Comparative Proximate Composition of Maize (Zea mays L.) Varieties Grown in South-western Nigeria

Adeniyi, O. O.; Ariwoola, O. S.

doi:10.21467/ias.7.1.1-5

Cited by 13 publications

(20 citation statements)

References 9 publications

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“…The highest amount of carbohydrates was found in the Istmeño and Paloma varieties (69.59 and 68.78 respectively); on average, sorghum grain has about 72.1% carbohydrates (Xiong et al, 2019). The differences between varieties may be due to genetic factors, factors related to the environment or to agronomic conditions during growth (Adeniyi & Ariwoola 2019).…”

Section: Proximal Analysis Of the Six Sorghum Varietiesmentioning

confidence: 96%

Proximal analysis and profile of fatty acids on six varieties of white grain sorghum with potential use in human consumption

Treviño-Salinas

Perales-Torres

Castillo-Ruíz

et al. 2021

CyTA - Journal of Food

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In Mexico, corn is the most widely used cereal, however, in arid areas it is not possible to cultivate it, so white sorghum represents an alternative. However, it is important to know the varieties nutritional content. Therefore, this study the proximal profile and fatty acids of six white sorghum varieties grown in Mexico were evaluated. Proximate analysis was carried out based on AACC methods and gas chromatography had been used for fatty acid analysis. Mazatlan and Sureño varieties showed the highest content of proteins (12%), fiber (7%), and ash (1.65%); regarding fat content, the highest values were found in Mazatlan and Costeño (4%). For fatty acid profile, saturated and unsaturated fatty acids were detected, including Omega 6 and 9. Sorghum represents an alternative, specially for arid and semiarid regions. The results indicate that these varieties are a viable source to produce foods for human consumption.

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Section: Proximal Analysis Of the Six Sorghum Varietiesmentioning

confidence: 96%

Proximal analysis and profile of fatty acids on six varieties of white grain sorghum with potential use in human consumption

Treviño-Salinas

Perales-Torres

Castillo-Ruíz

et al. 2021

CyTA - Journal of Food

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“…Corn, or maize, which can be harvested once a year, is an agricultural product that ranks third after wheat and rice in terms of cultivation area throughout the world [ 2 ]. As a multipurpose grain widely cultivated in many parts of the world, corn has many different types across the world [ 3 ]. The distinction of corn type is of great importance for crop monitoring, high-throughput phenotyping, and yield prediction [ 4 ].…”

Section: Introductionmentioning

confidence: 99%

Computer-Aided Multiclass Classification of Corn from Corn Images Integrating Deep Feature Extraction

Bhamidipati

Yaşar

Taşpınar

et al. 2022

Computational Intelligence and Neuroscience

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Corn has great importance in terms of production in the field of agriculture and animal feed. Obtaining pure corn seeds in corn production is quite significant for seed quality. For this reason, the distinction of corn seeds that have numerous varieties plays an essential role in marketing. This study was conducted with 14,469 images of BT6470, Calipso, Es_Armandi, and Hiva types of corn licensed by BIOTEK. The classification of images was carried out in three stages. At the first stage, deep feature extraction of the four types of corn images was performed with the pretrained CNN model SqueezeNet 1000 deep features were obtained for each image. In the second stage, in order to reduce these features obtained from deep feature extraction with SqueezeNet, separate feature selection processes were performed with the Bat Optimization (BA), Whale Optimization (WOA), and Gray Wolf Optimization (GWO) algorithms among optimization algorithms. Finally, in the last stage, the features obtained from the first and second stages were classified by using the machine learning methods Decision Tree (DT), Naive Bayes (NB), multi-class Support Vector Machine (mSVM), k-Nearest Neighbor (KNN), and Neural Network (NN). In the classification processes of the features obtained in the first stage, the mSVM model has achieved the highest classification success with 89.40%. In the second stage, as a result of the classifications performed through the active features selected by using three types of feature selection algorithms (BA, WOA, GWO), the classification success obtained with the mSVM model was 88.82%, 88.72%, and 88.95%, respectively. The classification accuracies of the tested methods and the classification accuracies obtained in the first stage are close to each other in terms of classification success. However, with the algorithms used in feature selection, successful classification processes have been carried out with fewer features and in a shorter time. The results of the study, in which classification was carried out in the inexpensive, the objective, and the shorter time of processing for the corn types, present a different perspective in terms of classification performance.

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“…Globally, maize is ranked third behind rice and wheat. Maize is referred as the 'queen of cereals' considering its maximum yield when compared with other cereals (Adeniyi and Ariwoola, 2019). Maize is the highest source of energy in the national diets of 22 countries across the world which includes 16 African countries (Ahaotu et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Microbiological, nutritional and sensory evaluation of snack bars developed using Bambara groundnut (Vigna subterranean L.) and maize (Zea mays)

Ahaotu¹,

Marvellous²,

Maduka³

2022

Afr. J. Microbiol. Res.

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Over the years, snacking has become a regular habit for majority of the population with increasing need for food manufacturers to meet consumers' demand through product development. In this study, snack bars were prepared using maize and Bambara nuts mixed in the following ratios: A, 100% maize; B, 100% Bambara nuts; C, 50% maize: 50% Bambara nuts; D, 75% maize: 25% Bambara nuts; E, 75% Bambara nuts: 25% maize. The total heterotrophic bacterial count of samples A to E was within the limit stipulated by International Commission on Microbiological Specification for Food. The frequency of occurrence of bacterial isolates from the samples include Bacillus species (24%), Staphylococcus species (24%), Lactobacillus species (24%), Escherichia coli (19%) and Serratia species (9%), while the fungal isolates include Aspergillus (33%), Penicillium (27%), Rhizopus (20%) and Saccharomyces species (20%). The moisture, ash, carbohydrate, crude protein, fat and fiber content of the samples were within the range of 11.47±0.

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Comparative Proximate Composition of Maize (Zea mays L.) Varieties Grown in South-western Nigeria

Cited by 13 publications

References 9 publications

Proximal analysis and profile of fatty acids on six varieties of white grain sorghum with potential use in human consumption

Proximal analysis and profile of fatty acids on six varieties of white grain sorghum with potential use in human consumption

Computer-Aided Multiclass Classification of Corn from Corn Images Integrating Deep Feature Extraction

Microbiological, nutritional and sensory evaluation of snack bars developed using Bambara groundnut (Vigna subterranean L.) and maize (Zea mays)

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