Texture estimation model for mulberry fruit from linear measurements

سال انتشار: 1400
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 244

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شناسه ملی سند علمی:

JR_JHPR-4-14_002

تاریخ نمایه سازی: 7 شهریور 1400

چکیده مقاله:

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 ۰, ۱.۵, and ۳ 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 ۳ °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 ۳ minutes with ۳% 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.

نویسندگان

Fatemeh Afsharnia

Department of Agricultural Machinery and Mechanization Engineering, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran

Mahmoud Ghasemi Nejad Raeini

Department of Agricultural Machinery and Mechanization Engineering, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran

Hassan Barzegar

Department of Food Science and Technology, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran

Parisa Ghasemi

Department of Food Science and Technology, Agricultural Sciences and Natural Resources University of Khuzestan, Mollasani, Iran

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