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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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Series of farming practice methods have been employed to increase maize production but there is no adequate information on the effect of these methods on the nutritional and mineral content of organically grown maize. This study investigated the effects of inorganic and biochar fertilized soils on the proximate composition and mineral content of maize. Maize seeds were planted on organically fertilized soil (sawdust and gliricidia biochar), chemically fertilized soil Nitrogen Phosphorus and Potassium (NPK fertilizer), and soil without any amendment as control. The proximate compositions (protein, ash, crude fat, carbohydrate, and moisture) and mineral contents (Na, Mg, K, Ca, Fe, and Zn) of the maize flour samples were determined using standard methods. The results showed that protein content ranged from 4.58% to 7.24% (protein), ash 0.82% to 1.09%, crude fat 3.84% to 4.61%, moisture 9.76% to 10.60%, and carbohydrate 76.85% to 80.31%. There was no significant (p ≤ 0.05) difference among the proximate compositions except for protein and carbohydrate. Maize planted on NPK fertilized soil had the highest crude protein content of 7.24%. Other results obtained included sodium (55.65 mg/100 g), magnesium (35.87 mg/100 g), and iron (6.78 mg/100 g). Maize from soil without amendments was significantly higher than maize from NPK fertilized and biochar fertilized soils. Also, maize from control plot had the highest calcium content value of 48.95 mg/100 g. We concluded that maize planted with NPK fertilizer had higher nutrient than those planted with biochar application. Also, the mineral content of maize planted in control plot was higher than those on the amended soil. This study investigated the effects of inorganic and biochar fertilized soils on the proximate composition and mineral content of maize. Results showed that maize planted with NPK fertilizer had higher nutrient than those planted with biochar application. Biochar treatment did not affect the proximate composition and mineral content of maize flour. [ABSTRACT FROM AUTHOR]

ABSTRACT The effects of storage (4 months) on the chemical composition of yam tubers and its relation to textural quality of a major yam food product (pounded yam) were studied using six varieties of Dioscorea rotundata and D. alata. Chemical composition of both freshly harvested tubers and those stored for 4 months were determined by standard methods of analysis. Sugar, nonstarchy carbohydrate and dry matter contents of the tubers increased during storage while the starch, fat and protein contents decreased. Pounded yam made from stored yam tubers were of better textural quality than those from freshly harvested ones. Storage of yam tubers could be an effective way of improving the textural quality of pounded yam. This is important for processing yam tubers into value-added products. PRACTICAL APPLICATION The results of this research provide a scientific basis for differences in the food quality of food products made from freshly harvested and stored yam tubers. Storage is important to the industrial processing of value-added products (e.g., instant yam flour, yam flakes) from yam tubers. This study will help processors in selecting appropriate raw materials that will give optimal food quality that is expected and will be accepted by consumers. [ABSTRACT FROM AUTHOR]

Of all the species of Dioscorea, D. alata possesses higher multiplication ratio and better storability, and requires less capital and labour to produce than the most common specie, D. rotundata. Exploitation of the industrial potential of D. alata by diversifying its utilisation through the development of novel products will expand its utilisation. This study therefore investigated the potential of developing instant poundo yam flour from D. alata. Instant poundo yam flour was prepared from D. alata by peeling, dicing and immersing yam tubers in sodium metabisulphite solution (800 ppm for 20 min). The tubers were thereafter blanched at 70 °C for either 5 or 10 min, dried in a cabinet dryer at 60 °C for 72 hr, milled and sieved (600 µm) to obtain two experimental samples of poundo yam flours. The proximate composition of the flours was determined using standard methods. Sensory evaluation was conducted to determine the sensory attributes [colour, flavour, taste, textural quality (strecthability, adhesiveness, cohesiveness, smoothness) and general acceptability] of the flours. The two instant poundo yam samples were further compared with a commercial poundo yam in terms of the sensory attributes. There was no significant difference (p≤0.05) in the proximate composition of the two experimental instant poundo yam samples but their textural quality differed significantly (p≤0.05). Instant poundo yam blanched for 10 min recorded higher sensory scores than the one blanched for 5 min and compared fairly well with the reference sample. An acceptable instant poundo yam has been developed from D. alata. [ABSTRACT FROM AUTHOR]