OPTIMIZATION OF THE ORGANIC FRUIT AND VEGETABLE DRYING PROCESS BY USING NON-DESTRUCTIVE TECHNIQUES

The aim of this project is the obtainment of a smart-prototype drier able to improve the hot-air drying process of organic fruits and vegetables using non-destructive technologies. Thus, a quality by design (QbD) approach has been followed in order to improve products quality and control strategy. For the intended purpose, both at-line near infrared spectroscopy (NIRS) and in-line computer vision (CV) techniques were tested. The data matrices were then subjected to chemometrics analysis in order to develop prediction and classification models able to follow up physico-chemical changes and recognise dehydration phases, respectively. Thermal (i.e. hot-water, microwave or steam blanching) and dipping (i.e. non-reducing sugar and/or ascorbic acid) pre-treatments were investigated as viable alternatives to reduce browning occurrence. Excellent performances (R2 = 0.91 - 0.98) were achieved in predicting physico-chemical changes (e.g. water activity, moisture content, soluble solid content, etc.) using NIRS coupled with partial least squares regression algorithm for both apple (var. Gala) and carrot (var. Romance). The prediction of colour changes using NIR wavelengths gave good results (R2 = 0.80 - 0.87), probably due to the fact that it is an indirect measurement. Features selection led to comparable prediction performances while reducing model complexity. Similarly, partial least squares discriminant analysis PLS-DA provided from good (> 0.85) to excellent (> 0.95) results in terms of sensitivity and specificity rates for the recognition of drying phases. Finally, computer-vision analysis showed potentiality in simultaneously monitoring morphological (e.g. area shrinkage and eccentricity), colour (CIELab) and physicochemical (moisture and drying rate) changes on apple cylinders during the process. Indeed, linear regression models gave excellent results (R2 = 0.993-0.999) in predicting changes in moisture content on the basis of the area shrinkage. The results confirm the feasibility of an accurate smart-control of the drying process based on non-destructive technology and set the basis for a scale up of the process

Feasibility of computer vision as Process Analytical Technology tool for the drying of organic apple slices

Quality of a product and sustainability of its production depend on the cumulative impacts of each processing step in the food chain and their interplay. Various research studies evidenced that many drying systems operate inefficiently in terms of drying time, energy demand (e.g. fossil fuels), raw material utilisation and resulting product quality. Moreover, not all conventional drying processes are allowed in the organic sector (Reg. EC 834/2007; Reg. EC 889/2008). In recent years, non-invasive monitoring and control systems have shown a great potential for improvement of the quality of the resulting products. Thus, there is a need for smart processes which allow for simultaneous multi factorial control to guarantee high-value end products, enhance energy and resource efficiency by using innovative and reliable microcontrollers, sensors and embracing various R&D areas (e.g. computer vision, deep learning, etc.). The objective of this study was to evaluate the feasibility of computer vision (CV) as a tool in development of smart drying technologies to non-destructively forecast changes in moisture content of apple slices during drying. Usage of computer vision (CV) as Process Analytical Technology in drying of apple slices was tested. Samples were subjected to various anti-browning treatments at sub- and atmospheric pressures, and dried at 60°C up to a moisture content on dry basis (MCdb) of 0.18 g/g. CV-based prediction models of changes in moisture content on wet basis (MCwb) were developed and promising results were obtained (R2P > 0.99, RMSEP = 0.011÷0.058 and BIASP < 0.06 in absolute value), regardless of the anti-browning treatment. The proposed methodology lays the foundations for a scale-up smart-drying system based on CV and automation

Feasibility of computer vision as Process Analytical Technology tool for the drying of organic apple slices

Usage of computer vision (CV) as Process Analytical Technology tool in drying of apple slices was tested. Samples were subjected to various anti-browning treatments at sub- and atmospheric pressures, and dried at 60°C up to a moisture content (dry basis) of 0.18 g/g. CV-based prediction models of changes in moisture content (wet basis) were developed and promising results were obtained (R2P > 0.99, RMSEP = 0.01÷0.06 and BIASP < 0.06 in absolute value), regardless of the anti-browning treatment

Linee guida per la trasformazione degli ortofrutticoli

Indice dei contenuti Agricoltura biologica dell'UE, norme di produzione Elencodeimetodi di trasformazione: - Minimamente processat - Mediamentep rocessata - Altamente processata Elenco dei metodi di trasformazione: - Ortofrutticoli tagliati freschi - Ortofrutticoli in scatola - Prodotti refrigerati e congelati - Prodotti disidratati - Trasformazione in succhi e blend - Prodottifermantati e sotto salamoia/aceto - Spezie ed erbearomatich

Linee di processo degli ortofrutticoli biologici

Agricoltura biologica dell'UE, norme di produzione Definizione di trasformazione di frutta e verdura: - Minimamente processata - Mediamente processata - Altamente processata Elenco dei metodi di trasformazione: - Ortofrutticoli tagliati freschi - Ortofrutticoli in scatola - Prodotti refrigerati e congelati - Prodotti disidratati - Trasformazione in succhi e blend - Prodotti fermantati e sotto salamoia/aceto - Spezie ed erbe aromatich

Module 6.1 Organic vegetable processing (1)/Ökologische Gemüseverarbeitung (1)/Processo degli ortofrutticoli biologici (1)

Fruit and vegetables processing is the set of methods and techniques used to transform raw ingredients into food for consumption. Organic processing needs to meet the organic integrity in terms of sustainability along the whole value chain

Module 6.2 Organic vegetable processing (2)/Ökologische Gemüseverarbeitung (2)/Processo degli ortofrutticoli biologici (2)

Development of knowledge and skills on food quality and safety and main criteria applied to organic produc

Aspetti generali della disidratazione

1. Le domande e le esigenze dei mercati globalizzati 2. Disidratazione degli alimenti - Panoramica della tematica - Qualità e sicurezza degli alimenti - Impatto sui costi di produzione - Tipologie di disidratazione - Impatto della disidratazione sulle caratteristiche qualitative del prodotto - La percezione dei consumatori della qualità dei prodotti disidratati Cambiamenti di colore - L’imbrunimento enzimatico - L’imbrunimento non enzimatico - Composizione chimica della specie e delle cultivar - Efficienza energetica - Aspetti generali - Un approccio di tipo «Quality By Design» - Tecnologie di disidratazione innovative - Disidratazione «smart» - Spettroscopia Vis/NI

Module 4.1 Drying - general aspects/Allgemeine Aspekte der Lebensmitteltrocknung/Aspetti generali della disidratazione

Market globalization ensures constant availability of many foods regardless of their production date. Innovation in both products and processes across the entire agri-food chain yield foods with improved shelf-life, organoleptic quality, nutritional value, safety and healthfulness

Processing and Quality Guidelines for Organic Food Processing

ForewordThese guidelines on quality and processing of organic foods have been prepared as part of the Core Organic Plus funded project “SusOrganic - Development of quality standards and optimi-sed processing methods for organic produce”. They intend to support actors in the organic food processing sector to simultaneously increase resource efficiency and product quality of their produce by providing deeper insights in raw material, process and product relevant aspects. The main focus of the presented work lies on the preservation of fruits, herbs, vegetables, fish and meat by the means of drying and chilling/freezing. THE AIMS OF THESE GUIDELINES ARE TO PROVIDE THE PROCESSORS WITH: • Drying related aspects • A deeper understanding for naturally occurring heterogeneities in raw materials and their impact on drying characteristics • Information on the impact of pre-treatment and holding time between preparation and drying on the resulting product quality • Information on the impact of drying and the related process settings on product quality • Information on improved drying strategies and process control concepts • Best practice examples for processing • Best practice based on LCA and LCCA • Food drying and related food logistics • Chilling and Freezing related aspects • General aspects of superchilling • Superchilling for organic meat and fish • Effects of freezing and freezing rate on organic fruit