande” × “Dimbuka-bukulula,” and NASPOT 11 × NASPOT 7. The moderate levels of narrow-sense heritability observed for the traits, coupled with the significant GCA and SCA effects, suggest that there is potential for their improvement through conventional breeding via hybridization and progeny selection and advancement. Although selection for weevil resistance may, to some extent, be challenging for breeders, efforts could be boosted through applying genomics-assisted breeding. Superior parents and families identified through this study could be deployed in further research involving the genetic improvement of these traits.
Sensory guided selection criteria for breeding consumer-preferred sweetpotatoes in Uganda
(Journal Article, 2022-10) Nakitto, M.; Johanningsmeier, S.D.; Moyo, M.; Bugaud, C.; Kock, H. de; Dahdouh, L.; Forestier-Chiron, N.; Ricci, J.; Khakasa, E.; Ssali, R.T.; Mestres, C.; Muzhingi, T.
Prioritizing sensory attributes and consumer evaluation early in breeding trials to screen for end-user preferred traits could improve adoption rates of released genotypes. In this study, a lexicon and protocol for descriptive sensory analysis (DSA) was established for sweetpotato and used to validate an instrumental texture method for which critical values for consumer preference were set. The study comprised several phases: lexicon development during a 4-day workshop; 3-day intensive panel training; follow-up virtual training, evaluation of 12 advanced genotypes and 101 additional samples from two trials in 2021 by DSA and instrumental texture analysis using TPA double compression; and DSA, instrumental texture analysis and consumer acceptability tests on 7 genotypes in on-farm trials. The established sweetpotato lexicon comprising 27 sensory attributes enabled characterization and differentiation of genotypes by sensory profiles. Significant correlation was found between sensory firmness by hand and mouth with TPA peak positive force (r = 0.695 and r = 0.648, respectively) and positive area (r = 0.748, r = 0.715, respectively). D20, NAROSPOT 1, NASPOT 8, and Umbrella were the most liked genotypes in on-farm trials (overall liking = 7). An average peak positive force of 3700 gf was proposed as a minimum texture value for screening sweetpotato genotypes, since it corresponded with at least 46 % of consumers perceiving sweetpotatoes as just-about-right in firmness and a minimum overall liking of 6 on average. Combining DSA with instrumental texture analysis facilitates efficient screening of genotypes in sweetpotato breeding programs.
Market Intelligence and Incentive-Based Trait Ranking for Plant Breeding: A Sweetpotato Pilot in Uganda
(Journal Article, 2022-03-04) Okello, J.J.; Swanckaert, J.; Martin Collado, Daniel; Santos, B.; Yada, B.; Mwanga, Robert O.M.; Schurink, A.; Quinn, Michael; Thiele, Graham; Heck, S.; Byrne, T.J.; Hareau, G.; Campos, Hugo
Crop breeding programs must accelerate crop improvement, spur widespread adoption of new varieties and increase variety turnover they are to meet the diverse needs of their clients. More comprehensive quantitative approaches are needed to better inform breeding programs about the preferred traits among farmers and other actors. However, the ability of current breeding programs to meet the demands of their clients is limited by the lack of insights about value chain actor preference for individual or packages of traits. Ranking traits based on monetary incentives, rather than subjective values, represents a more comprehensive, consistent, and quantitative approach to inform breeding programs. We conducted a large pilot in Uganda to assess the implementation of a novel approach to trait ranking, using a uniquely large sample of diverse sweetpotato value chain actors. We found meaningful differences in trait ranking and heterogeneity among different actors using this approach. We also show our approach’s effectiveness at uncovering unmet demand for root quality traits and at characterizing the substantial trait demand heterogeneity among value chain players. Implementing this approach more broadly for sweetpotato and other crops would increase the effectiveness of breeding programs to improve food security in developing countries.

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