Effect of maturity stages on the quality indices of wood apple (Feronia limonia) and modeling of its kinetics by applying machine learning approaches

Authors

  • J Goyary Assam University, Silchar - 788011, Assam, India Author
  • C B Khobragade Assam University, Silchar - 788011, Assam, India Author
  • S Chakraborty Ghani Khan Choudhury Institute of Engineering and Technology Narayanpur, Malda - 732141, West Bengal, India Author
  • A Tiwari Assam University, Silchar - 788011, Assam, India Author

DOI:

https://doi.org/10.24154/jhs.v18i1.2155

Keywords:

Bio-chemical properties, K-means cluster algorithm, maturity stages, wood apple

Abstract

In the present investigation, an inexpensive and non-destructive method was tested for the appropriate maturity classification of wood apple (Feronia limonia). The investigation was conducted to establish the pronounced effect of maturity stages on the growth kinetics, physico-chemical properties, and other quality indices of wood apple. A systematic trend was observed for all the properties namely sphericity, bulk density (g/cm3), true density (g/cm3), pH, total soluble solids TSS (°Brix), titratable acidity (%) and TSS/TA ratio, etc. of the fruit. In contrast, regular changes were also observed in the color properties at various maturity stages of the wood apple. The maturity kinetics was formulated by applying recurrent neural network (RNN) in compliance with K means cluster algorithm. RNN modeling was applied by considering color property (redness value) as input and six maturity indices as the output of the formulated structure. The RNN architecture, 1-6-6 showed the best results for forecasting the wood apple maturity based on color features. Further, based on the results of the K means cluster algorithm, the maturity stages were classified into three main categories, illustrated in the form of a simplified color chart. Hence, this investigation can be useful for proper control and identification of wood apple maturity during the processing.

References

Anonymous. 2018. Annual report. Ministry of Agriculture and Farmers welfare. www.agricoop.nic.in. (access date 18/09/2021).

AOAC. 2005. Official methods of analysis, Association of Official Analytical Chemists, Washington DC.

Avila, F., Mora, M., Oyarce, M., Zuñiga, A. and Fredes, C. 2015. A method to construct fruit maturity color scales based on support machines for regression: Application to olives and grape seeds. J. Food Engg., 162: 9-17. DOI: https://doi.org/10.1016/j.jfoodeng.2015.03.035

Bayram, M. 2005. Determination of the sphericity of granular food materials. J. Food Engg., 68(3): 385-390. DOI: https://doi.org/10.1016/j.jfoodeng.2004.06.014

Bobade, H., Sharma, S. and Singh, A. 2020. Indian Bael. In: Antioxidants in Fruits: Properties and Health Benefits (Ed.) Springer, Singapore, pp. 135-161. DOI: https://doi.org/10.1007/978-981-15-7285-2_8

Cheroutre-Vialette, M. and Lebert, A. 2002. Application of recurrent neural network to predict bacterial growth in dynamic conditions. Inter. J. Food Microbio., 73(23): 107-118. DOI: https://doi.org/10.1016/S0168-1605(01)00642-0

Devi, V.S. and Kulkarni, U.N. 2018. Physico-chemical characteristics and nutrient composition of wood apple (Ferona limonia Swingle) fruit with and without seeds. J. Farm Sci., 31(2): 192.http://14.139.155.167/test5/index.php/kjas/ article/view/8780

Goyary, J., Khobragade, C.B., Tiwari, A. and Malakar, S. 2021. A preliminary study of modeling the thin-layer drying kinetics of wood apple pulp in hot air oven. Bull. Environ. Pharma. Life Sci., 10(6): 106-111.

Gupta, A.K., Medhi, M., Chakraborty, S., Yumnam, M. and Mishra, P.2020. Development of rapid and non-destructive technique for the determination of maturity indices of pomelo fruit (Citrus grandis). J. Food Measur. Charac., 15(2): 1463-1474. DOI: https://doi.org/10.1007/s11694-020-00734-4

Jamil, M.S., Nadeem, R., Hanif, M.A., Ali, M.A. and Akhtar, K. 2010. Proximate composition and mineral profile of eight different unstudied date (Phoenix dactylifera L.) varieties from Pakistan. African J. Biotec., 9(22): 252-3259.

Karastogianni, S., Girousi, S. and Sotiropoulos, S. 2016. pH: principles and measurement. The Encyclo. Food Healt., 4: 333-338. DOI: https://doi.org/10.1016/B978-0-12-384947-2.00538-9

Khalloufi, S., Almeida-Rivera, C. and Bongers, P. 2010. A fundamental approach and its experimental validation to simulate density as a function of moisture content during drying processes. J. Food Engg., 97(2): 177-187. DOI: https://doi.org/10.1016/j.jfoodeng.2009.10.007

Kumar, A. and Deen, B. 2017. Studies on bio- chemical changes in wood apple (Limonia acidissima L.) fruits during growth and development. Int. J. Curr. Microbiol. App. Sci., 6(8): 2552-2560. DOI: https://doi.org/10.20546/ijcmas.2017.608.302

López-Camelo, A.F. and Gómez, P.A. 2004. Comparison of color indexes for tomato ripening. Horticul. Brasil., 22: 534-537. DOI: https://doi.org/10.1590/S0102-05362004000300006

Mani, A. and Mitra, S. 2020. Nutritional and medicinal properties of wood apple. Agriculture & Food: e-Newsletter, 2(5): 71-72.

Mansouri, A., Mirzabe, A.H. and Raufi, A.2017. Physical properties and mathematical modeling of melon (Cucumis melo L.) seeds and kernels. J. Saudi Soci. Agric. Sci., 16(3): 218-226. DOI: https://doi.org/10.1016/j.jssas.2015.07.001

Mohammadi, V., Kheiralipour, K. and Ghasemi- Varnamkhasti, M. 2015. Detecting maturity of persimmon fruit based on image processing technique. Sci. Hortic., 184: 123-128. DOI: https://doi.org/10.1016/j.scienta.2014.12.037

Mohsenin, N. N. 1970. Physical properties of plant and animal materials. In: Structure, Physical Characteristics and Mechanical Properties (Vol. 1). (Eds.) Gordon and Breach Science Publishers, New York.

Murakonda, S. Patel, G. and Dwivedi, M. 2021. Characterization of engineering properties and modeling mass and fruit fraction of wood apple (Limonia acidissina) fruit for post-harvest processing. J. Saudi Soc. Agric. Sci. DOI: https://doi.org/10.1016/j.jssas.2021.09.005

Pacheco, W.D.N. and López, F.R.J., 2019. Tomato classification according to organoleptic maturity (coloration) using machine learning algorithms K-NN, MLP, and K-Means Clustering. In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA). IEEE. pp. 1-5. DOI: https://doi.org/10.1109/STSIVA.2019.8730232

Ranganna, S.1986. Handbook of analysis and quality control for fruit and vegetable products. Tata McGraw-Hill Education.

Rao, N.G., Rao, P.P.G. and Rao, G.D. 2011. Preparation of wood apple (Feronia limonia L.) seed protein concentrate and evaluation of its nutritional and functional characteristics. Inter. Food Res. J., 18(3): 949-955.

Shanno, D.F. 1970. Conditioning of quasi-Newton methods for function minimization. Mathe. Comput., 24(111): 647-656. DOI: https://doi.org/10.1090/S0025-5718-1970-0274029-X

Sharma, H.P., Patel, H., Sharma, S. and Vaishali. 2014. Study of physic-chemical changes during wood apple (Feronia limonia) maturation. J. Food Res. Tech.,2(4): 148-152.

Slavin, J.L. and Lloyd, B. 2012. Health benefits of fruits and vegetables. Adv. Nutr., 3(4): 506-516. DOI: https://doi.org/10.3945/an.112.002154

Sonawane, A., Pathak, S.S. and Pradhan, R.C. 2020. Physical, thermal, and mechanical properties of bael fruit. J. Food Proc. Engg., 43(6): e13393. DOI: https://doi.org/10.1111/jfpe.13393

Su, M., Zhang, B., Ye, Z., Chen, K., Guo, J., Gu, X. and Shen, J.2013. Pulp volatiles measured by an electronic nose are related to harvest season, TSS concentration and TSS/TA ratio among 39 peaches and nectarines. Sci. Hortic. 150: 146-153. DOI: https://doi.org/10.1016/j.scienta.2012.10.020

Tscheuschner, H.D., 1987. NN Mohsenin: Physical Properties of plant and animal materials. Structure, Physical Characteristics and Mechanical Properties. 2. Aufl. 891 Seiten, zahlr. Abb. und Tab. Gordon and Breach Science Publishers, New York ua 1986. Preis: 140. DOI: https://doi.org/10.1002/food.19870310724

Yadav, T., Vishwakarma, D., Saloni, S. and Tiwari, S. 2018a. Wood apple : Its nutritive value and medicinal benefits. Inter. J. Agricul. Engg., 11: 159-163. DOI: https://doi.org/10.15740/HAS/IJAE/11.Sp.Issue/159-163

Yadav, V., Singh, A.K., Rao, V.A., Singh, S. and Saroj, P.L. 2018b. Wood apple variability: An underutilized dry land fruit from Gujarat, India. DOI: https://doi.org/10.20546/ijcmas.2018.706.063

Zhang, W., Chen, K., Zhang, B., Sun, C., Cai, C., Zhou, C., Xu, W., Zhang, W. and Ferguson, I.B. 2005. Post-harvest responses of Chinese bayberry fruit. Posthar. Biol. Techno., 37(3): 241-251. DOI: https://doi.org/10.1016/j.postharvbio.2005.05.005

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Published

30-06-2023

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Section

Research Papers

How to Cite

Goyary, J., Khobragade, C. B., Chakraborty, S., & Tiwari, A. (2023). Effect of maturity stages on the quality indices of wood apple (Feronia limonia) and modeling of its kinetics by applying machine learning approaches. Journal of Horticultural Sciences, 18(1), 128-137. https://doi.org/10.24154/jhs.v18i1.2155

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