Dataset Information

An extensive dataset for successful recognition of fresh and rotten fruits.

ABSTRACT: Detection of rotten fruits is very crucial for agricultural productions and fruit processing as well as packaging industries. Usually, the detection of fresh and rotten fruits is done manually which is an ineffective and lengthy process for farmers. For this reason, the development of a new classification model is required which will reduce human effort, cost, and production time in the agriculture industry by recognizing defects in the fruits. This article offers a major dataset to the researchers to develop effective algorithms for recognizing more variety of fruits and overcome the limitations by increasing accuracy as well as decreasing computation time. This dataset contains sixteen types of fruit classes, namely fresh grape, rotten grape, fresh guava, rotten guava, fresh jujube, rotten jujube, fresh pomegranate, rotten pomegranate, fresh strawberry, rotten strawberry, fresh apple, rotten apple, fresh banana, rotten banana, fresh orange, rotten orange. We collected various fresh and rotten fruit images from 16th to 31st March 2022 from different fruit shops and real fields with the help of a domain specialist from an agricultural organization. The dataset is hosted by the Department of Computer Science and Engineering, Jahangirnagar University, and is freely available at https://data.mendeley.com/datasets/bdd69gyhv8/1.

SUBMITTER: Sultana N

PROVIDER: S-EPMC9469664 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature

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An extensive dataset for successful recognition of fresh and rotten fruits.

Sultana Nusrat N Jahan Musfika M Uddin Mohammad Shorif MS

Data in brief 20220824

Detection of rotten fruits is very crucial for agricultural productions and fruit processing as well as packaging industries. Usually, the detection of fresh and rotten fruits is done manually which is an ineffective and lengthy process for farmers. For this reason, the development of a new classification model is required which will reduce human effort, cost, and production time in the agriculture industry by recognizing defects in the fruits. This article offers a major dataset to the research ...[more]

PMID: 36111284

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Project description:The extension of commercial life and the reduction of postharvest losses of perishable fruits is mainly based on storage at low temperatures alone or in combination with modified atmospheres (MAs) and controlled atmospheres (CAs), directed primarily at reducing their overall metabolism thus delaying ripening and senescence. Fruits react to postharvest conditions with desirable changes if appropriate protocols are applied, but otherwise can develop negative and unacceptable traits due to the onset of physiological disorders. Extended cold storage periods and/or inappropriate temperatures can result in development of chilling injuries (CIs). The etiology, incidence, and severity of such symptoms vary even within cultivars of the same species, indicating the genotype significance. Carbohydrates and amino acids have protective/regulating roles in CI development. MA/CA storage protocols involve storage under hypoxic conditions and high carbon dioxide concentrations that can maximize quality over extended storage periods but are also affected by the cultivar, exposure time, and storage temperatures. Pyruvate metabolism is highly reactive to changes in oxygen concentration and is greatly affected by the shift from aerobic to anaerobic metabolism. Ethylene-induced changes in fruits can also have deleterious effects under cold storage and MA/CA conditions, affecting susceptibility to chilling and carbon dioxide injuries. The availability of the inhibitor of ethylene perception 1-methylcyclopropene (1-MCP) has not only resulted in development of a new technology but has also been used to increase understanding of the role of ethylene in ripening of both non-climacteric and climacteric fruits. Temperature, MA/CA, and 1-MCP alter fruit physiology and biochemistry, resulting in compositional changes in carbon- and nitrogen-related metabolisms and compounds. Successful application of these storage technologies to fruits must consider their effects on the metabolism of carbohydrates, organic acids, amino acids and lipids.

Project description:Fresh fruits and vegetables can harbor large and diverse populations of bacteria. However, most of the work on produce-associated bacteria has focused on a relatively small number of pathogenic bacteria and, as a result, we know far less about the overall diversity and composition of those bacterial communities found on produce and how the structure of these communities varies across produce types. Moreover, we lack a comprehensive view of the potential effects of differing farming practices on the bacterial communities to which consumers are exposed. We addressed these knowledge gaps by assessing bacterial community structure on conventional and organic analogs of eleven store-bought produce types using a culture-independent approach, 16 S rRNA gene pyrosequencing. Our results demonstrated that the fruits and vegetables harbored diverse bacterial communities, and the communities on each produce type were significantly distinct from one another. However, certain produce types (i.e., sprouts, spinach, lettuce, tomatoes, peppers, and strawberries) tended to share more similar communities as they all had high relative abundances of taxa belonging to the family Enterobacteriaceae when compared to the other produce types (i.e., apples, peaches, grapes, and mushrooms) which were dominated by taxa belonging to the Actinobacteria, Bacteroidetes, Firmicutes, and Proteobacteria phyla. Although potentially driven by factors other than farming practice, we also observed significant differences in community composition between conventional and organic analogs within produce types. These differences were often attributable to distinctions in the relative abundances of Enterobacteriaceae taxa, which were generally less abundant in organically-grown produce. Taken together, our results suggest that humans are exposed to substantially different bacteria depending on the types of fresh produce they consume with differences between conventionally and organically farmed varieties contributing to this variation.

Project description:BACKGROUND:Toxoplasma gondii is the third most important contributor to health burden caused by food-borne illness. Ingestion of tissue cysts from undercooked meat is an important source of horizontal transmission to humans. However, there is an increasing awareness of the consumption of fresh fruit and vegetables, as a possible source for oocyst transmission, since this stage of the parasite can persist and remain infective in soil and water for long time. Herein, we outline findings related with detection of T. gondii oocysts in vegetables and berry fruits, which are usually raw consumed. The procedure includes the estimation of the number of oocysts. METHODS:Food samples were collected from local producers and supermarket suppliers. Toxoplasma gondii oocysts were concentrated after washing the samples by applying high resolution water filtration and immunomagnetic separation (method 1623.1: EPA 816-R-12-001-Jan 2012), in order to (i) remove potential Cryptosporidium spp. oocysts and Giardia spp. cysts present in the samples; and (ii) select T. gondii oocysts. Toxoplasma gondii oocyst detection and an estimation of their numbers was performed by conventional PCR and real time qPCR, using specific primers for a 183-bp sequence of the T. gondii repetitive DNA region. All PCR-positive DNA samples were purified and sequenced. Restriction enzyme digestion with EcoRV endonuclease confirmed the presence of the T. gondii DNA fragment. In addition, the presence of the parasite was observed by fluorescent microscopy, taking advantage of the oocysts autofluorescence under UV light. RESULTS:Forty percent of the analysed samples (95% CI: 25.5-56.5%) presented the expected PCR and digested DNA fragments. These fragments were confirmed by sequencing. Microscopic autofluorescence supported the presence of T. gondii-like oocysts. The estimated mean (± SE) oocyst concentration was 23.5 ± 12.1 oocysts/g, with a range of 0.6-179.9 oocysts/g. CONCLUSIONS:Our findings provide relevant evidence of contamination of fresh vegetables and berry fruits with T. gondii oocysts.

Dataset Information

An extensive dataset for successful recognition of fresh and rotten fruits.

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An extensive dataset for successful recognition of fresh and rotten fruits.

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