Volume estimation models for avocado fruit

Language
en
Document Type
Article
Issue Date
2022-05-10
Issue Year
2022
Authors
Mokria, Mulugeta
Gebrekirstos, Aster
Said, Hadia
Hadgu, Kiros
Hagazi, Niguse
Dubale, Workneh
Bräuning, Achim
Editor
Abstract

Avocado (Persea americana Mill.) is an important horticultural crop and proved to be a very profitable commercial crop for both local consumption and export. The physical characteristics of fruits are an important factor to determine the quality of fruit produced. On the other hand, estimation of fruit volume is time-consuming and impractical under field conditions. Thus, this study was conducted to devise cultivar-specific and generalized allometric models to analytically and non-destructively determine avocado fruit volume of five wildly distributed avocado cultivars. A significant relationship (P ≤ 0.01) was found between fruit diameter, length, and volume of each cultivar. Our best models (VM2 –for cultivar specific, and VM7-generalized model) has passed all the rigorous cross-validation and performance statistics tests and explained 94%, 92%, 87%, 93%, 94% and 93% of the variations in fruit volume of Ettinger, Fuerte, Hass, Nabal, Reed, and Multiple cultivars, respectively. Our finding revealed that in situations where measurements of volume would be inconvenient, or time-consuming, a reliable volume and yield estimation can be obtained using site- and cultivar-specific allometric equations. Allometric models could also play a significant role in improving data availability on avocado fruit physical appearance which is critical to assess the quality and taste of fresh products influencing the purchase decision of customers. Moreover, such information can also be used as a ripeness index to predict optimum harvest time important for planned marketing. More importantly, the models might assist horticulturists, agronomists, and physiologists to conduct further study on avocado production and productivity through agroforestry landuse system across Ethiopia.

Journal Title
PLoS ONE
Volume
17
Issue
2
Citation
PLoS ONE 17.2 (2022): e0263564. <https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0263564>
Zugehörige ORCIDs