A comprehensive review of fruit and vegetable classification techniques

Recent advancements in computer vision have enabled wide-ranging applications in every field of life. One such application area is fresh produce classification, but the classification of fruit and vegetable has proven to be a complex problem and needs to be further developed. Fruit and vegetable classification presents significant challenges due to interclass similarities and irregular intraclass characteristics. Selection of appropriate data acquisition sensors and feature representation approach is also crucial due to the huge diversity of the field. Fruit and vegetable classification methods have been developed for quality assessment and robotic harvesting but the current state-of-the-art has been developed for limited classes and small datasets. The problem is of a multi-dimensional nature and offers significantly hyperdimensional features, which is one of the major challenges with current machine learning approaches. Substantial research has been conducted for the design and analysis of classifiers for hyperdimensional features which require significant computational power to optimise with such features. In recent years numerous machine learning techniques for example, Support Vector Machine (SVM), K-Nearest Neighbour (KNN), Decision Trees, Artificial Neural Networks (ANN) and Convolutional Neural Networks (CNN) have been exploited with many different feature description methods for fruit and vegetable classification in many real-life applications. This paper presents a critical comparison of different state-of-the-art computer vision methods proposed by researchers for classifying fruit and vegetable

UK and EU policy for approval of pesticides suitable for organic systems: Implications for Wales

This study was commissioned by the Welsh Assembly Government (WAG) to review the pesticide approval system in the UK and Europe as far as it affects the use of substances and techniques for crop protection by organic producers in Wales. WAG considers it important that the UK pesticide approval system does not present unnecessary barriers to the development of organic production in Wales. Key Recommendations and scope for further work · WAG should work with the Pesticides Safety Directorate to ensure that the development of pesticide regulatory policy at both National and European level takes full account of the needs of both conventional and organic agriculture and horticulture in the UK. · There is scope for WAG to support the development of a National Pesticide Policy so that regulatory and commercial barriers impeding the development of organic pesticides are minimised. Not only could greater availability of ‘organic pesticides’ have a significant impact on organic production in Wales but there could be important implications for conventional horticulture systems and the use of alternatives to conventional pesticides. · One important regulatory barrier to the registration of ‘organic pesticides’ is the MRL requirement(s) for their approval and this needs to be resolved. Suitable analytical techniques are required to determine firstly whether these substances result in residues, and secondly to identify the breakdown and residue pathways. So far, this issue has not received the attention of any EU Member State. · According to the proposed framework for the 4th Stage Review of EU Pesticides Directive 91/414, notifiers are required to produce a dossier, at their own expense, covering characterisation, human toxicity, ecotoxicity efficacy and other relevant data. The Review includes specific provision for companies notifying the same substance to submit a shared dossier. This will help those businesses (many of which are relatively small companies) to save on the high cost of producing the dossiers. It will also aid the Commission since it will reduce the number of dossiers that have to be considered, and ensure that all the available data is included. WAG should encourage and support the production of collective dossiers; although as yet there is no indication of how this will be done in practice, and further details from the Commission are awaited. · This study has concluded that access to a wider range of ‘organically acceptable pesticides’ would not have a dramatic impact on organic production in Wales. However, in developing an integrated organic policy, WAG should continue to address the pesticides issue. Some of the methods of pest & disease control in organic systems are either physical or multi-cellular e.g. micro-organisms used as biocontrol agents. WAG agri environment policy may provide a vehicle to promote these techniques much more actively. Further, it is important to recognise that while Wales alone is too small to have a major impact on commercial and regulatory pressures, WAG can have an impact by working pro-actively with others to make progress. · There are no published EU or national Member State criteria that can be used to evaluate the acceptability of pesticide substances for organic production. Identifying such criteria and promoting their acceptance at EU level and nationally would allow more active substances to be made available. WAG should work with PSD and others to identify appropriate criteria. · The specific provisions of Article 7 in Annex 2(b) of the Organic Regulation (2092/91) place potential barriers to the adoption of organically acceptable substances for crop protection. There are a number of potentially useful substances currently not included in the Organic Regulation e.g. potassium bicarbonate. WAG should work with PSD and others to identify such substances and support the production of appropriate dossiers. WAG could also encourage further dialogue between the organic sector and Defra to identify amendments in the Organic Regulations to facilitate the inclusion of new pesticides. · Organic pest and disease management is not just a question of inputs but it also relies crucially on advice and extension through initiatives such as Farming Connect and the work of Organic Centre Wales. Long-term commitment to supporting on going advice and extension activities is vital to promote and disseminate best practice in Welsh agriculture and horticulture. · Organic horticulture, vegetable and fruit production systems are particularly sensitive to pest and disease management. Successful control of pests, diseases (and weeds) in these sectors can be critical to the business, and is not assured even when all husbandry and management methods have been effectively applied. Consequently, the use of organically acceptable crop protection methods resulting from future developments (e.g. biopesticides, biological control agents) could have an important role in pest and disease management in these sectors. Both organic and conventional producers in Wales could benefit from having these options available to them and WAG could encourage the adoption of these approaches through appropriate Technology Transfer activities. · The way in which such substances will be regulated at a European level in future is evolving as the review of the Pesticide Directive 91/414 EEC enters the 4th Stage. This stage of the review includes (amongst others) those substances permitted for use in organic production. The guidance documents for the evaluation of applications on plant protection products made from plants or plant extracts and from chemical substances are currently at the draft stage. The response of the Pesticide Safety Directorate and Defra to these developments is not yet clear but this provides an excellent opportunity for WAG to have an input at an early stage in the review process

Computer vision based classification of fruits and vegetables for self-checkout at supermarkets

The field of machine learning, and, in particular, methods to improve the capability of machines to perform a wider variety of generalised tasks are among the most rapidly growing research areas in today’s world. The current applications of machine learning and artificial intelligence can be divided into many significant fields namely computer vision, data sciences, real time analytics and Natural Language Processing (NLP). All these applications are being used to help computer based systems to operate more usefully in everyday contexts. Computer vision research is currently active in a wide range of areas such as the development of autonomous vehicles, object recognition, Content Based Image Retrieval (CBIR), image segmentation and terrestrial analysis from space (i.e. crop estimation). Despite significant prior research, the area of object recognition still has many topics to be explored. This PhD thesis focuses on using advanced machine learning approaches to enable the automated recognition of fresh produce (i.e. fruits and vegetables) at supermarket self-checkouts. This type of complex classification task is one of the most recently emerging applications of advanced computer vision approaches and is a productive research topic in this field due to the limited means of representing the features and machine learning techniques for classification. Fruits and vegetables offer significant inter and intra class variance in weight, shape, size, colour and texture which makes the classification challenging. The applications of effective fruit and vegetable classification have significant importance in daily life e.g. crop estimation, fruit classification, robotic harvesting, fruit quality assessment, etc. One potential application for this fruit and vegetable classification capability is for supermarket self-checkouts. Increasingly, supermarkets are introducing self-checkouts in stores to make the checkout process easier and faster. However, there are a number of challenges with this as all goods cannot readily be sold with packaging and barcodes, for instance loose fresh items (e.g. fruits and vegetables). Adding barcodes to these types of items individually is impractical and pre-packaging limits the freedom of choice when selecting fruits and vegetables and creates additional waste, hence reducing customer satisfaction. The current situation, which relies on customers correctly identifying produce themselves leaves open the potential for incorrect billing either due to inadvertent error, or due to intentional fraudulent misclassification resulting in financial losses for the store. To address this identified problem, the main goals of this PhD work are: (a) exploring the types of visual and non-visual sensors that could be incorporated into a self-checkout system for classification of fruits and vegetables, (b) determining a suitable feature representation method for fresh produce items available at supermarkets, (c) identifying optimal machine learning techniques for classification within this context and (d) evaluating our work relative to the state-of-the-art object classification results presented in the literature. An in-depth analysis of related computer vision literature and techniques is performed to identify and implement the possible solutions. A progressive process distribution approach is used for this project where the task of computer vision based fruit and vegetables classification is divided into pre-processing and classification techniques. Different classification techniques have been implemented and evaluated as possible solution for this problem. Both visual and non-visual features of fruit and vegetables are exploited to perform the classification. Novel classification techniques have been carefully developed to deal with the complex and highly variant physical features of fruit and vegetables while taking advantages of both visual and non-visual features. The capability of classification techniques is tested in individual and ensemble manner to achieved the higher effectiveness. Significant results have been obtained where it can be concluded that the fruit and vegetables classification is complex task with many challenges involved. It is also observed that a larger dataset can better comprehend the complex variant features of fruit and vegetables. Complex multidimensional features can be extracted from the larger datasets to generalise on higher number of classes. However, development of a larger multiclass dataset is an expensive and time consuming process. The effectiveness of classification techniques can be significantly improved by subtracting the background occlusions and complexities. It is also worth mentioning that ensemble of simple and less complicated classification techniques can achieve effective results even if applied to less number of features for smaller number of classes. The combination of visual and nonvisual features can reduce the struggle of a classification technique to deal with higher number of classes with similar physical features. Classification of fruit and vegetables with similar physical features (i.e. colour and texture) needs careful estimation and hyper-dimensional embedding of visual features. Implementing rigorous classification penalties as loss function can achieve this goal at the cost of time and computational requirements. There is a significant need to develop larger datasets for different fruit and vegetables related computer vision applications. Considering more sophisticated loss function penalties and discriminative hyper-dimensional features embedding techniques can significantly improve the effectiveness of the classification techniques for the fruit and vegetables applications

'Mediterranean' dietary pattern for the primary prevention of cardiovascular disease

It is well established that diet plays a major role in cardiovascular disease risk. The traditional Mediterranean dietary pattern is of particular interest because of observations from the 1960s that populations in countries of the Mediterranean region, such as Greece and Italy, had lower mortality from cardiovascular disease compared with northern European populations or the US, probably as a result of different eating habits. This review assessed the effects of providing dietary advice to follow a Mediterranean-style dietary pattern to healthy adults or people at increased risk of cardiovascular disease in order to prevent the occurrence of cardiovascular disease and reduce the risk factors associated with it. Definitions of a Mediterranean dietary pattern vary and we included only randomised controlled trials (RCTs) of interventions that reported at least two of the following components: (1) high monounsaturated/saturated fat ratio, (2) low to moderate red wine consumption, (3) high consumption of legumes, (4) high consumption of grains and cereals, (5) high consumption of fruits and vegetables, (6) low consumption of meat and meat products and increased consumption of fish, and (7) moderate consumption of milk and dairy products. The control group was no intervention or minimal intervention. We found 11 RCTs (15 papers) that met these criteria. The trials varied enormously in the participants recruited and the different dietary interventions. Four trials were conducted in women only, two trials were in men only and the remaining five were in both men and women. Five trials were conducted in healthy individuals and six trials were in people at increased risk of cardiovascular disease or cancer. The number of components relevant to a Mediterranean dietary pattern ranged from two to five and only seven trials described the intervention as a Mediterranean diet. The largest trial, which recruited only postmenopausal women and was not described as a Mediterranean diet meeting only two of the criteria described above, reported no difference in the occurrence of cardiovascular disease between the dietary advice group and the control group. The other trials measured risk factors for cardiovascular disease. As the studies were so different, it was not possible to combine studies for most of the outcomes. Where it was possible to combine studies, we found small reductions in total cholesterol levels as well as in the harmful low-density lipoprotein (LDL) cholesterol concentrations. The reductions in total cholesterol were greater in the studies that described themselves as providing a Mediterranean diet. None of the trials reported side effects. The review concludes that, from the limited evidence to date, a Mediterranean dietary pattern reduces some cardiovascular risk factors. However, more trials are needed to look at the effects of the different participants recruited and the different dietary interventions to see which interventions might work best in different populations

Plant cell walls: impact on nutrient bioaccessibility and digestibility

Cell walls are important structural components of plants, affecting both the bioaccessibility and subsequent digestibility of the nutrients that plant-based foods contain. These supramolecular structures are composed of complex heterogeneous networks primarily consisting of cellulose, and hemicellulosic and pectic polysaccharides. The composition and organization of these different polysaccharides vary depending on the type of plant tissue, imparting them with specific physicochemical properties. These properties dictate how the cell walls behave in the human gastrointestinal tract, and how amenable they are to digestion, thereby modulating nutrient release from the plant tissue. This short narrative review presents an overview of our current knowledge on cell walls and how they impact nutrient bioaccessibility and digestibility. Some of the most relevant methods currently used to characterize the food matrix and the cell walls are also described

An evaluation of the environmental care orientation of deciduous fruit producers in the Western Cape

A classification system developed to evaluate the environmental care orientation of companies and, more specifically, their strategies to deal with the environmental care requirements prescribed by the market was applied to the deciduous fruit sector in the Western Cape. A survey was done to determine the attitude towards and status of, environmental care activities amongst deciduous fruit producers who have already obtained Eurepgap certification or who are busy preparing for the certification audit. A questionnaire was used and the responses were judged in terms of the guidelines of the classification system. The nature of the typical South African - European deciduous fruit export supply chain is that South African producers desire to supply the retail market at higher prices than that of the wholesale market. The producers are then confronted with the stringent environmental care requirements of the retail chains, who use the environmental care product image aggressively as a selling point in the retail market, acting like typical Class III market oriented institutions. The classification shows that the majority of producers try to comply with these requirements with minimum effort (Class I). The more progressive producers accept them as good agricultural practices to increase their production efficiency. (Class II). Some farmers participate in a comprehensive Integrated Crop Management (ICM) system to establish a culture of environmental care at farm level in a more efficient way. ICM implementation also helps to prepare proactively for possible changes in the environmental care requirements of individual retail chains. This seems to be the more effective strategy for the primary producer.Crop Production/Industries, Environmental Economics and Policy,

Evaluation of quality parameters of apple juices using near-infrared spectroscopy and chemometrics

Near-infrared (NIR) spectra were recorded for commercial apple juices. Analysis of these spectra using partial least squares (PLS) regression revealed quantitative relations between the spectra and quality- and taste-related properties of juices: soluble solids content (SSC), titratable acidity (TA), and the ratio of soluble solids content to titratable acidity (SSC/TA). Various spectral preprocessing methods were used for model optimization. The optimal spectral variables were chosen using the jack-knife-based method and different variants of the interval PLS (iPLS) method. The models were cross-validated and evaluated based on the determination coefficients (R-2), root-mean-square error of cross-validation (RMSECV), and relative error (RE). The best model for the prediction of SSC (R-2 = 0.881, RMSECV = 0.277 degrees Brix, and RE = 2.37%) was obtained for the first-derivative preprocessed spectra and jack-knife variable selection. The optimal model for TA (R-2 = 0.761, RMSECV = 0.239 g/L, and RE = 4.55%) was obtained for smoothed spectra in the range of 6224-5350 cm(-1). The best model for the SSC/TA (R-2 = 0.843, RMSECV = 0.113, and RE = 5.04%) was obtained for the spectra without preprocessing in the range of 6224-5350 cm(-1). The present results show the potential of the NIR spectroscopy for screening the important quality parameters of apple juices.National Science Centre, Poland [2016/23/B/NZ9/03591

Agro-based industry of Tharparkar and barrage area of Sindh: Solutions and suggested policy

In this study solutions and suggested policy of agro-based industry of Tharparkar and barrage area of Sindh are given, and it is tenth chapter of the Ph.D submitted in 2002. Purpose of the study was to give the complete picture of solutions and recommendations. On the completion of this study and in the light of conclusions drawn it has been observed that to further develop agro-based industries in Thar and Barrage areas, it is necessary for the Government of Sindh to take steps for local organization and indigenous knowledge and leadership. The awareness of rangeland and livestock by the local organizations will help in the enhancement of all other agro-based industries. The development of agro-based industries in Thar will boost Sindh’s industrial economy. In order to alleviate poverty, it is also necessary that people be trained in the ways and means to develop their physical assets (land and livestock). In this way poverty will fall about 55 percent. For the development of Thar’s agro-based industries two formulas are suggested as bellow: A. Alleviation of poverty = Local Organizations + Livestock; B. Development of Thar = Local Organizations + Livestock + Roads + Electricity. For the achievement of purpose Proposed Immediate Measures, Medium and Long Term Measures should be taken.Solutions and Suggested Policy; Tharparkar; Barrage Area of Sindh; Agro-Based Industry; livestock

SUPPLY CHAIN MANAGEMENT IN THE FRESH PRODUCE INDUSTRY: A MILE TO GO?

We investigate the factors that influence vertical coordination in the fresh produce industry. Elaborating on the concept of governance structure, price and non-price coordination systems will be distinguished. Under previous research, there is a specific consideration as to how market conditions and institutional considerations influence the coordination of supply chains. In my presentation for the Food Distribution Research Society in Monterey, California, I analyzed how retail companies in the United States, France, and the Netherlands coordinate their supply chains of fruits and vegetables. Differences in product category and institutional environments do not contribute directly to the explanation of differences found in supply chain coordination systems. Industry-specific factors and firm-resource-based factors may supply a better understanding of these differences.Agribusiness,