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Color Shade Nets Improve Vegetables Quality at Harvest and Maintain Quality During Storage Cover

Color Shade Nets Improve Vegetables Quality at Harvest and Maintain Quality During Storage

Open Access
|Mar 2018

Abstract

The photoselective, light-dispersive shade nets can be used as an alternative to protect crops from adverse environmental conditions such as; excessive solar radiation, heat and drought stress, wind and hail, birds, flying pests, thus improving crop’s production, yield and quality. The physiological parameters discussed in the review include: vegetable growth parameters (leaf area, leaf chlorophyll), tissue structure, fruit ripening, physiological disorders, pest and disease incidence, fruit quality parameters (soluble solids content and titratable acidity), bioactive compounds (antioxidant activity, ascorbic acid, carotenoid and flavonoid contents) and aroma volatile compounds at harvest. Also, it is evident in the reviewed literature that light quality influences the biosynthesis, accumulation and retention of vegetable phytochemicals, as well as the decay development during storage. These new strategies to modulate light quality should be conveyed to vegetable producing farmers, thus allowing them to preserve the freshness and post-harvest quality of vegetables for an extended period of time, and to meet the consumers demand for vegetables with high nutritional value all year round. Research on light manipulation in horticultural systems is necessary for a sustainable and market-oriented open field and greenhouse vegetable production in the future.

DOI: https://doi.org/10.2478/contagri-2018-0002 | Journal eISSN: 2466-4774 | Journal ISSN: 0350-1205
Language: English
Page range: 9 - 19
Submitted on: Sep 1, 2017
Accepted on: Dec 18, 2017
Published on: Mar 9, 2018
Published by: University of Novi Sad
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2018 Zoran S. Ilić, Lidija Milenković, Ljubomir Šunić, Maja Manojlović, published by University of Novi Sad
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.