April 18, 2022
March 17, 2022
Mangoes are one of the major tropical fruits produced and exported globally. Efficiently producing and supplying fruits can increase profits for the stakeholders in the industry. The use of NIR spectroscopy to measure mango maturity at harvest time by estimating dry matter is well documented. A little known fact is that NIR spectroscopy can also be used post-harvest for mangoes during sorting, packing, and retailing.
Mangoes are climacteric fruits that can ripen after harvest. This characteristic is exploited by picking them when they are hard but mature. The external and internal appearance, or hardness, gives no clues to the fruit’s maturity. Hence, the dry matter has long been used as a maturity and quality indicator.
Dry matter is the sum total of all the solids in a fruit, minus its water content. The solids include starch, sugars, proteins, fat, fiber, etc.
The dry matter at harvest has also been found to be a good indicator of post-harvest quality since starch is converted to sugars as the mangoes ripen. Total soluble sugars, or sweetness, that reflects the eating quality of fruits has its own measure: the BRIX.
In mangoes, both dry matter (DM) and BRIX can be measured accurately with near infra-red (NIR) spectroscopy. This technique is non-destructive and replaces older, destructive methods of DM and BRIX estimation.
The oven drying method is the conventional method of estimating DM, and the refractometer is used to measure BRIX. In both cases, many fruits are cut for testing; repeated testing, which is necessary to determine maturity or quality, wastes many fruits. Moreover, the methods are time consuming and they require a laboratory and certain level of skill in conducting the tests.
DM is used as the maturity and quality indicator during harvest and during sorting, while total soluble sugars and titrable acidity are used as the quality indicators during post-harvest to measure taste and ripeness.
Figure 1: Difference in DM, TSS, and pulp color in 'Sindhri' mangoes at different harvest (HD) dates, Amin et al. 2016. (Image credits: DOI: 10.17660/ActaHortic.2016.1111.47)
The minimum average DM to harvest mangoes is fixed at 14%. DM at full maturity can increase up to 22% if the fruits are left on the trees; see Figure 1. However, Central Queensland University recommends picking fruits earlier to increase transport time. The university favors harvesting when 90% of the fruits sampled reach the recommended average; for example, this is a DM of 16.5% for Calypso and KP in Australia.
The ideal DM to predict harvest time for mangoes, worldwide, falls in the range of 14-16.5%. This typical DM depends not only on the variety of mangoes, but also the region or country where they are grown.
A farm can be divided into blocks if there is a difference in aspect or other environmental conditions on the farm; the average is calculated per block to get a more homogenous harvest quality and do the picking in phases.
Sorting for fruits takes place at many stages of the supply chain for mangoes: before storage, packaging, and retailing of whole fruits, and processing of fruits; see Figure 2.
Since a sizeable portion of the mango crops globally is meant for export, the introduction of DM, TSS, and titrable acidity measurements post-harvest can improve profits and consumer satisfaction. For example, “Tommy Atkins” mangoes are exported by ship to Germany, but due to poor quality and color on arrival, there is little demand for them.
Figure 2: Using DM, TSS, and titrable acidity to sort mangoes. (Image credits: https://www.slideshare.net/AustralianMangoes/mangoes-a-conditional-nonhost-for-fruit-flies-presentation-from-the-10th-australian-mango-conference)
NIR spectroscopy is a sophisticated technology that has been miniaturized to fit small portable meters that can be used in the farms, sorting and packing houses, warehouses, and laboratories. A beam of light of the chosen NIR spectrum is directed at a fruit. Depending on the compounds and their concentrations, there is a variation in the light that is absorbed, transmitted, or reflected back. These interactions with light are measured to identify the contents and their percentage in the fruit.
Felix Applied Food Science Instruments has several quality meters based on NIR spectroscopy. Two of them can be used for mangoes:
Both instruments can be handled with one hand and give individual measurements within twelve seconds. The devices are user-friendly and easy to use and read. The data from measurements can be stored and categorized according to a single fruit, plant, and plot. The information can be integrated and used with Fruit Maps, the first fruit maturity app available on the global market.
There were 50.65 million metric tons of mangoes that were produced globally in 2017. According to a 2019 Food and Agriculture Organization market review, mangoes make up fifty-two percent of the tropical fruits produced worldwide and make up twenty-three percent of the world trade in tropical fruits. However, the level of loss is also high. In developing countries like Kenya and Bangladesh, nearly forty to fifty percent of mangoes go to waste. Proper harvest, sorting, packing, and storage practices can go a long way in reducing this waste. Instruments like Felix Quality Meters can be used by individual farmers and consultants or shared through farmers’ cooperatives to bring the benefits of state-of-the-art science to the farms and the supply chain for mangoes.
Science Writer, CID Bio-Science
Ph.D. Ecology and Environmental Science, B.Sc Agriculture
Feature image courtesy of Prasanth M J
Altendorf, S. (2019). Major tropical fruits market review 2018. Rome, FAO. Retrieved from http://www.fao.org/3/ca5692en/ca5692en.pdf
Jha, S. N., Jaiswal, P., Narsaiah, K., Kumar, R., Sharma, R., Gupta, M., … Singh, A. K. (2013). Authentication of Mango Varieties Using Near-Infrared Spectroscopy. Agricultural Research, 2(3), 229–235. doi: 10.1007/s40003-013-0068-4
Luca, C. D. (2017, March 23). Factors that influence dry matter. Retrieved from https://www.industry.mangoes.net.au/resource-collection/2017/3/23/factors-that-influence-dry-matter
Malik, A.U., Gayle, M. C., Felipe, L., Pérez-Romero, L. F., & Carlos, C. (2017). Mango Dry Matter Measurement Protocol. Retrieved from https://www.researchgate.net/publication/322153362_Mango_Dry_Matter_Measurement_Protocol
Mango Handling Practices. Retrieved from https://www.mango.org/wp-content/uploads/2017/10/Mango_Handling_Practices_Eng.pdf
Nambi, V., Thangavel, K., & Jesudas, D. (2015). Scientific classification of ripening period and development of colour grade chart for Indian mangoes (Mangifera indica L.) using multivariate cluster analysis. Scientia Horticulturae, 193, 90–98. doi: 10.1016/j.scienta.2015.05.031
Neto, J. P. D. S., Leite, G. W. P., Oliveira, G. D. S., Júnior, L. C. C., Gratão, P. L., Camilo De Lelis Medeiros De Morais, & Teixeira, G. H. D. A. (2018). Cold storage of ‘Palmer’ mangoes sorted based on dry matter content using portable near infrared (VIS-NIR) spectrometer. Journal of Food Processing and Preservation, 42(6). doi: 10.1111/jfpp.13644
Portal, F. (2019, September 8). Overview global mango market - Sept 2019. Retrieved from https://www.farmingportal.co.za/index.php/agri-index/68-crops/3007-overview-global-mango-market-sept-2019
Shahbandeh, M., & Feb. (2020, February 3). Mango production worldwide 2017. Retrieved from https://www.statista.com/statistics/577951/world-mango-production/
Subedi, P., Walsh, K., & Purdy, P. (2013). Determination Of Optimum Maturity Stages Of Mangoes Using Fruit Spectral Signatures. Acta Horticulturae, 992, 521–527. doi:10.17660/actahortic.2013.992.64
Sundararaj, J.S., Muthuswamy, S., & Sadasivam, R. (1972). Storage of mango fruits. Acta Hortic. 24, 265-270. doi: 10.17660/ActaHortic.1972.24.53
Walsh, K., & Subedi, P. (2016). In-field monitoring of mango fruit dry matter for maturity estimation. Acta Horticulturae 1119, 273–278. doi: 10.17660/actahortic.2016.1119.38