The general aim of the project SUS&LOW is to increase the sustainability of fresh produce by testing and implementing lowinput agricultural practices (LIP) with positive impact on product quality with the support of nondestructive (ND) tools for realtime quality assessment and for product discrimination. Additionally, new marketing strategies are generated to better support the added value of the products and to satisfy the final consumers' preferences. The SUS&LOW project consists of three work packages (WP) and the adopted methodology used two model crops: rocket salad and tomato. The WP1, focused on the reduction of agricultural inputs, showed that sensorbased fertigation management might improve sustainability of soilless cultivation. Results coming from WP2, aimed to the evaluation of ND techniques, outlined the high potentiality of hyperspectral imaging (HSI) and Fourier transformednear infrared (FTNIR) techniques for the authentication of sustainable growing methods. Moreover, project activities' proved computer vision system (CVS) as an effective tool for evaluating the product quality also through the bag. The WP3, dealing with marketing strategies, indicated a positive approach of consumers compared to LIP products certified through a visual storytelling platform.
Sustaining lowimpact practices in horticulture through nondestructive approach to provide more information on fresh produce history and quality: the SUS&LOW project
G Attolico;L Bonelli;M Cefola;B Pace;M Palumbo;F Serio;
2023
Abstract
The general aim of the project SUS&LOW is to increase the sustainability of fresh produce by testing and implementing lowinput agricultural practices (LIP) with positive impact on product quality with the support of nondestructive (ND) tools for realtime quality assessment and for product discrimination. Additionally, new marketing strategies are generated to better support the added value of the products and to satisfy the final consumers' preferences. The SUS&LOW project consists of three work packages (WP) and the adopted methodology used two model crops: rocket salad and tomato. The WP1, focused on the reduction of agricultural inputs, showed that sensorbased fertigation management might improve sustainability of soilless cultivation. Results coming from WP2, aimed to the evaluation of ND techniques, outlined the high potentiality of hyperspectral imaging (HSI) and Fourier transformednear infrared (FTNIR) techniques for the authentication of sustainable growing methods. Moreover, project activities' proved computer vision system (CVS) as an effective tool for evaluating the product quality also through the bag. The WP3, dealing with marketing strategies, indicated a positive approach of consumers compared to LIP products certified through a visual storytelling platform.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.