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Texture estimation model for mulberry fruit from linear measurements | ||
| Journal of Horticulture and Postharvest Research | ||
| مقاله 2، دوره 4، Issue 3 - شماره پیاپی 14، آذر 2021، صفحه 263-276 اصل مقاله (1.71 M) | ||
| نوع مقاله: Original Article | ||
| شناسه دیجیتال (DOI): 10.22077/jhpr.2020.3658.1162 | ||
| نویسندگان | ||
| Fatemeh Afsharnia1؛ Mahmoud Ghasemi Nejad Raeini* 1؛ Hassan Barzegar2؛ Parisa Ghasemi2 | ||
| 1Department of Agricultural Machinery and Mechanization Engineering, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran | ||
| 2Department of Food Science and Technology, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran | ||
| چکیده | ||
| Purpose: The texture is an essential feature of the nutritional value of fruit and vegetables and plays a critical role in the acceptance and success of these products by the consumer. However, mechanical injuries cause softening and abrasion in the mulberry fruit tissue during harvesting, difficult to assess. The experiment was conducted to estimate the mulberry fruit texture model by linear measurements for several harvesting conditions. Research method: The mulberry may fall from the highest or middle branches or harvest by hand since three heights, including 0, 1.5, and 3 meters, were considered for both maturity stage, including purple and black stage, for dynamic loading experiments to measure texture in an orchard simulated ambiance. Mulberry fruits were stored at 3 °C for seven days. The abrasion area of mulberry fruit was determined by image analysis. Also, TA-XT PLUS Texture Analyzer (micro stable system, England) was used to perform the compression tests of mulberry fruits. Regression analysis of abrasion area versus practical factors (harvesting method, maturity stage, and storage time) was used to develop several models for assessing the area of fruit abrasion. Findings: The combined effect of hot water for 3 minutes with 3% citric acid resulted in better quality fruits (less mass loss, less degradation of soluble solids, organic acids, and vitamin C), in addition to delaying the development of browning pericarp and pulp until the sixth day of storage. Limitations: No limitations were founded. Originality/Value: These models promisingly and accurately estimate the abrasion area of fruit without applying any inaccurate procedures, e.g., using a caliper in many experimental comparisons. | ||
| کلیدواژهها | ||
| Abrasion area؛ Firmness؛ Linear measurements؛ Mulberry؛ Post-harvest quality | ||
| مراجع | ||
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Afsharnia, F., Mehdizadeh, S.A., Ghaseminejad, M. & Heidari, M. (2017). The effect of dynamic loading on abrasion of mulberry fruit using digital image analysis. Information Processing in Agriculture, 4(4), 291-299.
Ball, J. A. (1997). Evaluation of two lipid-based edible coatings for their ability to preserve post-harvest quality of green bell peppers. (Doctoral dissertation, Virginia Tech).
Bland, J. M., & Altman, D. G. (1986). Statistical methods for assessing agreement between two methods of clinical measurements, Lanceti, 327(8476), 307-310. https://doi.org/10.1016/S0140-6736 (86)90837-8
Bonneau, A., Boulanger, R., Lebrun, M., Maraval, I., Valette, J., Guichard, É., & Gunata, Z. (2018). Impact of fruit texture on the release and perception of aroma compounds during in vivo consumption using fresh and processed mango fruits. Food Chemistry, 239, 806-815. https://doi.org/10.1016/j.foodchem.2017.07.017
Cankaya, S., Kayaalp, G. Y., Sangun, L., Tahtali, Y., & Akar, M. (2006). A comparative study of estimation methods for parameters in multiple linear regression model. Journal of Applied Animal Research, 29, 43-47. http://dx.doi.org/10.1080/09712119.2006.9706568.
Derington, A. J., Brooks, J. C., Garmyn, A. J., Thompson, L. D., Wester, D. B., & Miller, M. (2011). Relationships of slice shear force and Warner–Bratzler shear force of beef strip loin steaks as related to the tenderness gradient of the strip loin. Meat Science, 88(1), 203-208. https://doi.org/10.1016/j.meatsci.2010.12.030
Fallovo, C., Cristofori, V., de-Gyves, E. M., Rivera, C. M., Rea, R., Fanasca, S., Bignami, C., Sassine, Y., & Rouphael, Y. (2008). Leaf area estimation model for small fruits from linear measurements. Horticulturae Science, 43(7), 2263-2267. https://doi.org/10.21273/HORTSCI.43.7.2263
Gill, J. L. (1986). Outliers, residuals, and influence in multiple regression. Journal of Animal Breeding and Genetics, 103(1-5), 161-175. http://dx.doi.org/10.1111/j.1439-0388.1986.tb00079.x
Gómez, P. A., & Camelo, A. F. (2002). Calidad postcosecha de tomates almacenados en atmósferas controladas. Horticultura Brasileira, 20(1), 38-43. http://dx.doi.org/10.1590/S0102-05362002000100007.
Holt, J. E., & Schoorl, D. (1976). Bruising and energy dissipation in apples. Journal of Texture Studies, 7, 411-432. https://doi.org/10.1111/j.1745-4603.1977.tb01149.x
Holt, J. E., & Schoorl, D. (1982). Strawberry bruising and energy dissipation. Journal of Texture Studies, 13(3), 349-357. https://doi.org/10.1111/j.1745-4603.1982.tb00888.x
Hong, G., Luo, M. R., & Rhodes, P. A. (2001). A study of digital camera colorimetric characterization based on polynomial modelling. Color Research and Application, 26(1), 76-84. http://dx.doi.org/10.1002/1520-6378(200102)26:13.0.CO;2-3.
Hou, J., Sun, Y., Chen, F., Wang, L., Bai, X., Wang, M., & Mao, Q. (2017). Application of natural frequencies for prediction of apple texture based on partial least squares regression. International Journal of Food Engineering, 13(10), 20160390. https://doi.org/10.1515/ijfe-2016-0390
Huber, D. J. (1983). The role of cell wall hydrolases in fruit softening. Horticultural Reviews, 5, 169-219. http://dx.doi.org/10.1002/9781118060728.ch4
Ioannides, Y., Howarth, M. S., Raithatha, C., Defernez, M., Kemsley, E. K., & Smith, A. C. (2007). Texture analysis of red delicious fruit: towards multiple measurements on individual fruit. Food Quality and Preference, 18(6), 825-833. https://doi.org/10.1016/j.foodqual.2005.09.012
Kay, J., & Pallas, J. (1991). Postharvest physiology of perishable plant produce. University of Georgia, USA, 226.
Khoje, S. (2018). Appearance and characterization of fruit image textures for quality sorting using wavelet transform and genetic algorithms. Journal of Texture Studies, 49(1), 65-83. https://doi.org/10.1111/jtxs.12284
Koyuncu, F. (2004). Organic acid composition of native black mulberry fruit. Chemistry of Natural Compounds, 40(4), 367-369. http://dx.doi.org/10.1023/B:CONC.0000048249.44206.e2
Maia, V. M., Salomão, L. C. C., Siqueira, D. L., Puschman, R., Mota Filho, V. J. G., & Cecon, P. R. (2011). Physical and metabolic alterations in" Prata Anã" banana induced by mechanical damage at room temperature. Scientia Agricola, 68(1), 31-36. http://dx.doi.org/10.1590/S0103-90162011000100005.
Marini, R. P. (2001). Estimating mean fruit weight and mean fruit value for apple trees: Comparison of two sampling methods with the true mean. Journal of the American Society for Horticultural Science, 126, 503-510. http://dx.doi.org/10.21273/jashs.126.4.503
Marquardt, D. W. (1970). Generalized inverse, ridge regression and biased linear estimation. Technometrics, 12, 591-612. http://dx.doi.org/10.2307/1267205.
Miranda, C., & Royo, J. B. (2003a). A statistical model to estimate potential yields in peach before bloom. Journal of the American Society for Horticultural Science, 128, 297-301. https://doi.org/10.21273/JASHS.128.3.0297
Miranda, C., & Royo, J. B. (2003b). Statistical model estimates potential yields in pear cultivars ‘Blanquilla’ and ‘Conference’ before bloom. Journal of the American Society for Horticultural Science, 128, 452-457. https://doi.org/10.21273/JASHS.128.4.0452
Miranda, C., & Royo, J. B. (2004). Statistical model estimates potential yield in ‘Golden Delicious’and ‘Royal Gala’ apples before bloom. Journal of the American Society for Horticultural Science, 129, 20-25. https://doi.org/10.21273/JASHS.129.1.0020
Mohammadi-Aylar, S., Jamaati-e-Somarin, S., & Azimi, J. (2010). Effect of stage of ripening on mechanical damage in tomato fruits. American-Eurasian Journal of Agricultural and Environmental Science, 9(3), 297-302.
Neter, J., Kutner, M. H., Nachtshein, C. J., & Wasserman, W. (1996). Applied linear regression models. 3rd Ed., Homewood, Ill., Irwin.
Özgen, M., Güneş, M., Akça, Y., Türemiş, N., Ilgin, M., Kizilci, G., Erdoğan, Ü., & Serçe, S. (2009). Morphological characterization of several Morus species from Turkey. Horticulture Environment and Biotechnology, 50(1), 9-13.
Papadakis, S. E., Abdul-Malek, S., Kamdem, R. E., & Yam, K. L. (2000). A versatile and inexpensive technique for measuring color of foods. Food Technology, 54(12), 48-51.
Paull, R. (1999). Effect of temperature and relative humidity on fresh commodity quality. Postharvest Biology and Technology, 15(3), 263-277. http://dx.doi.org/10.1016/S0925-5214(98)00090-8.
Peksen, E. (2007). Non-destructive leaf area estimation model for faba bean (Vicia faba L.). Scientia Horticulturae, 113, 322-328. http://dx.doi.org/10.1016/j.scienta.2007.04.003
Pinheiro, S. C. F. & Almeida, D. P. F., (2008). Modulation of tomato pericarp firmness through pH and calcium: Implications for the texture of fresh-cut fruit. Postharvest Biology and Technology, 47(1), 119-125. https://doi.org/10.1016/j.postharvbio.2007.06.002
Pitt, R. (1992). Viscoelastic properties of fruits and vegetables. Viscoelastic Properties of Foods, 49-76.
Ragni, L., Cevoli, C., Berardinelli, A., & Silaghi, F. A. (2012). Non-destructive internal quality assessment of “Hayward” kiwifruit by waveguide spectroscopy. Journal of Food Engineering, 109(1), 32-37.
Sánchez, M. D. (2002). World distribution and utilization of mulberry and its potential for animal. Proceedings of Electronic Conference on Mulberry for Animal Production. May and August 2000. Food and Agriculture Organization. http://www.fao.org/ DOCREP/005/X9895E/x9895e02.htm
Sánchez-Salcedo, E. M., Mena, P., García-Viguera, C., Martínez, J. J. & Hernández, F. (2015). Phytochemical evaluation of white (Morus alba L.) and black (Morus nigra L.) mulberry fruits, a starting point for the assessment of their beneficial properties. Journal of Functional Foods, 12, 399-408.
Subedi, P. P., & Walsh, K. B. (2009). Non-invasive techniques for measurement of fresh fruit firmness. Postharvest Biology and Technology, 51(3), 297-304. https://doi.org/10.1016/j.postharvbio.2008.03.004
Taniwaki, M., Sakura, N., & Kato, H. (2010). Texture measurement of potato chips using a novel analysis technique for acoustic vibration measurements. Food Research International, 43(3), 814-818. https://doi.org/10.1016/j.foodres.2009.11.021
Van Dijk, C., Boeriu, C., Peter, F., Stolle-Smits, T., & Tijskens, L. M. M. (2006a). The firmness of stored tomatoes (cv. Tradiro). 1. Kinetic and near infrared models to describe firmness and moisture loss. Journal of Food Engineering, 77(3), 575-584. https://doi.org/10.1016/j.jfoodeng.2005.07.029
Van Dijk, C., Boeriu, C., Stolle-Smits, T., & Tijskens, L. M. M. (2006b). The firmness of stored tomatoes (cv. Tradiro). 2. Kinetic and near infrared models to describe pectin degrading enzymes and firmness loss. Journal of Food Engineering, 77(3), 585-593. https://doi.org/10.1016/j.jfoodeng.2005.07.017
Watcharasing, J., Thiralertphanich, T., Panthuwadeethorn, S., & Phimoltares, S. (2019). Classification of fruit in a box (FIB) using hybridization of color and texture features. 16th International Joint Conference on Computer Science and Software Engineering (JCSSE). Chonburi, Thailand (pp. 303-308). https://doi.org/10.1109/JCSSE.2019.8864164.
Watson, L., & Dallwitz, M. J. (2007). Moraceae. The families of flowering plants: Descriptions, illustrations, identification, and information RetrieVal. 1992 onward. CABI.
Weaver, W.W. (2001). Sauer's herbal cures: America's first book of botanic healing, 1762-1778. Taylor and Francis.
Zhang, B., Peng, B., Zhang, C., Song, Z., & Ma, R. (2017). Determination of fruit maturity and its prediction model based on the pericarp index of absorbance difference (I AD) for peaches. PloS One, 12(5), p.e0177511. https://doi.org/10.1371/journal.pone.0177511 | ||
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