Importance of Machine Vision Framework with Nondestructive Approach for Fruit Classification and Grading: A Review

Machine vision technology has gained significant importance in the agricultural industry, particularly in the non-destructive classification and grading of fruits. This paper presents a comprehensive review of the existing literature, highlighting the crucial role of machine vision in automating the fruit quality assessment process. The study encompasses various aspects, including image acquisition techniques, feature extraction methods, and classification algorithms. The analysis reveals the substantial progress made in the field, such as developing sophisticated hardware and software solutions, which have improved accuracy and efficiency in fruit grading. Furthermore, it discusses the challenges and limitations, such as dealing with variability in fruit appearance, handling different fruit types, and real-time processing. The identification of future research needs emphasizes the potential for enhancing machine vision frameworks through the integration of advanced technologies like deep learning and artificial intelligence.Additionally, it underscores the importance of addressing the specific needs of different fruit varieties and exploring the applicability of machine vision in real-world scenarios, such as fruit packaging and logistics. This review underscores the critical role of machine vision in non-destructive fruit classification and grading, with numerous opportunities for further research and innovation. As the agricultural industry continues to evolve, integrating machine vision technologies will be instrumental in improving fruit quality assessment, reducing food waste, and enhancing the overall efficiency of fruit processing and distribution

Innovations in non-destructive techniques for fruit quality control applied to manipulation and inspection lines

Tesis por compendioLa industria alimentaria, concretamente el sector poscosecha, necesita innovar en sus procesos productivos, optimizando los mismos para rentabilizar sus actividades, garantizando productos de calidad capaces de satisfacer las necesidades de los consumidores. La presente tesis doctoral se centra en evaluar el potencial de la espectroscopia VIS-NIR para la caracterización e inspección de la calidad de la fruta tanto fuera de línea como a tiempo real en procesos automatizados. En un primer lugar, la viabilidad de la técnica se estudió a nivel de laboratorio en estado estático (off-line), con el fin de conocer y optimizar las condiciones de medición. Posteriormente, se evaluó la calidad interna y externa de diferentes tipos de frutas como son caqui, nectarina y mango. En una segunda etapa, se llevó a cabo una automatización de los procesos de inspección mediante el desarrollo de nuevos prototipos in-line. Para este propósito, y con el objetivo de completar y corroborar los resultados obtenidos de manera estática, se estudió la integración de dos sondas VIS-NIR en una garra robótica capaz de manipular mangos. Finalmente, se estudió la integración de una sonda VIS-NIR a una cinta transportadora. Los resultados obtenidos a nivel estático han demostrado que la espectroscopia VIS-NIR es un método no destructivo muy prometedor para predecir la astringencia en caqui. Así mismo, ha demostrado ser una adecuada herramienta para clasificar al 100% entre variedades de nectarinas como "Big Top" y "Diamond Ray" con una apariencia externa e interna muy similar, pero con diferentes propiedades organolépticas. De manera similar, fue posible clasificar al 100% variedades como "Big Top" y "Magique" de apariencia externa y composición similar pero distinto color de pulpa., y además se desarrolló un índice de calidad interna (IQI) para evaluar la calidad de las nectarinas. Por lo que respecta a los trabajos off-line realizados con mangos de la variedad "Osteen", fue posible predecir su calidad interna mediante los índices de madurez (RPI) y de calidad (IQI) con un gran rendimiento. A su vez, los ensayos experimentales efectuados con estos mismos mangos bajo la manipulación no destructiva de una garra robótica, demostraron que los mejores modelos eran capaces de predecir tanto la firmeza mecánica, el contenido en sólidos solubles, la luminosidad de la pulpa, así como el índice RPI de las muestras en base a la información obtenida por los acelerómetros instalados en los dedos de la garra robótica. En cuanto a los ensayos realizados de manera in-line, el primer prototipo desarrollado se basó en la integración de dos sondas VIS-NIR en una garra robótica dispuesta con dos acelerómetros. El sistema desarrollado permitió alcanzar una buena estimación de la calidad del mango a través del índice RPI fusionando la información tanto de los espectros VIS-NIR como del impacto no destructivo de los acelerómetros. De este modo quedó demostrado que era posible obtener una predicción similar trabajando de forma in-line como trabajando de manera off-line para la predicción del mismo índice de calidad en mangos. El segundo prototipo in-line desarrollado se basa en la integración de una sonda VIS-NIR en una cinta transportadora para la identificación de distintas variedades y orígenes de manzanas. El prototipo desarrollado permitió registrar resultados de clasificación tan buenos como los efectuados de manera off-line con, por ejemplo, nectarina. De este modo, se puede concluir que la espectroscopia VIS-NIR permite monitorear la calidad y clasificar fruta poscosecha tanto en modo off-line como in-line. Los nuevos prototipos desarrollados aportan claras ventajas respecto a los procesos tradicionales realizados a mano, como son la reducción del tiempo de inspección, la disminución de la cantidad de residuos generados y la posibilidad de inspeccionar toda la producción, obteniendo así un análisis más estandarizThe food industry, concretely the post-harvest sector, needs to innovate in their production processes, optimizing them to make their activities profitable, guaranteeing quality products capable of satisfying the needs of consumers. The present doctoral thesis focuses on evaluating the potential of visible and near infrared spectroscopy (VIS-NIR) for the characterization and inspection of fruit quality both off-line and in real time in automated processes. Firstly, the viability of the technique was studied at the laboratory level in a static mode (off-line), in order to know and optimise the measurement conditions. Subsequently, the internal and external quality of different types of fruits such as persimmon, nectarine and mango were evaluated. Secondly, an automation of the inspection processes was carried out through the development of new in-line prototypes. For this purpose, and with the aim of completing and corroborating the results obtained in a static mode, the integration of two VIS-NIR probes in a robotic gripper capable of manipulating mangoes was studied. Finally, the integration of a VIS-NIR probe to a conveyor belt was studied as an in-line monitoring tool on the inspection process of different apple varieties. The results obtained in static mode have shown that VIS-NIR spectroscopy is a very promising non-destructive method to predict the astringency in persimmon. Likewise, it has demonstrated to be an adequate tool to classify 100% between nectarine varieties such as 'Big Top' and 'Diamond Ray' with very similar external and internal appearance, but with different organoleptic properties. Similarly, it was possible to classify 100% varieties such as 'Big Top' and 'Magique' with external appearance and similar composition but different pulp colour. An internal quality index (IQI) was developed to evaluate the quality of nectarines, which can be predicted through VIS-NIR spectroscopy. Regarding the off-line work carried out with mangoes of 'Osteen' variety, it was possible to predict its internal quality through the indexes of maturity (RPI) and quality (IQI) with a high performance. Moreover, the experimental tests carried out with these same mangoes under the non-destructive manipulation of a robotic gripper, showed that the best models were able to predict both the mechanical firmness, the soluble solids content, the brightness of the pulp, as well as the RPI index of the samples based on the information obtained by the accelerometers installed on the fingers of the robotic gripper. Regarding the tests carried out in an in-line mode, the first developed prototype was based on the integration of two VIS-NIR probes in a robotic gripper fitted with two accelerometers. The developed system allowed reaching a good estimation of mango quality through the RPI index. In this way, it was demonstrated that it was possible to obtain a similar prediction working in-line as off-line mode for the prediction of the same quality index in mangoes. The second developed in-line prototype is based on the integration of a VIS-NIR probe in a conveyor belt for the identification of different varieties and origins of apples, achieving a success rate of 98% with the system. The developed prototype allowed to register classification results as good as those carried out off-line with, for example, nectarine. In this way, it can be concluded that VIS-NIR spectroscopy allows monitoring the quality and classifying post-harvest fruit in both off-line and in-line mode, being a tool that allows improving and guaranteeing the correct quality and food safety. The new developed prototypes provide clear advantages over the traditional processes performed by hand, such as the reduction of inspection time, the reduction of the amount of waste generated by destructive quality analysis and the possibility of inspecting full production, obtaining a more standardised analysis of the quality of the products.La indústria alimentària, concretament el sector postcollita, necessita innovar en els seus processos productius, optimitzant els mateixos per a rendibilitzar les seues activitats, garantint productes de qualitat capaços de satisfer les necessitats dels consumidors. La present tesi doctoral es centra en avaluar el potencial de l'espectroscòpia visible i infraroig pròxim (VIS-NIR) per a la caracterització i la inspecció de la qualitat de la fruita tant fora de línia com a temps real en processos automatitzats. En un primer lloc, la viabilitat de la tècnica es va estudiar a nivell de laboratori en estat estàtic (off-line), a fi de conéixer i optimitzar les condicions de mesurament. Posteriorment, es va avaluar la qualitat interna i externa de diferents tipus de fruites com són caqui, nectarina i mango. En una segona etapa, es va dur a terme una automatització dels processos d'inspecció per mitjà del desenvolupament de nous prototips in-line. Per aquest propòsit, i amb l'objectiu de completar i corroborar els resultats obtinguts de manera estàtica, es va estudiar la integració de dos sondes VIS-NIR en una garra robòtica capaç de manipular. Finalment, es va estudiar la integració d'una sonda VIS-NIR a una cinta transportadora. Els resultats obtinguts a nivell estàtic han demostrat que l'espectroscòpia VIS-NIR és un mètode no destructiu molt prometedor per a predir l'astringència en caqui. Així mateix, ha demostrat ser una adequada ferramenta per a classificar al 100% entre varietats de nectarines com "Big Top" i "Diamond Ray" amb una aparença externa i interna molt semblant, però amb diferents propietats organolèptiques. De manera semblant, va ser possible classificar al 100% varietats com "Big Top" i "Magique" d'aparença externa i composició semblant però distint color de polpa. Es va desenvolupar un índex de qualitat interna (IQI) per avaluar la qualitat de les nectarines. Pel que fa als treballs off-line realitzats amb mangos de la varietat "Osteen" va ser possible predir la seua qualitat interna mitjançant els índexs de maduresa (RPI) i de qualitat (IQI) amb un gran rendiment. Al mateix temps, els assajos experimentals efectuats amb estos mateixos mangos baix la manipulació no destructiva d'una garra robòtica, van demostrar que els millors models eren capaços de predir tant la fermesa mecánica, el contingut en sòlids solubles, la lluminositat de la polpa, així com l'índex RPI de les mostres basant-se en l'informació obtinguda pels acceleròmetres instal¿lats en els dits de la garra robòtica. En quant als assajos realitzats de manera in-line, el primer prototip desenvolupat es va basar en la integració de dos sondes VIS-NIR en una garra robòtica disposada amb dos acceleròmetres. El sistema desenvolupat va permetre aconseguir una bona estimació de la qualitat del mango a través de l'índex RPI fusionant l'informació tant dels espectres VIS-NIR com de l'impacte no destructiu dels acceleròmetres. D'esta manera va quedar demostrat que era possible obtindre una predicció semblant treballant de forma in-line com off-line per a la predicció del mateix índex de qualitat en mangos. El segon prototip in-line desenvolupat es va basar en la integració d'una sonda VIS-NIR en una cinta transportadora per a l'identificació de distintes varietats i orígens de pomes. El prototip desenvolupat va permetre registrar resultats de classificació tan bons com els efectuats de manera off-line. D'aquesta manera, es pot concloure que l'espectroscòpia VIS-NIR permet monitorar la qualitat i classificar fruita postcollita tant en mode off-line com in-line. Els nous prototips desenvolupats aporten clars avantatges respecte als processos tradicionals realitzats a mà, com són la reducció del temps d'inspecció, la disminució de la quantitat de residus generats pels anàlisis destructives de qualitat i la possibilitat d'inspeccionar tota la producció, obtenint així un anàlisi més estandarditzCortés López, V. (2018). Innovations in non-destructive techniques for fruit quality control applied to manipulation and inspection lines [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/110969TESISCompendi

Hormonal regulation of mango fruit ripening

Mango fruit ripen quickly. It is highly perishable. Short shelf life of mango fruit limits its transportation to distant domestic and international markets. The objective of my research was to elucidate the role of changes in endogenous levels of brassinosteroids (BRs), ethylene, abscisic acid (ABA) and/or indole-3-acetic acid (IAA) in modulating the ripening processes of 'Kensington Pride' mango fruit. The endogenous levels of these regulators were regulated using inhibitors of their biosynthesis and/or action to unfold their mechanism in delaying/hastening mango fruit ripening, extending storage life and improving fruit quality as well as to underpin the mode of action of ABA and NO in modulating ethylene biosynthesis and activities of fruit softening enzymes in the pulp during ripening and/or alleviating chilling injury (CI) during cool storage.Higher endogenous level of ABA at the climacteric-rise stage triggered the climacteric peak of ethylene production coupled with a significant quadratic relationship between both of them; suggest that ABA play a key role in modulating mango fruit ripening. The exogenous application of ABA (1.0 - 2.0 mM) promoted skin colour development and fruit softening during ripening, and the trend was reversed with its inhibitor of biosynthesis - nordihydroguaiaretic acid (0.1 - 0.2 mM NDGA). The endogenous level of IAA was higher at the initial stage of ripening and decline over ripening period. The exogenous application of 45 - 60 ng g-1 FW Epi- BL increased the climacteric peak of ethylene and respiration, promoted skin colour, but the changes in the endogenous level of BRs (castasterone and brassinolide) are unlikely to modulate mango fruit ripening as it is present in a trace amounts in mango pulp tissues throughout the ripening period.Exogenous postharvest application of ABA (1.0 mM) increased the climacteric peak of ethylene production through promoting the activities of 1- aminocyclopropane-1-carboxylic acid (ACC) synthase (ACS), ACC oxidase (ACO) enzymes, and ACC content, decreased the fruit firmness with increased exopolygalacturonase (exo-PG), endo-PG and endo-1,4-_-D-glucanase (EGase) activities, decreased pectinesterase (PE) activity in the pulp, higher total sugars and sucrose, advanced degradation of total organic acids, citric and fumaric acid. The application of 0.2 mM NDGA showed reverse trends for these ripening indicator parameters.NO fumigation (20 μL L-1 or 40 μL L-1) was more effective in delaying fruit ripening when applied at the pre-climacteric (PC) stage, than at the climacteric-rise (CR) stage. NO (20 μL L-1) fumigation delayed and suppressed the endogenous ethylene production, activities of ACS and ACO enzymes, and ACC content, rate of respiration, higher pulp rheological properties (firmness, springiness, cohesiveness, chewiness, adhesiveness, and stiffness) with lower activities of exo-, endo-PG, EGase, but maintained higher PE activity in pulp tissues during ripening at 21°C and cool storage (13°C). NO treatments (20 and 40 μL L-1) significantly alleviated CI index during ripening at ambient temperature following 2- or 4-week of cold-stored (5°C) period. All NO fumigation treatments significantly suppressed ethylene production and respiration rates irrespective of cold storage period. NO–fumigated with above 5 μL L-1 significantly delayed fruit softening up to 2 days and retarded colour development, reduced total sugar and fructose concentrations, increased tartaric and shikimic acid at fully ripe stage during ripening period irrespective of cold-stored fruit.In conclusion, the higher levels of endogenous IAA in fruit pulp during the PC stage and the accumulation of ABA prior to the climacteric stage might switch on ethylene production that triggers fruit ripening. There is a significant quadratic relationship between endogenous level of ABA in the pulp and ethylene production during fruit ripening period. Exogenous Epi-BL promoted fruit ripening, whilst, the changes in endogenous levels of BRs are unlikely to modulate mango fruit ripening. Moreover, the exogenous application of ABA (1.0 mM) promoted the activities of ethylene biosynthesis enzymes (ACS and ACO) and ACC content and ethylene biosynthesis as well as endo-PG activity in the pulp, whilst, the NDGA-treated fruit showed the reverse trends. The application of NO fumigation (20 L L-1) at PC stage can be effectively used to delay the fruit ripening up to 2 days at ambient temperature (21°C) and cool-storage (13°C) through suppression the activity of ethylene biosynthesis and softening enzymes and alleviate CI following 2- and 4-week cold storage (5°C) without any adverse effects on fruit quality

Sustainable Land Use and Rural Development in Southeast Asia: Innovations and Policies for Mountainous Areas

Sustainable Development; Landscape/Regional and Urban Planning; Agricultur

Modulation of fruit ripening, storage time and quality of fruits with emulsion of Chitosan alone and loaded with Salicylic acid or Oxalic acid

Efficacy of chitosan emulsion, salicylic acid (SA) or oxalic acid (OA) alone and chitosan loaded with SA or OA on ethylene production, extending storage life and maintenance of climacteric (nectarine and plum) and non-climacteric fruit (sweet orange) quality at ambient temperature and cold conditions was investigated. Beneficial effects of these coating treatments in regulating ethylene production, fruit softening, reducing weight loss and diseases and quality parameters varied between climacteric and non-climacteric fruits, cultivars and storage conditions

Radial Basis Function Neural Network in Identifying The Types of Mangoes

Mango (Mangifera Indica L) is part of a fruit plant species that have different color and texture characteristics to indicate its type. The identification of the types of mangoes uses the manual method through direct visual observation of mangoes to be classified. At the same time, the more subjective way humans work causes differences in their determination. Therefore in the use of information technology, it is possible to classify mangoes based on their texture using a computerized system. In its completion, the acquisition process is using the camera as an image processing instrument of the recorded images. To determine the pattern of mango data taken from several samples of texture features using Gabor filters from various types of mangoes and the value of the feature extraction results through artificial neural networks (ANN). Using the Radial Base Function method, which produces weight values, is then used as a process for classifying types of mangoes. The accuracy of the test results obtained from the use of extraction methods and existing learning methods is 100%

Sausages: Nutrition, Safety, Processing and Quality Improvement

Sausages are privileged foods due to their diversity, nutritional value, deep roots in the culture of the peoples and economic importance. In order to increase the knowledge and to improve the quality and safety of these foods, an intense research activity was developed from the early decades of the past century. This book includes ten research works and a review showing important and interesting advances and new approaches in most of the research topics related to sausages. After an editorial of the Editor reflecting the aims and contents of the book, the initial five chapters deal with microbiological issues of the sausage manufacture (characterization and study of the bacterial communities of sausages, study of the metabolism and the technological and safety characteristics of concrete microbial strains, and use of starter cultures to improve the sausage quality). Chemical hazards also receive some attention in this book with a chapter on the optimization of the smoking process of traditional dry-cured meat products to minimize the presence of PAHs. The partial or total replacement of the traditional ingredients in sausages with unconventional raw materials for the obtaining of novel and varied products are the subject of three chapters. Next, a chapter is dedicated to another interesting topic, the search and the essay of natural substitutes for synthetic additives due to the increasing interest of consumers in healthier meat products. The book ends with an interesting review on the safety, quality and analytical authentication of halāl meat products, with particular emphasis on salami