Non-destructive techniques to determine optimal harvesting time in mango fruit

Authors: OSUNA-GARCIA, JORGE - Instituto Nacional De Investigaciones Forestales Y Agropecuarias (INIFAP); GRACIANO-CRISTOBAL, MARIA - Instituto Nacional De Investigaciones Forestales Y Agropecuarias (INIFAP); Goenaga, Ricardo

Submitted to: Acta horticulturae
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/10/2024
Publication Date: 1/30/2025
Citation: Osuna-Garcia, J.A., Graciano-Cristobal, M.J., Goenaga, R.J. 2025. Non-destructive techniques to determine optimal harvesting time in mango fruit. Acta horticulturae. 1415: 155-162. https://doi.org/10.17660/ActaHortic.2025.1415.17.
DOI: https://doi.org/10.17660/ActaHortic.2025.1415.17

Interpretive Summary: When mangoes are exported over long distances, fruits are often harvested when they are green and not fully ripe. This can result in fruit that doesn’t meet the quality and flavor expectations of consumers. In Mexico, current methods for determining ripeness (pulp color and total soluble solids) are destructive, meaning they damage the fruit. Some countries use dry matter (DM) content as a non-destructive technique, but Mexico doesn't have local standards for this method. This research aimed to create and validate a model to predict the DM content of major mango varieties exported from Mexico. In 2019, five groups of 40 mangoes each were harvested from 'Tommy Atkins,' 'Ataulfo,' 'Kent,' and 'Keitt' cultivars at different ripeness stages. These mangoes were scanned using an F-750® spectrometer, and the DM values were determined using a forced air convection oven. An artificial neural network model was developed and validated in 2020 and 2021. The model successfully predicted the DM content with high accuracy, showing only a small difference (0.4%) between the spectrometer and conventional methods. This means the F-751® spectrometer can non-destructively determine the DM content for various cultivars, helping to ensure that mangoes are harvested at the right ripeness stage for optimal quality and flavor. 'Ataulfo' showed the best fit for the model, while 'Keitt' had the worst.

Technical Abstract: When exported to long distance markets, mango fruit is harvested at green ripe stage. Thus, fruit quality and flavor not always reach the market according to consumer’s requirement. In Mexico, pulp colour and total soluble solids content are used as harvest criteria; however, both are destructive. Some countries use the dry matter (DM) content, which is a non-destructive technique, but it is not applied because there are no local standards. Therefore, the objectives were to build and validate a model to predict the DM content of main mango exporting varieties in Mexico. During 2019, five groups of 40 fruits each (from unripe to already colourful) were harvested from ‘Tommy Atkins’, ‘Ataulfo’, ‘Kent’ and ‘Keitt’ cultivars. The 200 fruits were scanned in both cheeks with an F-750® spectrometer to obtain the DM values. The reference values were attained by a forced air oven at 60°C for 72 h. The model was built by means of the artificial neural network application and validated during 2020 and 2021 in commercial orchards. Dry matter was estimated applying the model generated in 2019 and loaded into an F-751® spectrometer. The model was promising since it presented an R2=0.8487 and an RMSE=0.9059. Regarding validation, the average values of cultivars and ripening stages at harvest were 15.6% for the spectrometer and 15.2% for the conventional method, only 0.4 points of difference. It indicates the feasibility of the F-751® to determine non-destructively the DM content of any of the cultivars; although differences were detected among them. ‘Ataulfo’ showed the best fit of the prediction model, while ‘Keitt’ had the worst.