Aller au contenu principal
2012 article

Prediction of volume, weight and surface area of banana (Musa acuminata) using picture image analysis

3Citations signalées, ce qui n’est pas une note de qualité
0Institutions déclarées
0Pays d’affiliation déclarés

Le résumé fourni par la source

The design of processing equipments, materials and processes for the handling of crops require data of the physical properties of the crops such as weight, volume and surface area. Obtaining these data can be very tedious and destructive to the samples being used. This research aims at a nondestructive, fast, but accurate and easy way of finding volume, weight, and surface area of a crop from its picture image. Banana (Musa acuminata) was used for the study and the mean weight, volume, surface area, plan area, and plan perimeter were 142.07±23.48 g, 158.90±33.14 cm 3 , 171.25±22.32 cm 2 , 79.34±10.45 cm 2 and 47.41±3.72 cm, respectively. The values obtained were correlated, using plan area and perimeter as the independent variables and weight, volume and surface area as the dependent variables. The prediction equations obtained using plan area measurements are Weight (g) = 1.866×plan area (cm 2 ) – 5.9649; Volume (cm 3 ) = 1.8518×plan area (cm 2 ) – 11.978; Surface area (cm 2 ) = 1.5568×plan area (cm 2 ) – 47.737. These prediction equations offer better prediction values than perimeter, but of these equations only the prediction equation for weight can be used with an appreciable r-squared value of 68.89%. Therefore, this equation can be used by designers after obtaining a picture image of the banana.

Ce résumé expose les affirmations des auteurs. BNTIC ne l’interprète pas comme une validation indépendante des résultats.

Le contrôle bibliographique ouvert

Aucun DOI disponible pour le contrôle Crossref.

Les sujets associés

Agricultural Engineering and MechanizationLeaf Properties and Growth MeasurementMechanical Engineering and Vibrations Research

BNTIC News n’est pas le producteur de ces données. Les publications sont interrogées à la demande dans Crossref, OpenAIRE, DOAJ, Europe PMC, HAL, DataCite, AfricArXiv, ROR et la Banque mondiale, sans clé d’accès. OpenAlex reste optionnel. Aucun service payant n’est nécessaire et aucune donnée externe n’est enregistrée en base. Consulter les sources et leurs limites.