PROJECT DESCRIPTION
Brief Description
The main idea of this project is to sustain the quality of production and of the environment by means of low input agricultural practices (LIP) and non-destructive (ND) quality evaluation.
ND quality evaluation will, in fact, provide evidence of production quality and will be an additional tool for discrimination of fresh products obtained with LIP and estimation of quality and shelf-life of packaged products. This last information will be used in order to design strategies to ensure better marketing conditions for fresh produce from LIP. Reduction of the agricultural inputs in the greenhouses will be obtained optimizing the use of water and fertilizers in soilless and soil cultivation in the first work package (WP1). In WP2, the quality attributes of the production will be assessed by conventional and ND approaches with emphasising on possible differences deriving from the application of LIP, developing algorithms for discrimination based on spectral information. Then, in the WP3, the possible influence on consumer choices of certification of LIP practices resulting from ND methods and their willingness to pay will be tested in order to produce adequate and realistic marketing strategies. Finally, dissemination and coordination activities will be carried out in WP4 and WP5 respectively.
Key Words:
Sustainability, Food Quality, Computer Vision, Spectroscopic and Spectrometric Techniques, Vegetable Crops,
Non-Destructive Evaluation
General Aim
The general aim of the project is to increase the amount of sustainably-produced fresh produce by testing and implementing low-input agricultural practices (LIP) with a positive impact on product quality with the support of non-destructive (ND) tools for real-time quality assessment and product discrimination, which may inspire new marketing strategies to better support the added value of the products and increase incomes of potential users. Producing high-quality products represents a key driver in the horticultural sector although the concept of quality has evolved substantially over the past few decades. From traditional attributes (visual and organoleptic) also representing the main focus of most of the quality standards and regulations, more recently other important aspects are gaining relevance: the consolidated consumer attention towards the nutritional value of fresh horticultural products and their increasing sensitivity towards the environmental impact of production processes. Efficient use of resources (water and fertilizers) in irrigated greenhouse agriculture are promising and increasingly adopted strategies to achieve better crop performance, improved nutritional, and sensorial quality.
The proposed methodology will use two crop models: rocket leaves (Diplotaxis tenuifolia L.) and tomato (Solanum Lycopersicum L.), representing leafy and fruit vegetables, diffusely produced in greenhouses.
General Objective
The general objective of the project will be reached through the following partial objectives:
To increase the efficiency of water and fertilizers in soilless (with open and closed-cycles with recirculation of nutrients) and soil cultivation in unheated greenhouses in order to reduce the impact on the environment and on the society.
To assess the quality of products with conventional and innovative non-destructive approaches, providing innovative tools for the discrimination of those obtained by LIP and for the quality prediction of products while in their package.
To test the hypothesis of the influence of quality certification of LIP practices resulting from ND methods on consumer choices and their willingness to pay, in order to produce adequate and realistic marketing strategies.
Expected Results
The project results are expected to reduce the impact of agriculture on the environment, ensuring high-quality crop to the consumer, higher incomes to farmers, and reduced food losses to the society. The added information on crop history and the marketing strategies will allow to sustain and diffuse the use of LIP, creating a virtuous mechanism which will positively affect further farmers and consumers choices.
The general aim of the project is to increase the amount of sustainably-produced food by testing and implementing low-input agricultural practices (LIP) with a positive impact on product quality, by developing non-destructive tools for real-time quality assessment and product discrimination, and by generating new marketing strategies to better support the added value of the products and increase incomes of potential users.
Producing high-quality products represents a key driver in the horticultural sector although the concept of quality has evolved substantially over the past few decades. From traditional attributes (visual and organoleptic) also representing the main focus of most of the quality standards and regulations, more recently other important aspects are gaining relevance: the consolidated consumer attention towards the nutritional value of fresh horticultural products and their increasing sensibility towards the environmental impact of production processes.
The intensive use of natural resources and external inputs for horticulture production is having a considerable impact on the environment. However, the investigation on the environmental and social impact of horticultural production is receiving limited attention compared with other food production. The adoption of LIP, with a proper certification, may thus be considered as a part of the above mentioned broader concept of quality.
On the other side, the higher prices paid for guarantees derived from these labels, as for social certification of sustainable production, increase the risk of frauds. Product authenticity is, in fact, a major concern for both consumers and for processors who are worried about unfair competition in the market (Reid et al., 2006). Thus the need for additional tools to prove the authenticity of the product. Production of vegetable crops under controlled environments (ie greenhouses) has expanded considerably over recent decades in Mediterranean areas (FAO, 2013). Initially, research efforts and the related introduction of technical innovations focused on high-quality, healthy products. However, concern with environmentally-sustainable production has risen in the last decade as industrial greenhouse crops are usually seen as entailing high environmental impact (Torellas et al., 2012). On the other hand, there is also plenty of evidence that greenhouse vegetable production may decrease the environmental impact compared to the field cultivation (Stanghellini, 2014).
Efficient use of resources (water and fertilizers) in irrigated greenhouse agriculture, are promising and increasingly adopted strategies to achieve better crop performance, improved nutritional and sensorial quality (Montesano et al., 2015; Montesano et al., 2018). With respect to traditional systems, soilless cultivation and, particularly, closed-cycle with recycling of nutrient solution (NS) produces a number of benefits, including the possibility to standardize the production process, to improve plant growth and yield, and to obtain higher efficiency in water and nutrient use. Moreover, it is also possible to modulate the regulation of secondary metabolism of plants by optimal control of nutrient solution composition or by imposing controlled stress, and to actuate biofortification processes, generally leading to improved nutritional value of products (Rouphael et al., 2018). Innovative technologies based on the use of sensor networks for fertigation management may considerably reduce water and fertilizers consumption and increase the overall use efficiency of those inputs and may lead to qualitative and quantitative improvements while preventing both under- and over-irrigation. Therefore, a first partial objective of this Project will be to increase the efficiency of water and fertilizers in soilless (with open and closed-cycles with recirculation of nutrients) and soil cultivation in unheated greenhouses in order to reduce the impact on the environment and on the society. Innovative technologies based on the use of sensor networks for fertigation management may considerably reduce water and fertilizers consumption and increase the overall use efficiency of those inputs and may lead to qualitative and quantitative improvements while preventing both under- and over-irrigation. Therefore, a first partial objective of this Project will be to increase the efficiency of water and fertilizers in soilless (with open and closed-cycles with recirculation of nutrients) and soil cultivation in unheated greenhouses in order to reduce the impact on the environment and on the society. Innovative technologies based on the use of sensor networks for fertigation management may considerably reduce water and fertilizers consumption and increase the overall use efficiency of those inputs and may lead to qualitative and quantitative improvements while preventing both under- and over-irrigation. Therefore, a first partial objective of this Project will be to increase the efficiency of water and fertilizers in soilless (with open and closed-cycles with recirculation of nutrients) and soil cultivation in unheated greenhouses in order to reduce the impact on the environment and on the society.
Normally, the most used instrumental techniques to measure quality attributes of fruits and vegetables are destructive and involve a considerable amount of manual work, primarily due to sample preparation. In addition, most of these analytical techniques are time consuming and sometimes may require sophisticated equipments. Finally, they can be performed only on a limited number of specimens, and therefore their statistical relevance may be limited (Amodio et al., 2017a). Research has been focused on developing non-contact, rapid, environmental-friendly and accurate methods for non-invasive evaluation of quality in fruits and vegetables. Nowadays, there are a few emerging non-destructive analytical instruments and approaches for this task, including spectroscopy, hyperspectral imaging and computer vision (Liu et al., 2017).
Near infrared spectroscopy has gained wide attention in the food sector due to its capacity of providing fingerprints of different products on the basis of the interaction between their molecular structure and the incident light (Workman and Shenk, 2004) which is the result of different pre- harvest factors that also affect final composition and quality. The feasibility of NIRS-based analysis to evaluate quality attributes of fresh fruits for commercial application have been reported by numerous authors (Amodio et al., 2017b; Arendse et al., 2018).
Hyperspectral imaging (HSI) combines the principles of spectroscopy and conventional imaging or computer vision. It is mainly used for internal bruise and defect detection in fruits and vegetables (Xing et al. 2005; Ariana et al., 2010) but also to predict internal composition (Piazzolla et al. 2013 and 2017; Yang et al., 2015; Liu et al., 2017). Amodio et al. (2017a) showed the potentiality of hyperspectral imaging in the Vis-NIR spectral range to predict internal content of soluble solids, phenols and antioxidant activity of fennel heads. In addition, this technique provided important information about the maturity of fennel heads. Some studies successfully applied these methods for the discrimination of production origin and agricultural practices. NIR and HSI were in fact used for the classification of apples (Guo et al., 2013), persimmon (Khanmohammadi et al., 2014) and arabica coffee (Bona et al. 2017) from different origins. As for production systems (Sánchez et al., 2013) investigated the potentiality of NIRS technologies to discriminate green asparagus grown under organic and conventional methods. More recently, Amodio et al. (2017c) successfully discriminated conventionally and organically grown strawberries, being also able to identify two different types of organic production systems applied to the same genetic material on the same growing site.
All these studies have suggested multispectral and hyperspectral systems as valid tools to evaluate quality of different agricultural products and, more interestingly, as a potential tool for product authentication.
In addition, Computer Vision Systems (CVS) may be applied to extend quality prediction and discrimination along the whole supply chain from harvesting up to consumers. CVS combines mechanics, optical instrumentation, electromagnetic sensing and digital image processing technology (Patel et al., 2012). Recently, CVSs have been used to assess quality and marketability of tomatoes (Arias et al., 2000), artichokes (Amodio et al., 2011), fresh-cut nectarines (Pace et al., 2011), fresh-cut lettuce ( Pace et al., 2014), fresh-cut radicchio (Pace et al., 2015) and rocket leaves (Cavallo et al., 2017). Moreover, they have been applied for the prediction of internal quality of colored carrots (Pace et al., 2013). Even more interesting is the application of these systems during the post-packaging phase and along the whole distribution chain. Despite the relevance of quality evaluation of packaged products, few investigations were reported in literature. Multi-spectral reflective image analysis has been applied to monitor the evolution and spoilage of leafy spinach covered by plastic materials (Lara et al., 2013); more recently, Cavallo et al. (2018) have proposed an application of image analysis by CVS for non-destructive and contactless evaluation of quality of packaged fresh-cut lettuce. Therefore the interest of investigating the application of CVS to detect quality and shelf-life of packaged products. Cavallo et al. (2018) have proposed an application of image analysis by CVS for non-destructive and contactless evaluation of quality of packaged fresh-cut lettuce. Therefore the interest of investigating the application of CVS to detect quality and shelf-life of packaged products. Cavallo et al. (2018) have proposed an application of image analysis by CVS for non-destructive and contactless evaluation of quality of packaged fresh-cut lettuce. Therefore the interest of investigating the application of CVS to detect quality and shelf-life of packaged products.
Accordingly, a second partial objective of the Project will be to assess the quality of products with conventional and innovative non-destructive approaches, providing innovative tools for discrimination of those obtained by LIP, and for quality prediction of products while in their package.
Finally the possibility of using a non-destructive approach for increasing the information on product history (e.g. growing location and agricultural practice) may be considered as baseline to develop marketing tools to promote the diffusion of sustainable production system. Cost barrier is an obstacle for choosing low input products instead of the conventional, even if environment is mentioned as a strong commitment (Padle and Foster, 2005; Krystallis and Chryssohoidis, 2005). Therefore, as the knowledge about consumer preferences for the adoption of LIP is still matter of debate, a third partial objective of this Project will be to test the hypothesis of the influence of quality certification of LIP practices resulting from ND methods on consumer choices and their willingness to pay, in order to produce adequate and realistic marketing strategies.
Social and economic impacts of the Project are related to the potential reduction of agricultural inputs with increased sustainability of the production and reduced impact for the environment, ensuring high quality crop to the consumer and reducing the food losses. The added information on crop history and the marketing strategies will allow to sustain and diffuse the use of LIP, creating a virtuous mechanism which will positively affect further farmers and consumers choices. Moreover continuous quality monitoring is valuable to enable longer time of transportation, exploiting special environmental conditions (temperature, humidity, modified or controller atmosphere) while checking the state of products, thus reducing food losses. Timely detection of quality changes make possible to reuse products through recycling processes and to reduce waste. Smart shelves can continuously check products and improve their management. Smart refrigerators can extend this check at consumers' home to further prevent losses. Objective non-destructive and contactless quality evaluation can make objective and consistent the quality levels in the expanding online markets of fresh products.
Regarding the scientific impact, the WP1 will provide detailed evidence, supported by scientific data, of the effects of different growing techniques / systems on crop performance and sustainability of production processes in Mediterranean greenhouse conditions. Moreover, a wide range of management strategies, corresponding to different levels of availability of smart tools and competences, will be tested to provide further insight into the effectiveness of new tools. In particular, the project will provide updated data on the water / fertilizers use efficiency related to the case studies analyzed, with reference to the species, the different growing techniques, and the use of smart tools to support decisions. We also expect from the project the definition of cultivation protocols for the two studied species with clear relations between the cultivation management strategies and the impacts on the product measurable quality and the sustainability of the production process. ND methods will enable to discriminate product obtained with LIP on the basis of spectral changes induced, providing useful information on produce quality for the consumer, and at the same time, for the farmers. This will be possible without the need for specific expertise and time consuming laboratory analysis, but by simple locating a fruit close to a sensor. Moreover ND prediction models for the internal quality of rocket and tomato will be provided. The study about ND and contactless CVS based techniques will provide further insights about the color correction process needed to obtain calibrated color images and about the correlation between measurable color characteristics and the quality parameters of interest. The project will identify the relevant colors for correcting the visual appearance of the product: this will provide proper guidelines about the colors to be used to design the graphical elements of the packaging (to avoid the placement of color-chart in the scene) and will develop and tune correction models that will focus on correcting especially the colors that are really present in the product at hand. The combination of these results is expected to enable a reliable and robust quality prediction and discrimination that would be applicable flexibly and extensively from harvest to transportation, during the shelf-life up to the refrigerator of consumers. The possibility to bring quality prediction and discrimination at smartphone level will also be studied. The study will also identify the colors characteristics that are more reliable and informative about the quality and will develop and verify statistical and machine learning methods that best model their functional correlation with the parameters of interest for each considered product.
Finally, results of WP3 will allow identifying the impact on producer income coming from LIP practices and ND technologies. Measuring consumer preferences will depict the impact of the technology on potential marketing and certification strategies. In case the premium price consumers are willing to pay is significantly high, there is room for the technological transfer and the scale up of those LIP practices and ND based certification. Consumer segmentation is going to identify the market niche of consumers that recognize quality throughout the impact of LIP. Investors and producers, therefore, could better target their communication strategies in order to promote their differentiated production based on ND methods certification. Impacts for start-ups and new business are thus expected to be positive as well.
Work Packages
The Project consists of three WPs. The first WP will be aimed to the reduction of the agricultural input in the greenhouses, with the optimization of the use of water and fertilizers in soilless and soil cultivation. For soilless cultivation, open and closed-cycles with recirculation of nutrients will be studied, whereas the use of advanced sensors will allow the reduction of resources, even in open-cycle systems, allowing to control the impact on the environment and the society. WP2 will be dedicated to the quality assessment, and the implementation of new tools to provide information on produce quality and history, with particular focus on discriminating produce obtained with LIP on the basis of spectral information. Non-destructive methods, including NIR, Hyperspectral imaging and digital imaging have been used in some cases for food authentication, showing an interesting potential of application. Conventional attributes assessing maturity index, sensorial and nutritional quality will be also evaluated with the aim of characterizing the quality of the obtained products and to build prediction models based on ND methods to predict internal quality also trough the packaging. For this last activity, in order to extend the consistency of the results, a commercially important fresh-cut fruit (i.e. apple) will be also studied. Finally the WP3 will test the hypothesis of the influence of quality certification of LIP practices resulting from ND methods on consumer choices and their willingness to pay, in order to produce adequate and realistic marketing strategies. Results produced from all WPs will feed Tasks in WP4 ensuring dissemination in different formats and to various targets. Finally, coordination activities, described in WP5, will concern all phases of the Project from its very beginning, ensuring optimal execution, exchange of information and products, and managing contingencies.
Partial and general objectives will be reached through research activities organized in work packages (WP), as following detailed:
Different growing systems and different levels of inputs use (water and fertilizers) will be compared, with a focus on the effects of the different growing conditions on the resources use efficiency and on the product quality. The cultivation under greenhouse will be used as a case study.
WP2: Non destructive quality evaluation (WP Leader: Prof. Maria Luisa Amodio)
Quality of products from WP1 will be evaluated with conventional and non-destructive techniques, with the particular aim of characterizing the fingerprint of low-input produced crop and to evaluate produces quality also through the packaging.
A survey is going to be conducted through questionnaires delivered online. The product concept that optimize the choice and the related consumer segments, based on consumer characteristics, and their willingness to pay are going to be identified and reported. Such a bundle of results will compose the marketing strategy to maximize the sales.
WP4: Dissemination of results
The target of this WP is to disseminate results of the Project to scientific community and to potential users.
WP5: Project coordination
The target of this WP is related to the optimal execution of the Project both from scientific and financial point of view.
The WP1 will aim to define realistic strategies for the rational application of inputs (water and fertilizers) in unheated tunnel conditions, using soil-based and soilless cultivation systems (both open and closed cycles, ie with nutrient solutions recycling), and taking advantage of sensor-based techniques. For rocket, soil-based production will be tested for standard and rational low input practices, and compared with soilless cultivation, while for tomato the focus will be on the optimization of soilless cultivation.
WP2 will be dedicated to the quality assessment. Conventional attributes assessing maturity index, sensorial and nutritional quality attributes will be evaluated. Non-destructive methods (including NIR, Hyperspectral imaging and digital imaging) will be tested to predict internal quality also through the packaging. For this last activity, in order to extend the consistency of the results, a commercially important fresh-cut fruit (ie apple) will also be studied. In addition, the potentiality of non-destructive methods to discriminate among produces of different origins will also be tested, providing a potential new tool to inform the consumers about product quality and history.
WP1 activities are crucial for the project and will cover most part of it. The findings of WP1 will be the basis for the advancements to be obtained in the other project's WPs in innovative instrumental quantification of quality attributes and the identification of proper marketing strategies based on the consumers perception of quality and sustainability.
Since the Project will deal with 2 crops, the SC will be convened at the beginning of the project and before rocket and tomatoes will be available for the other research units working on WP2. This is a very crucial phase of the Project in relation to the needs of raw material and of the need of interaction among Units within each WP. PI and the SC will help to manage this interaction.
Results of WP1 and WP2 will be used for WP3, which will presumably start at the end of the 2nd year and will finish at the end of the Project, and particularly for the second task with will be presumably start around the end of the second year.
Results produced from all WPs will feed Tasks in WP4 ensuring dissemination in different formats and to various targets. WP4 will start as soon as first results will be made available, presumably at the end of first year and will continue until the end of the Project and probably beyond that.
Finally, coordination activities, described in WPE, will concern all phases of the Project from its very beginning, ensuring optimal execution.