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Abstract Cassava (Manihot esculenta Crantz) is an essential stable food crop in Sub-Saharan Africa commonly consumed amongst the low-income communities in Africa. Though cassava roots and leaf have vast economic and commercial benefits, it produces cyanogenic glycosides, which are toxic and most often responsible for the bitter taste of some cassava cultivars. The study evaluates the cassava roots and leaves’ cyanogenic potential and dry matter content of the Genetic Gain Assessment trial grown in a different environment. It establishes the association between the cyanogenic potential (CNP) and the roots and leaves dry matter (DM). Genetic Gain Assessment (GGA) cassava genotypes (N = 400) selected for the Uniform Yield Trial (UYT) breeding stage were planted under IVS (Dry season in Inland Valley Hydromorphic area) and Upland (rain-fed conditions) in two locations of IITA Research Farms, namely; Ibadan (IVS and Upland) and Mokwa (Upland) in Nigeria. The CNP content of cassava leaves in IVS, Mokwa, and Upland ranged from 3.39 to 272.16 mg/100 g, 4.28 to 228.72 mg/100 g, and 13.13 to 127.39 mg/100 g, respectively. However, the respective CNP range in root samples across IVS, Mokwa, and Upland was 0.76–76.31 mg/100 g, 0.94–136.53 mg/100 g, and 2.37–47.11 mg/100 g. Also, the mean ± SD of DM content of leaves were 27.97 ± 3.01%, 28.81 ± 4.01%, and 13.65 ± 3.69%, respectively, in IVS, Mokwa, and Upland, while the root samples had mean ± SD of DM content of 38.09 ± 4.80%, 32.69 ± ,5.93% and 24.63 ± 5.07% respectively. Furthermore, location and genotype had a highly significant effect (p

Water yam (Dioscorea alata), also known as winged yam, is one of the most economically significant yam species, serving as a staple food crop in tropical and subtropical regions. Its widespread cultivation is due to its favorable agronomic characteristics, including high yield, improved tuber storability, and significant nutritional and health benefits. Despite these advantages, water yam often remains underutilized due to consumer biases towards its traditional food product quality, particularly for pounded yam preparations. In this study, we evaluated fifty-eight improved genotypes of water yams grown across three locations to assess their potential to produce superior food qualities comparable to the widely consumed white yams (D. rotundata). Seven white yams, including popular landraces, were used to set thresholds for desirable food quality. Through standardized analysis, yam samples were assessed for their biochemical composition and culinary and sensory texture attributes. The results revealed varying ranges of dry matter (DM), starch, sugar, protein, crude fiber (CF), fat, and amylose, spanning from 20.35 to 35.95 g/100 g, 42.81 to 83.31 g/100 g, 4.76 to 6.95 g/100 g, 4.33 to 6.62 g/100 g, 1.55 to 3.89 g/100 g, 0.32 to 0.53 g/100 g, and 29.27 to 38.52 g/100 g, respectively. The mean values (±SD) were found to be 29.85 ± 4.0 g/100 g (DM), 67.90 ± 44g/100 g (starch), 5.82 ± 0.64 g/100 g (sugar), 6.31 ± 1.31 g/100 g (protein), 2.14 ± 0.57 g/100 g (crude fiber), 0.44 ± 0.08 (fat), and 33 ± 16.43 g/100 g (amylose). Significant effects (p < 0.001) of the planting environments and genotypes on the biochemical composition of the yam samples were observed, except for the sugar content. Furthermore, specific water yam genotypes, such as TDa 0900354, TDa 9801174, TDa 1401619, TDa 1400301, TDa 140091, TDa 0100029, TDa 1100793, TDa 1401249, TDa 1100242, and TDa 1401276, exhibited biochemical properties and culinary and sensory textural attributes akin to the improved white yam genotypes and their landrace counterparts. These findings underscore the potential for promoting selected water yam genotypes to diversify food options and reduce reliance on a limited array of crops, particularly in traditional food-insecure regions of tropical Africa.

The use of the biophysical and textural qualities of fufu to choose the possible substitution of an adopted cassava variety (TMEB419-V1) with improved genotypes from the breeding program was assessed in this study. Standard methods were used for the biophysical and textural attributes of the fufu produced from different cassava roots. The outcomes portray that the means of the biophysical attributes of the fufu flour from different cassava genotypes are swelling power (SWP) of 13.59%, solubility index (SI) of 3.41%, dispersibility of 26.77%, bulk density (BD) of 54.46%, water absorption capacity (WAC) of 149.44%, peak viscosity of 693.97 RVU, trough viscosity of 319.76 RVU, breakdown viscosity of 374.21 RVU, final viscosity of 433.84 RVU, setback viscosity of 114.08 RVU, peak time of 4.49 min, and pasting temperature of 78.52°C, as well as moisture content of 4.92%, ash content of 0.52%, sugar content of 2.85%, starch content of 76.24%, amylose content of 31.68%, and cyanogenic potential content (CNP) of 3.03 mg HCN/kg. The sensory texture attributes depict that the cooked fufu dough was stretchable, slightly hard, sticky, and mouldable. The instrumental texture attribute of the cooked fufu dough is hardness 27.18 N/m2, adhesiveness −62.04 N/m2, moldability 0.93, stretchability 0.89, and gumminess 25.26 N/m2. Similar functional (BD) and pasting (peak and breakdown viscosities) properties and chemical composition (amylose content) to that of the control sample (V1 variety) were produced from the V6 genotype. However, the cooked fufu dough prepared from the V7 and V8 genotypes was comparable to that of the V1 variety in terms of the sensory (stretchability) and instrumental (moldability) texture attributes; therefore, most of the genotypes may be suitable for producing fufu flour like the control sample (V1 variety) based on attributes preferred by the consumers.

There is little or no information on the relationship between the quality of fufu flour and the textural attributes of cooked dough. Quality attributes of flour were therefore correlated with the sensory texture profile analysis (STPA) and instrumental texture profile analysis (ITPA) of the dough produced from six varieties of cassava. Results showed that the water absorption capacity (WAC) of flour had a positive correlation (p

This study investigated the effects of genotype, location, and planting season on the proximate composition and metabolizable energy of advanced maize hybrids. Twenty-five hybrid maize and a local variety as control were harvested from five locations 100 days after planting for two seasons. The maize samples were sorted, cleaned, and pulverized using a laboratory mill and were analyzed for nutritional composition and metabolizable energy (ME) using standard laboratory methods. Moisture content, ash, fat, and protein had mean ± SD of 8.97 ± 0.40%, 1.48 ± 0.05%, 4.31 ± 0.19, and 8.88 ± 0.18%, respectively. ME had a mean ± SD of 379.77 ± 2.17 kJ, and total carbohydrates had values ranging from 74.68 and 77.20%, with an average of 76.68%. Results showed that most of the variations expressed in the proximate compositions of the maize hybrids were not significantly (p > 0.05) dependent on the genotypes. In contrast, locations significantly affected the maize hybrids’ proximate composition and metabolizable energy (p < 0.001). In addition, there was no significant effect (p > 0.05) of location by genotype interaction on the proximate composition and ME of the maize samples. The planting season also exhibited a significant (p < 0.001) difference for all the proximate parameters. Fourteen out of the twenty-five maize hybrids were similar to the local variety in terms of proximate composition and metabolizable energy. Therefore, they could be recommended for advancement in the breeding stages for release for household and industrial uses.

Gari is a creamy, granular flour obtained from roasting fermented cassava mash. Its preparation involves several unit operations, including fermentation, which is essential in gari production. Fermentation brings about specific biochemical changes in cassava starch due to the actions of lactic acid bacteria. Consequently, it gives rise to organic acids and a significant reduction in the pH. Consumer preferences for gari are influenced by these changes and impact specific functional characteristics, which are often linked to cassava genotypes. Measurement of these functional characteristics is time-consuming and expensive. Therefore, this study aimed to develop high-throughput and less expensive prediction models for water absorption capacity, swelling power, bulk density, and dispersibility using Near-Infrared Reflectance Spectroscopy (NIRS). Gari was produced from 63 cassava genotypes using the standard method developed in the RTB foods project. The prediction model was developed by dividing the gari samples into two sets of 48 samples for calibration and 15 samples as the validation set. The gari samples were transferred into a ring cell cup and scanned on the NIRS machine within the Vis-NIR range of 400–2,498 nm wavelength, though only the NIR range of 800–2,400 nm was used to build the model. Calibration models were developed using partial least regression algorithms after spectra pre-processing. Also, the gari samples were analysed in the laboratory for their functional properties to generate reference data. Results showed an excellent coefficient of determination in calibrations (R2Cal) of 0.99, 0.97, 0.97, and 0.89 for bulk density, swelling power, dispersibility, and water absorption capacity, respectively. Also, the performances of the prediction models were tested using an independent set of 15 gari samples. A good prediction coefficient (R2 pred) and low standard error of prediction (SEP) was obtained as follows: Bulk density (0.98), Swelling power (0.93), WAC (0.68), Dispersibility (0.65), and solubility index (0.62), respectively. Therefore, NIRS prediction models in this study could provide a rapid screening tool for cassava breeding programs and food scientists to determine the food quality of cassava granular products (Gari).

Specific biochemical properties and textural attributes determine the final quality and acceptability of yam food products. This study assessed the flour and cooking qualities (boiled yam) of sixteen elite white yam genotypes (D. rotundata) grown in three locations. Fresh yam samples were cut into regular-shaped pieces and boiled using the standard procedure. Sub-samples were oven-dried at 65 °C for 72 h and milled to flour. The biochemical profiling for the yam flour showed, on average, 61.35 ± 5.15% starch, 5.35 ± 0.15% sugar, 1.55 ± 0.24% crude fiber, 1.91 ± 0.31% ash, 5.65 ± 0.66% protein, 0.33 ± 0.02% fat and 34.87 ± 1.94% amylose content. The boiled yam's water absorption and cooking time ranged from 0.35 to 5.17% and 7.00–18 min, with an average of 2.74% and 10.64 min, respectively. The hardness of boiled yam from the sensory assay correlated positively with the hardness of instrumental texture analysis (p < 0.001, r = 0.47). In contrast, the hardness of instrumental texture had a significant negative correlation with the chewiness of sensory profile analysis (p < 0.05, r = 0.37). Likewise, water absorption correlated positively and significantly (p < 0.05, r = 0.43) with the chewiness of the sensory analysis. The study shows that the sensory attributes that determine the acceptability of boiled yam could be determined using instrumental measurements to save time and cost.

The cassava starch market is promising in sub-Saharan Africa and increasing rapidly due to the numerous uses of starch in food industries. More accurate, high-throughput, and cost-effective phenotyping approaches could hasten the development of cassava varieties with high starch content to meet the growing market demand. This study investigated the effectiveness of a pocket-sized SCiO™ molecular sensor (SCiO) (740−1070 nm) to predict starch content in freshly ground cassava roots. A set of 344 unique genotypes from 11 field trials were evaluated. The predictive ability of individual trials was compared using partial least squares regression (PLSR). The 11 trials were aggregated to capture more variability, and the performance of the combined data was evaluated using two additional algorithms, random forest (RF) and support vector machine (SVM). The effect of pretreatment on model performance was examined. The predictive ability of SCiO was compared to that of two commercially available near-infrared (NIR) spectrometers, the portable ASD QualitySpec® Trek (QST) (350−2500 nm) and the benchtop FOSS XDS Rapid Content™ Analyzer (BT) (400−2490 nm). The heritability of NIR spectra was investigated, and important spectral wavelengths were identified. Model performance varied across trials and was related to the amount of genetic diversity captured in the trial. Regardless of the chemometric approach, a satisfactory and consistent estimate of starch content was obtained across pretreatments with the SCiO (correlation between the predicted and the observed test set, (R2P): 0.84−0.90; ratio of performance deviation (RPD): 2.49−3.11, ratio of performance to interquartile distance (RPIQ): 3.24−4.08, concordance correlation coefficient (CCC): 0.91−0.94). While PLSR and SVM showed comparable prediction abilities, the RF model yielded the lowest performance. The heritability of the 331 NIRS spectra varied across trials and spectral regions but was highest (H2 > 0.5) between 871−1070 nm in most trials. Important wavelengths corresponding to absorption bands associated with starch and water were identified from 815 to 980 nm. Despite its limited spectral range, SCiO provided satisfactory prediction, as did BT, whereas QST showed less optimal calibration models. The SCiO spectrometer may be a cost-effective solution for phenotyping the starch content of fresh roots in resource-limited cassava breeding programs.

Yellow-fleshed cassava root (YFCR) is processed into traditional products that may influence its bioactivities. In this study, the antioxidant and anti-hyperglycaemic activities of three traditional products (lafun, fufu and gari) from five genotypes (IITA-TMS-IBA070337, 182961, 182962, 182986, 183044) of YFCR were evaluated. The YFCR genotypes were grown at the International Institute of Tropical Agriculture (IITA) research field, Ibadan. The bioactive constituents (total carotenoids, total phenolics, tannins and total flavonoids), antioxidant [2,2-azinobis (3-ethyl-benzothiazoline-6-sulfonic acid) radical cation (ABTS•+) and 1,1-diphenyl-2- picrylhydrazyl radical (DPPH•) scavenging capacities, and reducing power], and starch-digesting enzymes (α-amylase and α-glucosidase) inhibitory activities of the products were determined using standard laboratory methods. The glucose response of the products was assessed in human subjects. The concentrations of the bioactive constituents of the products from different genotypes varied significantly (p < 0.05). The ABTS•+ and DPPH• scavenging capacities and the reducing power of the products also differed significantly (p < 0.05), such that the lafun from IITA-TMS-IBA182962, IITA-TMS-IBA070337 and IITA-TMS-IBA070337 had the strongest ABTS•+ and DPPH• scavenging capacities, and reducing power, respectively. The α-amylase and α-glucosidase inhibitory activities of the three products differed significantly (p < 0.05), with the lafun from IITA-TMS-IBA070337 and IITA-TMS-IBA07033 having the strongest α-amylase and α-glucosidase inhibitory activity, respectively. Also, the lafun from IITA-TMS-182986 had the least glucose response, while the fufu from IITA-TMS-IBA070337 had the highest glucose response. Overall, the lafun from different genotypes of YFCR had the most potent antioxidant and starch-digesting enzymes inhibitory activities and the least glucose responses. Hence, lafun may be a promising dietary intervention targeting oxidative stress, hyperglycaemia, and their resultant type 2 diabetes.

The use of the biophysical and textural attributes of gari/eba to determine the possible substitution of an adopted cassava variety (TMBE419) with the improved genotypes from the breeding program was evaluated in this study. Standard methods were used for the characterization of the biophysical and textural attributes of the gari/eba from different cassava roots. It was observed that the mean of the biophysical attributes of the gari is swelling power (SWP) 12.46%, dispersibility 59.70%, water absorption capacity (WAC) 474.60%, peak 355.82 RVU, breakdown 111.02 RVU, and final 423.07 RVU viscosities, peak time 4.91 min, pasting temperature 80.14°C, moisture content 3.92%, ash content 0.98%, starch content 71.98%, amylose content 31.47% and cyanogenic potential (CNP) content 0.47 mg HCN/kg. There were significant differences (p < 0.05) in all the biophysical attributes of the gari samples. The instrumental texture attribute of the eba is hardness 40.46 N/m2, mouldability 0.93, and stretchability 1.04. The sensory texture attributes depict that all the eba was moderately soft, sticky, and mouldable. Significant differences (p < 0.05) exist in the instrumental and sensory texture attributes of the eba samples. The PCA shows that gari made from TMS14F1285P0006 and TMS13F1053P0010 genotypes may have similar behavior in terms of dispersibility, SWP, and peak and breakdown viscosities to that of the TMBE419 variety. Also, the stickiness of the eba prepared from the TMS14F1285P0006 and TMS13F1053P0010 genotypes may be the same as that of the TMBE419 variety. Therefore, TMS14F1285P0006 and TMS13F1053P0010 genotypes may be good replacements for producing gari/eba in place of the TMBE419 variety.

Hyperspectral imaging (HSI) is one of the most often used techniques for rapid quality evaluation for various applications. It is a non-destructive technique that effectively evaluates the quality attributes of root and tuber crops, including yam and cassava, and their food products. Hyperspectral imaging technology, which combines spectroscopy and imaging principles, has an advantage over conventional spectroscopy due to its ability to simultaneously evaluate the physical characteristics and chemical components of various food products and specify their spatial distributions. HSI has demonstrated significant potential for obtaining quick information regarding the chemical composition of the root and tuber, such as starch, protein, dry matter, amylose, and soluble sugars, as well as physical characteristics such as textural properties and water binding capacity. This review highlights the principles of near-infrared hyperspectral imaging (NIR-HSI) techniques combined with relevant image processing tools. It then provides cases of its application in determining crucial biochemical quality traits and textural attributes of roots and tuber crops, focusing on cassava and yam. The need for more information on using NIR-HSI in the quality evaluation of yam and cassava was underscored. It also presents the challenges and prospects of this technology.

Gliricidia sepium (Jacq.) Walp is a well-known agroforestry leguminous tree that provides multiple benefits in different agroecological zones. Its apparent versatility is seen in improving animal feed, cleaning environmental wastes, and healing inflammations. It was also found to have significant benefits in agroforestry due to its ability to enhance soil fertility through nitrogen fixation and green manure. However, this article reviews the use of Gliricidia sepium to improve soil fertility and crop agronomic and nutritional properties. Google Scholar, PubMed, and Science Direct were the databases consulted for the relevant articles used in this review. Trees and leaves of G. sepium, either used as mulch, biochar, or intercropped, have enhanced soil fertility indicators, such as total soil carbon, nitrogen, phosphorus, available phosphorus, pH, cation exchange capacity, and soil organic matter in different farming systems. Its immense positive performance in improving the yield of crops led to an economic advantage for low-income farmers. G. sepium can also lower the use of mineral fertilizer as its adoption grows, leading to a greener environment in the agricultural sector. The review concluded that there is a plethora of research on the effect of Gliricidia on maize yield enhancement; hence further investigations should be conducted on using Gliricidia sepium as a green fertilizer to improve yields and the nutritional properties of other crops.

African yam bean has immense food and nutrition potential and is resilient to adverse environmental conditions. Despite its potential, the crop is underutilized, which could be attributed to seed hardness (requiring about 6–24 hours of cooking time); and the abundance of antinutrient factors (tannin, phytate, and oxalate). This study evaluated the physical (seed hardness, cooking time) and chemical compositions (crude protein, tannin, phytate, and oxalate) of 93 AYB accessions grown in Ethiopia. The seed hardness of each accession was determined by the compression force and compression time using Texture Analyzer, whereas cooking time was ascertained using Mattson Bean Cooker. The accession’s crude protein level, tannin, oxalate, and phytate were investigated from flour samples using standard laboratory procedures. Highly significant (P

The study evaluates the effects of genotype, maturity, and growing location on the functional and pasting properties of freshly harvested orange maize hybrids and open-pollinated varieties (OPVs). Eight fresh orange maize hybrid and eight fresh maize OPV, including the control, were harvested at three stages: 20, 27, and 34 days after planting (DAP). The freshly harvested maize samples were lyophilized and characterized for the pasting and functional properties using standard laboratory methods. The peak viscosity, final viscosity, and swelling power of the OPVs increased between 20 and 27 DAP. Additionally, the water absorption capacity increased between 20 and 27 DAP for the maize hybrids, with a decreasing trend between 27 and 34 DAP. However, genotypes 2, from the orange maize hybrid, and 5, amongst the OPV, were outstanding with the highest peak viscosities, indicating good final product quality. The combined ANOVA for the fresh orange maize hybrid and OPV showed a highly significant effect (p ≤ 0.01 and p ≤ 0.001) for the maturity and location on the pasting and functional properties except for the pasting temperature, final viscosity, and pasting time which showed no significant effect. In contrast, the location by genotypes by maturity interactions had no significant effects on the pasting and functional properties of the fresh maize hybrid and the orange OPV except only for the setback, which was highly significant at p ≤ 0.001. Nutritionists, food scientists, and maize breeders could use the information from this study to select the best maize genotypes at the appropriate harvesting period suitable for the production of the preferred maize-based products of consumers.

The accurate quantification of amino acids in maize breeding programs is challenging due to the high cost of analysis using High-Performance Liquid Chromatography (HPLC) and other conventional methods. Using the Near-Infrared Spectroscopic (NIRS) method in breeding to screen many genotypes has proven to be a fast, cost-effective, and non-destructive method. Thus, this study aimed to develop and apply the NIRS prediction models for quantifying amino acids in biofortified quality protein maize (QPM). Sixty-three (63) QPM maize genotypes were used as the calibration set, and another twenty (20) genotypes were used as the validation set. The microwave hydrolysis system coupled with post-column derivatization with 6-amino-quinoline-succinimidyl-carbamate as the derivatization reagent and the HPLC method were used to generate the reference data set used for the calibration development. The calibration models were developed for essential and non-essential amino acids using WINSI Foss software. Good coefficients of determination in calibration (R2cal) of 0.91, 0.93, 0.93, and 0.91 and low standard errors in calibrations (SEC) of 0.62, 0.71, 0.26, and 1.75 were obtained for glutamic acids, alanine, proline, and leucine, respectively, while aspartic acids, serine, glycine, arginine, tyrosine, valines, and phenylalanine had fairly good R2Cal values of 0.86, 0.71, 0.81, 0.78, 0.68, 0.79, and 0.75. In contrast, poor (R2cal) was obtained for histidine (0.07), cystine (0.09), methionine (0.09), lysine (0.20), threonine (0.51), and isoleucine (0.09), respectively. The models’ prediction performances (R2pred) and standard error of prediction (SEP) were reasonably good for certain amino acids such as aspartic acid (0.90), glycine (0.80), arginine (0.94), alanine (0.90), proline (0.80), tyrosine (0.83), valine (0.82), leucine (0.90), and phenylalanine (0.88) with SEP values of 0.24, 0.39,0.24, 0.93, 0.47,0.34, 0.78, 2.20, and 0.77, respectively. However, certain amino acids had their R2pred below 0.50, which could be improved to become useful for screening purposes for those amino acids. Further work is recommended by including a training set representing the sample population’s variance to improve the model’s performance.

Bananas are important staples in tropical and sub-tropical regions and their potential as a source of provitamin A has recently attracted attention for biofortification. A collection of 189 banana genotypes (AAB-plantains, M. acuminata cultivars and bred hybrids) was screened to determine variability in fruit pulp provitamin A carotenoid (pVAC) content using high performance liquid chromatography. Total carotenoid content in tested genotypes varied from 1.45 µg/g for hybrid 25447-S7 R2P8 to 36.21 µg/g for M. acuminata cultivar ITC.0601 Hung Tu with a mean of 8.00 µg/g fresh weight. Predominant carotenoids identified were α-carotene (38.67%), trans-β-carotene (22.08%), lutein (22.08%), 13-cis-β-carotene (14.45%) and 9-cis-β-carotene (2.92%), indicating that about 78% of the carotenoids in bananas are pVAC. High pVAC genotypes were identified for integration into biofortification strategies to combat vitamin A deficiency in developing countries. Keywords: Banana, Carotenoid, Plantain hybrids, Provitamin A

High throughput techniques for phenotyping quality traits in root and tuber crops are useful in breeding programs where thousands of genotypes are screened at the early stages. This study assessed the effects of sample preparation on the prediction accuracies of dry matter, protein, and starch content in fresh yam using Near-Infrared Reflectance Spectroscopy (NIRS). Fresh tubers of Dioscorearotundata (D. rotundata) and Dioscoreaalata (D. alata) were prepared using different sampling techniques—blending, chopping, and grating. Spectra of each sample and reference data were used to develop calibration models using Modified Partial Least Square (MPLS). The performance of the model developed from the blended yam samples was tested using a new set of yam samples (N = 50) by comparing their wet laboratory results with the predicted values from NIRS. Blended samples had the highest coefficient of prediction (R2pre) for dry matter (0.95) and starch (0.83), though very low for protein (0.26), while grated samples had the lowest R2pre of 0.87 for dry matter and 0.50 for starch. Results showed that blended samples gave a better prediction compared with other methods. The feasibility of NIRS for the prediction of dry matter and starch content in fresh yam was highlighted.