Boiled yam end-user preferences and implications for trait evaluation

Modelling convectional oven drying characteristics and energy consumption of dehydrated yam (Dioscorea rotundata) chips

The influence of pre-treatments and different dehydrating temperatures on the drying dynamics, energy consumption, and quality attribute of yam chips was studied. Dehydration was executed employing a convectional oven dryer under four temperatures (50, 60, 70, and 80 °C) and 2.0 m/s air velocity. Yam chips were subjected to pre-treatment conditions of blanching (for 1, 2, 3, 4, and 5 min), citric acid (1 and 5 %), and ascorbic acid (1 and 5 %) solutions whereas, untreated yam chips samples served as the control. Dehydrated yam chips were further assessed for textural and colour properties. The drying rate was found to be faster at a higher temperature of 80 °C compared to lower temperatures of 50, 60, and 70 °C. The asymptotic model was established to be the suitable descriptive model for predicting moisture profile in the pre-treated yam chips based on highest R2 values (0.995-0.999), lowest χ2 values (4.422-18.498), and the root mean square error (RMSE) values (2.103-4.30). Pre-treatment and drying temperature had a significant (p < 0.05) impact on the hardness and colour of dehydrated yam chips. Blanching at 4 min yielded yam chips with most preferred texture (hardness: 81.3 N) and lightness (L*) in colour values (71.07 %) after drying compared to other pre-treated samples. The effective moisture diffusivity values of the pre-treated samples were in the range of 5.17294 × 10-9m2/s to 1.10143 × 10-8m2/s for 5 % citric acid samples at 50 °C and all pre-treated samples at 80 °C respectively. The general findings of the study indicated a least energy usage of 43.68 kWh as a cost-effective method of drying. Also, 4 min blanching, 5 % citric acid, and 1 % ascorbic acid at 80 °C were found to be the optimum conditions for pre-treating yam chips based on lower energy level consumption rates and improved sensory properties thus attributing to the quality of the dried yam chips.

Instrumental procedures to assess the extensibility of pounded yam and relationship with sensory stretchability and consumer preferences

BACKGROUND

Stretchability is the most important sensory textural attribute considered by consumers of pounded yam. It is important both for the processor during pounding and for the consumer during consumption to measure this attribute while screening large populations of yam genotypes intended for advanced breeding and eventual adoption. Texture determined by sensory evaluation and consumer perception is time consuming and expensive. It can be instrumentally mimicked by texture analyzer, thereby providing an efficient alternative screening tool.

RESULTS

Two instrumental methods (uniaxial extensibility and lubricated squeezing flow) were applied to assess the extensional properties of pounded yam. In order to evaluate the accuracy, repeatability and discrimination of the methods, six yam genotypes with contrasting extensional properties, previously evaluated by 13 panellists in terms of stretchability and moldability and by 99 participants randomly selected in terms of overall liking, were used. Both methods allowed the discrimination of different genotypes as a function of extensional properties. Principal components showed that the genotypes were grouped within separate components associated with specific sensory attributes and their related instrumental texture parameters. Moreover, significant correlations were found between uniaxial extensibility textural attributes, bi-extensional viscosity and consumer overall liking. However, the sensory attributes were not significantly correlated with instrumental data and consumer overall liking.

CONCLUSION

Bi-extensional viscosity and uniaxial extensibility attributes can be used to discriminate and screen yam genotypes for their stretchability characteristics. © 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.

Starch granule size and shape characterization of yam (Dioscorea alata L.) flour using automated image analysis

BACKGROUND

Roots, tubers and bananas (RTB) play an essential role as staple foods, particularly in Africa. Consumer acceptance for RTB products relies strongly on the functional properties of, which may be affected by the size and shape of its granules. Classically, these are characterized either using manual measurements on microscopic photographs of starch colored with iodine, or using a laser light-scattering granulometer (LLSG). While the former is tedious and only allows the analysis of a small number of granules, the latter only provides limited information on the shape of the starch granule.

RESULTS

In this study, an open-source solution was developed allowing the automated measurement of the characteristic parameters of the size and shape of yam starch granules by applying thresholding and object identification on microscopic photographs. A random forest (RF) model was used to predict the starch granule shape class. This analysis pipeline was successfully applied to a yam diversity panel of 47 genotypes, leading to the characterization of more than 205 000 starch granules. Comparison between the classical and automated method shows a very strong correlation (R2 = 0.99) and an absence of bias for granule size. The RF model predicted shape class with an accuracy of 83%. With heritability equal to 0.85, the median projected area of the granules varied from 381 to 1115 μm2 and their observed shapes were ellipsoidal, polyhedral, round and triangular.

CONCLUSION

The results obtained in this study show that the proposed open-source pipeline offers an accurate, robust and discriminating solution for medium-throughput phenotyping of yam starch granule size distribution and shape classification. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Varietal and environmental influences on organoleptic and cooking quality of water yam (Dioscorea alata) landraces

BACKGROUND

Yam is a major staple food that provides both energy (starch) and bioactive compounds. However, there is a lack of knowledge on its cooking quality. We have determined the cooking quality of five varieties of water yam (among those most appreciated by consumers), when they were steamed or boiled. The yams were grown in two contrasting locations with regard to pedoclimatic conditions.

RESULTS

Ratio of length to mean circumference of the tuber, difficulty to peel, cooking time, color attributes, hardness of steamed pulp, and dry matter (DM) and starch contents significantly varied among varieties. Cooking time and hardness of the cooked pulp, either steamed or boiled, were higher for tubers grown at the drier location, with vertisols, than at the rainy one, with a ferralitic soil. The raw pulp was richer in starch at the rainy location. We found no correlation between either textural properties or DM and the cooking time. A slight (r = 0.44) but significant correlation was recorded between the DM of the raw pulp and the hardness of the steamed product.

CONCLUSION

We propose a comprehensive multicriteria approach for determination of yam cooking quality, textural properties, color attributes and chemical composition, along with varietal and environmental influences. This approach takes into consideration the complexity of food quality, allows a better understanding of its determinants and provides a basis for useful guidelines for breeders. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Convolutional neural network allows amylose content prediction in yam (Dioscorea alata L.) flour using near infrared spectroscopy

BACKGROUND

Yam (Dioscorea alata L.) is the staple food of many populations in the intertropical zone, where it is grown. The lack of phenotyping methods for tuber quality has hindered the adoption of new genotypes from breeding programs. Recently, near-infrared spectroscopy (NIRS) has been used as a reliable tool to characterize the chemical composition of the yam tuber. However, it failed to predict the amylose content, although this trait is strongly involved in the quality of the product.

RESULTS

This study used NIRS to predict the amylose content from 186 yam flour samples. Two calibration methods were developed and validated on an independent dataset: partial least squares (PLS) and convolutional neural networks (CNN). To evaluate final model performances, the coefficient of determination (R2), the root mean square error (RMSE), and the ratio of performance to deviation (RPD) were calculated using predictions on an independent validation dataset. The tested models showed contrasting performances (i.e., R2 of 0.72 and 0.89, RMSE of 1.33 and 0.81, RPD of 2.13 and 3.49 respectively, for the PLS and the CNN model).

CONCLUSION

According to the quality standard for NIRS model prediction used in food science, the PLS method proved unsuccessful (RPD < 3 and R2 < 0.8) for predicting amylose content from yam flour but the CNN model proved to be reliable and efficient method. With the application of deep learning methods, this study established the proof of concept that amylose content, a key driver of yam textural quality and acceptance, can be predicted accurately using NIRS as a high throughput phenotyping method. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Genome-wide dissection of the genetic factors underlying food quality in boiled and pounded white Guinea yam

BACKGROUND

Food quality traits related to the genetics of yam influence the acceptability for its consumption. This study aimed at identifying genetic factors underlying sensory and textural quality attributes of boiled and pounded yam, the two dominant food products from white Guinea yam.

RESULTS

A genome-wide association study (GWAS) of a panel of 184 genotypes derived from five multi-parent crosses population was conducted. The panel was phenotyped for the qualities of boiled and pounded yam using sensory quality and instrument-based textural profile assays. The genotypes displayed significant variation for most of the attributes. Population differentiation and structure analysis using principal component analysis (PCA) and population structure-based Bayesian information criteria revealed the presence of four well-defined clusters. The GWAS results from a multi-random mixed linear model with kinship and PCA used as covariate identified 13 single-nucleotide polymorphic (SNP) markers significantly associated with the boiled and pounded yam food qualities. The associated SNP markers explained 7.51-13.04% of the total phenotypic variance with a limit of detection exceeding 4.

CONCLUSION

Regions on chromosomes 7 and 15 were found to be associated with boiled and pounded yam quality attributes from sensory and instrument-based assays. Gene annotation analysis for the regions of associated SNPs revealed co-localization of several known putative genes involved in glucose export, hydrolysis and glycerol metabolism. Our study is one of the first reports of genetic factors underlying the boiled and pounded yam food quality to pave the way for marker-assisted selection in white Guinea yam. © 2023 Society of Chemical Industry.

User preferences and consumer acceptability of boiled plantain in rural and urban localities in Cameroon

BACKGROUND

An understanding of the preferences of different stakeholders in the plantain value chain in rural and urban segments in Cameroon is important for the selection and adoption of new plantain cultivars. Boiled plantain is one of the most commonly consumed food products from this crop in Cameroon. Gendered food mapping and consumer testing with two plantain landraces (Batard and Big Ebanga) and a plantain-like hybrid (CARBAP K74) was carried out in rural and urban areas in the West and Littoral regions of Cameroon.

RESULTS

Plantain users in these two regions were categorized into producers, traders, processors, and consumers. Preferences indicated that raw plantain should bear long and large fruits, with heavy bunches, and an orange pulp color, whereas boiled plantain should present with a yellow color and a soft and mealy pulp, with a good plantain aroma. Batard and Big Ebanga were liked moderately by consumers, whereas CARBAP K74 was liked slightly. CARBAP K74 was on par with Batard and Big Ebanga for some attributes, except for color and sweetness.

CONCLUSION

More emphasis should be given to attributes such as color, firmness, and taste for the development of new plantain clones to be adopted by end users consuming boiled green plantain. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Characterizing quality traits of boiled yam: texture and taste for enhanced breeding efficiency and impact

BACKGROUND

Boiled yam key quality attributes typical for West African consumers are that it is crumbly, easy to break and has a sweet taste. New yam varieties are being developed but high- or medium-throughput tools to assess the required quality traits and their range of acceptance are limited. This study assessed the acceptance thresholds of these quality attributes and established predictive models for screening yam varieties that meet the required consumer preferences.

RESULTS

Overall liking was associated with sweet taste, crumbliness and easiness to break (r-values 0.502, 0.291 and -0.087, respectively). These parameters and selected biophysical parameters highly discriminated the boiled yam varieties. Crumbly texture and easiness to break were well predicted by penetration force and dry matter, whereas sweet taste were well predicted by dry matter and sugar intensity. A high crumbliness and sweet taste are preferred (sensory scores above 6.19 and 6.22 for crumbly and sweet taste, respectively, on a 10 cm unstructured line scale), while a too high easiness to break is disliked (sensory scores ranging from 4.72 to 7.62). Desirable biophysical targets were between 5.1 and 7.1 N for penetration force, dry matter around 39% and sugar intensity below 3.62 g 100 g-1. Some improved varieties fulfilled the acceptable thresholds, and screening was improved through deviation from the optimum.

CONCLUSION

Acceptance thresholds and deviation from optimum for boiled yam assessed through the instrumental measurements are promising tools for yam breeders. © 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.

Whole-genome sequencing and comparative genomics reveal candidate genes associated with quality traits in Dioscorea alata

BACKGROUND

Quality traits are essential determinants of consumer preferences. Dioscorea alata (Greater Yam), is a starchy tuber crop in tropical regions. However, a comprehensive understanding of the genetic basis underlying yam tuber quality remains elusive. To address this knowledge gap, we employed population genomics and candidate gene association approaches to unravel the genetic factors influencing the quality attributes of boiled yam.

METHODS AND RESULTS

Comparative genomics analysis of 45 plant species revealed numerous novel genes absent in the existing D. alata gene annotation. This approach, adding 48% more genes, significantly enhanced the functional annotation of three crucial metabolic pathways associated with boiled yam quality traits: pentose and glucuronate interconversions, starch and sucrose metabolism, and flavonoid biosynthesis. In addition, the whole-genome sequencing of 127 genotypes identified 27 genes under selection and 22 genes linked to texture, starch content, and color through a candidate gene association analysis. Notably, five genes involved in starch content and cell wall composition, including 1,3-beta Glucan synthase, β-amylase, and Pectin methyl esterase, were common to both approaches and their expression levels were assessed by transcriptomic data.

CONCLUSIONS

The analysis of the whole-genome of 127 genotypes of D. alata and the study of three specific pathways allowed the identification of important genes for tuber quality. Our findings provide insights into the genetic basis of yam quality traits and will help the enhancement of yam tuber quality through breeding programs.