End-user preferences to enhance prospects for varietal acceptance and adoption in potato breeding in Uganda.

BACKGROUND: Potato varieties have diverse biophysical characteristics, so it is important for breeders to have the capacity to choose those that meet the preferences of end users, such as mealiness, firmness, and taste, among others. Combining user preferences with descriptive information regarding the sensory characteristics of boiled potatoes can contribute to the improvement of consumer-driven varieties. This study aimed to factor in the preferences of end users to improve the prospects for varietal acceptance, adoption, and discrimination among genotypes in potato breeding. RESULTS: The priority quality traits (traits that play the most significant roles in acceptance and adoption) of the boiled potatoes were determined by evaluating gender and livelihood using the G+ tool. The G+ tool is designed to assess gender impact on roots, tubers and bananas (RTB) traits by serving as a validation check to reflect on important gender-based issues in agricultural food systems in order to reduce harm and promote positive impact. Potato genotypes were differentiated by penetration (textural parameters as measured by standard texture probe) and the procedure was repeatable, as there was no significant difference between the cooking replicates at 40 min of cooking. Instrument-based texture parameters, such as penetration peak force (hardness/firmness) and area (area under the curve, which represents energy needed to penetrate) of boiled potato tubers were significantly associated with sensory attributes such as fracturability and hardness in the mouth. An attempt to differentiate genotypes using near-infrared spectroscopy (NIRS) revealed that the average results observed for the calibration for yellow color (r2 = 0.70), homogeneity of color (r2 = 0.48), moisture in mass (r2 = 0.40), and uniformity of texture (r2 = 0.56) suggested that these parameters could be used for initial breeding screening purposes. CONCLUSIONS: The preferred traits of the boiled potato can be integrated into the potato-breeding program/product profile. Near-infrared spectroscopy shows strong potential to predict potato color and the ability of NIRS models to predict some texture attributes is also promising. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Combined use of sensory methods for the selection of root, tuber and banana varieties acceptable to end-users.

BACKGROUND: The assessment of user acceptability in relation to crop quality traits should be a full part of breeding selection programs. Our methodology is based on a combination of sensory approaches aiming to evaluate the sensory characteristics and user acceptability of root, tuber and banana (RTB) varieties. RESULTS: The four-stepped approach links sensory characteristics to physicochemical properties and end-user acceptance. It starts with the development of key quality traits using qualitative approaches (surveys and ranking) and it applies a range of sensory tests such as Quantitative Descriptive Analysis with a trained panel, Check-All-That-apply, nine-point hedonic scale and Just-About-Right with consumers. Results obtained on the same samples from the consumer acceptance, sensory testing and physicochemical testing are combined to explore correlations and develop acceptability thresholds. CONCLUSION: A combined qualitative and quantitative approach involving different sensory techniques is necessary to capture sensory acceptance of products from new RTB clones. Some sensory traits can be correlated with physicochemical characteristics and could be evaluated using laboratory instruments (e.g. texture). Other traits (e.g. aroma and mealiness) are more difficult to predict, and the use of a sensory panel is still necessary. For these latter traits, more advanced physicochemical methods that could accelerate the breeding selection through high throughput phenotyping are still to be developed. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Decision tree scoring system to guide selection for consumer preference in sweetpotato breeding trials.

BACKGROUND: Previously, a lexicon and protocol for quantitative descriptive analysis (QDA) was established for the Uganda sweetpotato breeding program. The implication of QDA scores for priority sensory attributes on consumer preference should be determined to interpret results efficiently and make decisions effectively. The present study aimed to develop a gender-responsive decision tree to obtain an overall sweetpotato eating quality score to facilitate demand-led targeted breeding selection. It focused on Kamuli and Hoima districts (Uganda) and uses pre-lease advanced clones ('NKB3', 'NKB105', 'NKB135', 'D11' and 'D20'), released varieties ('NASPOT 8' and 'NAROSPOT 1') and landraces ('Muwulu-Aduduma', 'Umbrella'). RESULTS: Including boiled sweetpotato sensory characteristics, namely mealy, sweet taste, sweetpotato smell, firm and not fibrous, in breeding design would benefit end-users, especially women given their role in varietal selection, food preparation and marketing. 'D20', 'NASPOT 8' and 'NAROSPOT 1' were most liked in both districts. 'NKB3' and 'D11' were the least liked in Hoima, whereas 'Muwulu-Aduduma' was the least liked in Kamuli. There was a positive correlation between color and overall liking (r2 = 0.8) and consumers liked the color (average rating ≥ 6 on a nine-point hedonic scale) of all genotypes. Threshold values (average rating on 11-point scales) for consumer acceptability were identified (sweet taste = 6, sweetpotato aroma and flavor = 6, firmness = 3, and mealiness = 4). A regression decision tree tool was created to calculate an eating quality selection index when screening lines in breeding programs using the values. CONCLUSION: Decision trees that include consumer needs and gender considerations would facilitate demand-led breeding and make varietal selection in sweetpotato breeding programs more effective. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Contrasting effects of polysaccharide components on the cooking properties of roots, tubers and bananas.

BACKGROUND: Consumer preferences for boiled or fried pieces of roots, tubers and bananas (RTBs) are mainly related to their texture. Different raw and cooked RTBs were physiochemically characterized to determine the effect of biochemical components on their cooking properties. RESULTS: Firmness in boiled sweetpotato increases with sugar and amylose contents but no significant correlation was observed between other physicochemical characteristics and cooking behaviour. Hardness of boiled yam can be predicted by dry matter (DM) and galacturonic acid (GalA) levels. For cassava, no significant correlation was found between textural properties of boiled roots and DM, but amylose and Ca2+ content were correlated with firmness, negatively and positively, respectively. Water absorption of cassava root pieces boiled in calcium chloride solutions was much lower, providing indirect evidence that pectins are involved in determining cooking quality. A highly positive correlation between textural attributes and DM was observed for fried plantain, but no significant correlation was found with GalA, although frying slightly reduced GalA. CONCLUSION: The effect of main components on texture after cooking differs for the various RTBs. The effect of global DM and major components (i.e. starch, amylose) is prominent for yam, plantain and sweetpotato. Pectins also play an important role on the texture of boiled yam and play a prominent role for cassava through interaction with Ca2+ . © 2023 Bill and Melinda Gates Foundation. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Review of instrumental texture measurements as phenotypic tool to assess textural diversity of root, tuber and banana food products.

Roots, tubers and bananas (RTBs) contribute immensely to food security and livelihoods in sub-Saharan Africa, Asia and Latin America. The adoption of RTB genotypes in these regions relies on the interplay among agronomic traits, ease of processing and consumer preference. In breeding RTBs, until recently little attention was accorded key textural traits preferred by consumers. Moreover, a lack of standard, discriminant, repeatable protocols that can be used to measure the textural traits deter linkages between breeding better RTB genotypes and end user/consumer preferences. RTB products texture - that is, behaviour of RTB food products under unique deformations, such as disintegration and the flow of a food under force - is a critical component of these preferences. The preferences consumers have for certain product texture can be evaluated from expert sensory panel and consumer surveys, which are useful tools in setting thresholds for textural traits, and inform breeders on what to improve in the quality of RTBs. Textural characterization of RTBs under standard operating procedures (SOPs) is important in ensuring the standardization of texture measurement conditions, predictability of textural quality of RTBs, and ultimately definition of RTB food product profiles. This paper reviews current SOPs for the textural characterization of RTBs, including their various associated methods, parameters, challenges and merits. Case studies of texture characterized during development of SOPs and evaluation of texture of RTB populations are discussed, together with insights into key textural attributes and correlations between instrumental, sensory and consumer assessment of texture unique to various RTB food products. Hardness was considered a universal key textural attribute to discriminate RTBs. The review should provide adequate insight into texture of RTB food products and critical factors in their measurement. It aims to promote inclusion of texture in breeding pipelines by investigating which textural traits are prioritized by consumers, particularly since the inclusion of textural traits has recently gained prominence by breeders in improving RTBs. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Connecting data for consumer preferences, food quality, and breeding in support of market-oriented breeding of root, tuber, and banana crops.

The 5-year project 'Breeding roots, tubers and banana products for end user preferences' (RTBfoods) focused on collecting consumers' preferences on 12 food products to guide breeding programmes. It involved multidisciplinary teams from Africa, Latin America, and Europe. Diverse data types were generated on preferred qualities of users (farmers, family and entrepreneurial processors, traders or retailers, and consumers). Country-based target product profiles were produced with a comprehensive market analysis, disaggregating gender's role and preferences, providing prioritised lists of traits for the development of new plant varieties. We describe the approach taken to create, in the roots, tubers, and banana breeding databases, a centralised and meaningful open access to sensory information on food products and genotypes. Biochemical, instrumental textural, and sensory analysis data are then directly connected to the specific plant record while user survey data, bearing personal information, were analysed, anonymised, and uploaded in a repository. Names and descriptions of food quality traits were added into the Crop Ontology for labelling data in the databases, along with the various methods of measurement used by the project. The development and application of standard operating procedures, data templates, and adapted trait ontologies improved the data quality and its format, enabling the linking of these to the plant material studied when uploaded in the breeding databases or in repositories. Some modifications to the database model were necessary to accommodate the food sensory traits and sensory panel trials. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Sensory guided selection criteria for breeding consumer-preferred sweetpotatoes in Uganda.

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.

Machine learning methods in near infrared spectroscopy for predicting sensory traits in sweetpotatoes.

It has been established that near infrared (NIR) spectroscopy has the potential of estimating sensory traits given the direct spectral responses that these properties have in the NIR region. In sweetpotato, sensory and texture traits are key for improving acceptability of the crop for food security and nutrition. Studies have statistically modelled the levels of NIR spectroscopy sensory characteristics using partial least squares (PLS) regression methods. To improve prediction accuracy, there are many advanced techniques, which could enhance modelling of fresh (wet and un-processed) samples or nonlinear dependence relationships. Performance of different quantitative prediction models for sensory traits developed using different machine learning methods were compared. Overall, results show that linear methods; linear support vector machine (L-SVM), principal component regression (PCR) and PLS exhibited higher mean R2 values than other statistical methods. For all the 27 sensory traits, calibration models using L-SVM and PCR has slightly higher overall R2 (x¯ = 0.33) compared to PLS (x¯ = 0.32) and radial-based SVM (NL-SVM; x¯= 0.30). The levels of orange color intensity were the best predicted by all the calibration models (R2 = 0.87 - 0.89). The elastic net linear regression (ENR) and tree-based methods; extreme gradient boost (XGBoost) and random forest (RF) performed worse than would be expected but could possibly be improved with increased sample size. Lower average R2 values were observed for calibration models of ENR (x¯ = 0.26), XGBoost (x¯ = 0.26) and RF (x¯ = 0.22). The overall RMSE in calibration models was lower in PCR models (X = 0.82) compared to L-SVM (x¯ = 0.86) and PLS (x¯ = 0.90). ENR, XGBoost and RF also had higher RMSE (x¯ = 0.90 - 0.92). Effective wavelengths selection using the interval partial least-squares regression (iPLS), improved the performance of the models but did not perform as good as the PLS. SNV pre-treatment was useful in improving model performance.

Baked sweetpotato textures and sweetness: An investigation into relationships between physicochemical and cooked attributes.

Sweetpotato varieties vary greatly in perceived textures and sweetness. This study identified physicochemical factors that influence these attributes in cooked sweetpotatoes. Fifteen genotypes grown on three plots were baked and evaluated by a trained descriptive sensory analysis panel for sweetness and 13 texture attributes. Mechanical parameters were measured by texture profile analysis (TPA); and composition (starch, cell wall material, sugar contents), starch properties (thermal, granule type ratios, granule sizes), and amylase activities were characterized. TPA predicted fracturability and firmness well, whereas starch and sugar contents, B-type starch granule ratio, and amylase activities influenced prediction of mouthfeel textures. Sweetness perception was influenced by perceived particle size and sugar contents; and maltose generation during baking was highly correlated with raw sweetpotato starch content. These relationships between physicochemical sweetpotato properties and baked textures and sweetness could benefit breeders and processors in selecting biochemical traits that result in consumer preferred products.

Using machine learning for image-based analysis of sweetpotato root sensory attributes.

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 high-throughput 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.

Gender mainstreaming in sweetpotato breeding in Uganda: a case study.

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. Method: 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. Conclusion: Following an all-inclusive approach coupled with training 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.

Prioritising quality traits for gender-responsive breeding for boiled potato in Uganda.

Using quantitative, qualitative and sensorial data collected from western (Kabale) and central (Rakai) Uganda, this paper identifies and describes gender-responsive traits preferred in varieties for the boiled potato market. These traits are aggregated into a product profile to support breeding programme design and decision-making that will increase probability of variety acceptance. An interdisciplinary and participatory methodology was used to collect data on socio-economic on trait preferences, processing and organoleptics and finally, to develop a lexicon through a sensorial panel. Characteristics that were important to both men and women, such as red skin and yellow flesh, are linked to market preferences. Women-only preferred characteristics such as big size and mealiness are linked to processing efficiency and eating quality. Besides agronomic traits, breeders must consider factors such as gender roles, social norms, and market preferences traits that guide farmers and other food chain actors in their selection of new varieties.

Development of a food product profile for boiled and steamed sweetpotato in Uganda for effective breeding.

This study sought to understand user preferences of raw, boiled and steamed sweetpotato, a staple food in Uganda. A sequential methodology involving state of knowledge review, gendered food mapping, processing diagnosis and consumer testing was used in Lira and Kamwenge districts. Preferred raw sweetpotato characteristics were large roots (≥ 3 cm diameter) with a sweet taste, smooth skin and hard texture, while mealiness, sweet taste and good sweetpotato smell were important attributes for boiled sweetpotato. Processors, mostly women, highlighted ease of peeling and sappiness of raw roots. There were gender differences in quality characteristic preferences and perceived importance. The released variety, NASPOT 8, had the highest overall liking in Kamwenge and was well liked in Lira. Penalty analysis of consumer data showed that sweetness and firmness were key drivers of overall liking. The results will support breeding programmes in meeting specific end-user product profiles, selection criteria and uptake of new varieties.

Dietary intakes of adolescents from food insecure households: analysis of data from the 6th (2013-2015) Korea National Health and Nutrition Examination Survey.

BACKGROUND/OBJECTIVES: This study aimed at evaluating the dietary intakes of Korean adolescents affected by food insecurity, in comparison with those who were food secure. SUBJECTS/METHODS: The study used one day 24-hour dietary recall data from the 6th Korea National Health and Nutrition Examination Survey. The study subjects consisted of 1,453 adolescents of whom 695 were middle school-aged and 758 were high school-aged. Food security status was assessed using the 18-item questionnaire. Nutrient intake was evaluated in terms of nutrient density, insufficient intake, and excessive intake for selected nutrients, in addition to meeting the appropriate range for total energy intake and energy intakes from carbohydrate, sugar, protein, fat, and saturated fatty acids. Food intake was evaluated in terms of food group servings and dietary diversity score (DDS). RESULTS: The percentages of food insecurity were 11.1% for middle school-aged adolescents and 16.8% for high school-aged adolescents. Food insecure middle school-aged adolescents had higher intake of carbohydrate (P = 0.006) but lower intake of fat (P = 0.010) and saturated fatty acids (P = 0.005) than their food secure counterparts although the intake of both groups was in the recommended ranges. Nutrient intake among high school-aged adolescents was generally similar regardless of food security status. Both food secure and insecure adolescents showed insufficient intake of vitamin A, vitamin C, and calcium, and excessive sodium intake. They additionally had low prevalence of meeting appropriate intake ranges for energy, carbohydrate, and sugar. Food intake in terms of food group servings and DDS was also similar regardless of food security status among both age groups, with low intakes of foods from fruit and dairy groups. CONCLUSIONS: Except for a few nutrients among the middle school-aged adolescents, dietary intakes among Korean adolescents did not differ by food security status in this study.