Detection of Adenovirus in Fresh Fruit, Vegetables, Wastewater and Manure from Irrigated Farms in Ouagadougou, Burkina Faso

Enteric viral pathogens are responsible for numerous epidemics associated with the consumption of fresh fruit and vegetable, whether raw or minimally processed. The aim of the present study was to assess agricultural practices and the presence of adenovirus (AdV) in fruits and vegetables, manure and irrigation wastewater sampled in the urban and peri-urban perimeters of Ouagadougou. A total of 286 samples including 30 lettuces, 42 tomatoes, 30 carrots, 30 strawberries, 74 manures and 80 wastewater samples were collected from four market garden sites in and around Ouagadougou. Nested PCR was performed with specific primers to detect adenoviruses (AdVs). A face-to-face survey was carried out using a questionnaire on market garden production practices. Overall, adenoviruses prevalence was 5.9% [IC95, 3.2% - 8.7%] in all samples analyzed. It was specifically 7.14% (3/42) from tomatoes, 6.7% (2/30) from lettuces, 20% (6/30) on strawberries and 7.5% (6/80) in irrigation water. The survey showed that irrigation water came from untreated sources (dam, well, canal) and then 52% of farms used untreated manure. No farms have implemented measures to limit access by domestic and wild animals. This work shows the presence of human adenoviruses in surface irrigation water and fresh produce, which is of concern when fresh produce is consumed raw. To reduce the public health risks associated with consuming these foods, it is essential to follow good hygiene and cultivation practices.

Optimizing Household Wastes (Rice, Vegetables, and Fruit) as an Environmentally Friendly Electricity Generator

The high consumption of electricity and issues related to fossil energy have triggered an increase in energy prices and the scarcity of fossil resources.Consequently,many researchers are seeking alternative energy sources.One potential technology,the Microbial Fuel Cell(MFC)based on rice,vegetable,and fruit wastes,can convert chemical energy into electrical energy.This study aims to determine the potency of rice,vegetable,and fruit waste assisted by Cu/Mg electrodes as a generator of electricity.The method used was a laboratory experiment,including the following steps:electrode preparation,waste sample preparation,incubation of the waste samples,construction of a reactor using rice,vegetable,and fruit waste as a source of electricity,and testing.The tests included measuring electrical conductivity,electric current,voltage,current density,and power density.Based on the test results,the maximum current and voltage values for the fruit waste samples were 5.53 V and 11.5 mA,respectively,with a current density of 2.300 mA/cm^(2) and a power density of 12.719 mW/cm^(2).The results indicate the potential for a future development.The next step in development involves determining the optimum conditions for utilizing of rice,vegetable,and fruit waste.The results of the electrical conductivity test on rice,vegetable,and fruit waste samples were 1.51,2.88,and 3.98 mS,respectively,with the highest electrical conductivity value found in the fruit waste sample.

Rapid screening of 420 pesticide residues in fruits and vegetables using ultra high performance liquid chromatography combined with quadrupole-time of flight mass spectrometry

A new method for screening and identification 420 pesticide residues in fruits and vegetables by ultra-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry(UPLC-Q-TOF/MS)were developed.The samples were extracted with acetonitrile/acetic acid(99:1,V/V),and clean-up by SinChERS-Nano(single-step,cheap,effective,rugged,safe,nano)column,determined by UPLC-Q-TOF/MS.The accurate mass database and MS/MS database which contains 420 pesticides were established,the automatic retrieval of detection results was carried on according to the accurate mass,retention time,isotope ratio,ion fragment information,and so on.Method verification was performed on leeks samples.The results showed that 420 pesticides had good linearity in the range of 0.1-100μg/L,and the correlation coeffificients(R2)was greater than 0.990.The limits of detections(LODs)and limits of quantifications(LOQs)of 420 pesticides were in range of 0.05-2.0 and 0.1-5.0μg/L,respectively.The average spike recoveries at 3 levels were 70.1%to 119.7%,and the relative standard deviations(RSD)were lower than 20%(n=6).With this method,a survey of pesticide residues was conducted for 110 samples of 10 different fruits and vegetables,which provided scientific data for ensuring pesticide residue safety of the fruits and vegetables consumed daily by the public.This method was simple,sensitive and accurate,and could be used for rapid screening of 420 pesticide residues in fruits and vegetables.

Selected fermented indigenous vegetables and fruits from Malaysia as potential sources of natural probiotics for improving gut health

In the Peninsular Malaysia and Northern Borneo island of Malaysia, various rich indigenous leafy vegetables and fruits grow and contribute to the nutritional and dietary values of the population. They have high water contents, thus, naturally vulnerable to rapid food spoilage. Food preservation and processing play a vital role in the inhibition of food pathogens in fruits and vegetables that are prevalent in Malaysia. Lactic acid fermentation is generally a local-based bioprocess, among the oldest form and well-known for food-processing techniques among indigenous people there. The long shelf life of fermented vegetables and fruits improves their nutritional values and antioxidant potentials. Fermented leaves and vegetables can be utilized as a potential source of probiotics as they are host for several lactic acid bacteria such as Lactobacillus confusus, Weissella paramesenteroides, Enterococcus faecalis, Lactobacillus plantarum, Lactobacillus buchneri, Lactobacillus paracasei, Lactobacillus pentosus, Pediococcus acidilactici, Pediococcus pentosaceus and Leuconostoc mesenteroides. These strains may be more viable in metabolic systems whereby they can contribute to a substantial increase in essential biologically active element than industrial starter cultures. This review is aimed to address some essential fermented fruits and vegetables in Malaysia and their remarkable reputations as a potential sources of natural probiotics.

Experimental Study and Modeling of a Convective Dryer for Fruits and Vegetables

The present work deals with the study of the thermal performances of a convective dryer for fruits and vegetables. This dryer, operating with energy generated from the combustion of biomass in a boiler connected to a water/air heat exchanger could be a solution to the problematic of energy related to drying. An experimental and theoretical study is carried out on the temperature profile inside the dryer. For this purpose, 10.3 kg of tomatoes were dried on the experimental setup. The operation lasted about 16 hours and reduced the moisture content from 93.8% to 12% in wet basis. The overall thermal efficiency of the convective dryer during the trial is 10.76%. For the theoretical study, the dryer components (boiler, water/air exchanger and drying chamber) are first modeled individually;the different sub-programs are then coupled to form the convective dryer program. The method of global heat balances combined with the one called “ε-NUT” is used. The set of equations is discretized using the implicit method of finite differences, then solved with the Gauss algorithm in Fortran 90. The theoretical results obtained are in good agreement with those measured.

Nutraceutical Potentiality of Fruits of Red Variety of Pseudospondias microcarpa (A. Rich) Engl.

The red fruits of Pseudospondias microcarpa (A. Rich) Engl. are widely consumed by the populations of northern Congo for their sweet and tangy flavor as well as for their characteristic smell. The objective of this study was to show the food potential of the fruits of this plant for their valorization. Organic solvent extracts were prepared and subjected to phytochemical screening to determine the nutrients and phytonutrients of this fruit. Raw juice was extracted by trituration without adding water and subjected to physicochemical and biochemical analyses in order to determine its quality and its antiradical activity. The raw juice obtained is moderately acidic (pH 3.28), very cloudy and colored (turbidity of 1019 NTU). It has a dry matter content of 3.771% ± 0.013% reflecting the 70% dominance of water in the weight of the fruit and the presence of dissolved organic matter in its juice. Energy nutrients (sugars, amino acids), carotenoids, coumarins, tannins, flavonoids, terpenes and sterols have been highlighted as nutrients with therapeutic potential commonly called phytonutrients of this fruit. The juice presented a dominance in polyphenols (134.8500 ± 0.0023 mg gallic acid/100 g) than in carotenoids (5.100 ± 0.010 mg carotene/100 g), high levels of mineral macroelements (calcium: 3570.00 ± 2.05 mg and potassium: 4576.00 ± 9.49 mg) and trace elements (copper: 11.13 ± 0.10 mg, iron: 3.02 ± 0.03 mg and zinc: 2.57 ± 0.08 mg). These compounds exhibited good antioxidant activity. The presence of these nutrients and phytonutrients in these fruits is interesting for the proper functioning of certain organs and the prevention of certain diseases. This fruit is therefore an energizing and functional food that can compete with conventional fruits whose juices are marketed.

Structural characterization of three acidic polysaccharides from Opuntia dillenii Haw.fruits and their protective effect against hydrogen peroxide-induced oxidative stress in Huh-7 cells

Three novel acidic polysaccharide fractions(OFPP-1,OFPP-2,OFPP-3)with different m olecular weights(803.7,555.1 and 414.5 k Da)were isolated from the peeled Opuntia dillenii Haw.fruits by alkali-extraction,graded alcohol precipitation and column chromatography.Structural analysis indicated that OFPPs were pectic polysaccharides consisting of rhamnose,arabinose and galactose residues.The backbone of OFPP-1 consisted of a repeating unit→6-α-D-Galp A-(1→2)-α-L-Rhap-(1→with T-α-D-Galp A-(1→6)-α-D-Galp A-(1→4)-α-D-Glcp-(1→,T-β-D-Xylp-(1→6)-α-D-Galp A-(1→4)-α-D-Glcp-(1→or T-α-D-Galp A-(1→3)-α-L-Araf-(1→as the side chains.The backbone of OFPP-2 consisted of a disaccharide repeating unit→2)-α-L-Rhap-(1→4)-β-D-Galp A-(1→with T-β-L-Araf-(1→as the branches substituted at the O-4 position of→2,4)-α-LRhap-(1→.Whereas the backbone of OFPP-3 was→2,4)-α-L-Rhap-(1→2)-α-L-Rhap-(1→3)-β-L-Araf-(1→or→2,4)-α-L-Rhap-(1→2)-α-L-Rhap-(1→4)-β-D-Galp A-(1→,which was branched at the O-4 position of→2,4)-α-L-Rhap-(1→.Moreover,these three polysaccharide fractions could protect Huh-7 cells against H2O2-induced oxidative stress to different extents by decreasing the MDA content and increasing the SOD,CAT,GSH-Px activities and the GSH level in the Huh-7 cells.These results suggest that OFPPs have the potential to be used as natural antioxidants.

An Artificial Intelligence-Based Framework for Fruits Disease Recognition Using Deep Learning

Fruit infections have an impact on both the yield and the quality of the crop.As a result,an automated recognition system for fruit leaf diseases is important.In artificial intelligence(AI)applications,especially in agriculture,deep learning shows promising disease detection and classification results.The recent AI-based techniques have a few challenges for fruit disease recognition,such as low-resolution images,small datasets for learning models,and irrelevant feature extraction.This work proposed a new fruit leaf leaf leaf disease recognition framework using deep learning features and improved pathfinder optimization.Three fruit types have been employed in this work for the validation process,such as apple,grape,and Citrus.In the first step,a noisy dataset is prepared by employing the original images to learn the designed framework better.The EfficientNet-B0 deep model is fine-tuned on the next step and trained separately on the original and noisy data.After that,features are fused using a serial concatenation approach that is later optimized in the next step using an improved Path Finder Algorithm(PFA).This algorithm aims to select the best features based on the fitness score and ignore redundant information.The selected features are finally classified using machine learning classifiers such as Medium Neural Network,Wide Neural Network,and Support Vector Machine.The experimental process was conducted on each fruit dataset separately and obtained an accuracy of 100%,99.7%,99.7%,and 93.4%for apple,grape,Citrus fruit,and citrus plant leaves,respectively.A detailed analysis is conducted and also compared with the recent techniques,and the proposed framework shows improved accuracy.

Regional Brand and High-quality Development of Fruits in Ethnic Areas of the Yangtze River Economic Belt under the Greater Food Approach

Establishing the Greater Food Approach and promoting the Yangtze River Economic Belt s national major regional development strategy can better support and serve the agricultural power and Chinese-style modernization.This paper introduces the characteristics of fruit industry in 16 autonomous prefectures and 47 autonomous counties under the jurisdiction of the Yangtze River Economic Belt.It studies the intellectual property resources of brand marks from the aspects of geographical indications,collective trademarks,certification trademarks,well-known trademarks in China and national design patents,and analyzes the main problems of brand and high-quality development of fruit industry in these ethnic autonomous areas.Finally,it puts forward some strategies,such as improving the protection of intellectual property rights of geographical indications,using intellectual property rights of brand signs,building modern seed industry upgrading project,drawing lessons from the experience of thousand villages demonstration project,ensuring that large-scale poverty does not occur,and building a diversified food supply system.

Deep Learning-Based Classification of Rotten Fruits and Identification of Shelf Life

The freshness of fruits is considered to be one of the essential characteristics for consumers in determining their quality,flavor and nutritional value.The primary need for identifying rotten fruits is to ensure that only fresh and high-quality fruits are sold to consumers.The impact of rotten fruits can foster harmful bacteria,molds and other microorganisms that can cause food poisoning and other illnesses to the consumers.The overall purpose of the study is to classify rotten fruits,which can affect the taste,texture,and appearance of other fresh fruits,thereby reducing their shelf life.The agriculture and food industries are increasingly adopting computer vision technology to detect rotten fruits and forecast their shelf life.Hence,this research work mainly focuses on the Convolutional Neural Network’s(CNN)deep learning model,which helps in the classification of rotten fruits.The proposed methodology involves real-time analysis of a dataset of various types of fruits,including apples,bananas,oranges,papayas and guavas.Similarly,machine learningmodels such as GaussianNaïve Bayes(GNB)and random forest are used to predict the fruit’s shelf life.The results obtained from the various pre-trained models for rotten fruit detection are analysed based on an accuracy score to determine the best model.In comparison to other pre-trained models,the visual geometry group16(VGG16)obtained a higher accuracy score of 95%.Likewise,the random forest model delivers a better accuracy score of 88% when compared with GNB in forecasting the fruit’s shelf life.By developing an accurate classification model,only fresh and safe fruits reach consumers,reducing the risks associated with contaminated produce.Thereby,the proposed approach will have a significant impact on the food industry for efficient fruit distribution and also benefit customers to purchase fresh fruits.

Contents of Phytosterols in Vegetables and Fruits Commonly Consumed in China

Objective To quantify five specific dietary phytosterols and phytostanols in vegetables and fruits commonly consumed in China. Methods A total of 34 different kinds of vegetables and 33 kinds of fruits were chosen according to the consuming habit of Chinese people. All the samples were purchased from two shops in Beijing. The contents of phytosterols （13-sitosterol, campesterol, stigmasterol, 13-sitostanol, and campestanol） were analyzed by GLC method which was established by our laboratory, and the total phytosterols were calculated. Results The total phytosterol content in vegetables ranged 1.1-53.7 mg/100 g edible portion. The highest concentration was found in pea, cauliflower, broccoli, and romaine lettuce. The phytosterol contents in fruits ranged 1.6-32.6 mg/100 g, the highest concentration was found in navel orange, tangerine, and mango. Conclusion The phytosterol contents in vegetables and fruits are not as high as those in edible oils, but because of the large amount of consumption, they also play an important role in increasing the people＇s phytosterols intake, indicating that increased intake of vegetables and fruits with higher phytosterol contents helps increase the phytosterol intake in China.

Simultaneous Screening of 733 Pesticide Residues in Fruits and Vegetables by a GC/LC-Q-TOFMS Combination Technique

In this paper,we report the construction of two accurate mass databases and the development of a combination detection method that simultaneously screens for 733 pesticide and chemical contaminant multi-residues via high-throughput liquid chromatography(LC)-and gas chromatography(GC)-quadru pole-time-of-flight mass spectrometry(Q-TOFMS).This work demonstrates that electronic mass spectral standards may replace chemical-source standard materials as references through one sample preparation and the combination of GC/LC-Q-TOFMS screening.This cutting-edge technique has also replaced multiresidue determination using targeted detection with non-targeted screening.The pesticide residue types,sensitivity,recovery,and reproducibility of this combination technique are evaluated in eight fruit and vegetable matrices.This technique shows three advantages:①In comparison with the discovery capability of a single technique,the combination technique shows an improvement of 51.1%(GC-QTOFMS)and 39.6%(LC-Q-TOFMS),respectively;②the combination technique can satisfy a screening limit lower than 10μg·kg^-1 and meet the requirements of“uniform standards,”although some of the pesticide residues could be optimized to further improve screening sensitivity;③over 488 pesticides with recoveries between 60%-120%and relative standard deviation(RSD)<20%at a spiked level of 10μg·kg^-1 were detected with the combination technique in eight different matrices.From 2012 to 2017,this combination technique was applied in an investigation to screen pesticide residues from 1384 sampling locations for 38138 batched samples covering 18 categories and 134 types of fruits and vegetables obtained from across the mainland of China.After statistical analysis,533 pesticides in 115891 determinations were detected,and the regularity of pesticides in the fruits and vegetables sold on the Chinese market was shown.

Antioxidant Capacities and Main Reducing Substance Contents in 110 Fruits and Vegetables Eaten in China

The aim of this study was to screen strongly-antioxidant fruits and vegetables and supply practical diet guidance for the public. We used 1,1-diphenyl-2-picrylhydrazyl (DPPH), ferric-reducing antioxidant potential (FRAP), 2,2’-azino-bis-3-ethylbenzthiazoline-6-sulphonic acid (ABTS) and total reducing power (TRP) assays to investigate antioxidant activities in 110 fruits and vegetables. To analyze the correlation between antioxidant capacities and main reducing substance contents, total phenolic, flavonoid and vitamin C contents were assessed. The results showed great variation in antioxidant activity, and fifteen fruits and vegetables possessed the strongest antioxidant capacities: Toona sinensis, hawthorn, jujube, lotus root, persimmon, red plum, black plum, chilli pepper, star fruit, strawberry, blueberry, cherry, peach, pomegranate and great burdock. Total phenolic contents showed higher correlation with antioxidant capacity when using FRAP and TRP assays than when using the DPPH or ABTS assay. Phenolics and flavonoids, rather than vitamin C, contributed to antioxidant potential in most fruits and vegetables.

Analysis of the Influencing Factors and Key Driving Force concerning the Efficiency of Green Supply Chain of Fruits and Vegetables

Like the general green supply chain,the green supply chain of fruits and vegetables also requires low negative effects of the environment and high resource utilization rate,as well as the healthiness and freshness of fruits and vegetables.Currently,the level of development of the green supply chain of fruits and vegetables is low in China,and the freshness of fruits and vegetables can not be well maintained,so there is an urgent need to improve the operational efficiency of the green supply chain of fruits and vegetables.The operational efficiency of the green supply chain of fruits and vegetables is affected by many factors,and the most important factor is the incomplete consistency between the individual interests of supply chain members and the overall interests of supply chain.Therefore,the key driving force to improve the efficiency of green supply chain of fruits and vegetables is to build the scientific and rational collaborative decision-making mechanism of supply chain,in order to solve the problems concerning the green supply chain of fruits and vegetables,such as risk sharing,cost control and revenue allocation,thereby achieving the coordinated development of the green supply chain of fruits and vegetables.

Fruits and Vegetables Freshness Categorization Using Deep Learning

The nutritional value of perishable food items,such as fruits and vegetables,depends on their freshness levels.The existing approaches solve a binary class problem by classifying a known fruit\vegetable class into fresh or rotten only.We propose an automated fruits and vegetables categorization approach that first recognizes the class of object in an image and then categorizes that fruit or vegetable into one of the three categories:purefresh,medium-fresh,and rotten.We gathered a dataset comprising of 60K images of 11 fruits and vegetables,each is further divided into three categories of freshness,using hand-held cameras.The recognition and categorization of fruits and vegetables are performed through two deep learning models:Visual Geometry Group(VGG-16)and You Only Look Once(YOLO),and their results are compared.VGG-16 classifies fruits and vegetables and categorizes their freshness,while YOLO also localizes them within the image.Furthermore,we have developed an android based application that takes the image of the fruit or vegetable as input and returns its class label and its freshness degree.A comprehensive experimental evaluation of proposed approach demonstrates that the proposed approach can achieve a high accuracy and F1score on gathered FruitVeg Freshness dataset.The dataset is publicly available for further evaluation by the research community.

Studies on Fungi Responsible for the Spoilage/Deterioration of Some Edible Fruits and Vegetables

Investigation of fungi responsible for the post harvest deterioration of Lycopersicum esculentus (tomatoes), Elaeis guineensis (palm fruit), Ipomoea batatas (sweet potato), Solanum tuberosum (Irish potato), Musa sapientum (banana), Doucus carota (carrot), Musa paradisiaca (plantain), Carica papaya (pawpaw), Persea americana (Avocado pear), Citrullus lanatus (water-melon) and Capsicum chinense (fresh red pepper) from five different markets and farm lands in Enugu state, Nigeria was carried out. Healthy and diseased samples were collected from the selected markets/ farmlands. Fungal species found associated with the deterioration of the various fruits and vegetables tested included Mucor species (M. indicus, M. amphibiorum, M. racemosus and M. hiemalis), Rhizopus species (Rhizopus stolonifer, R. nigrican and R. oligosporus), Candida albicans, Aspergillus species (Aspergillus fumigatus, A. niger and A. flavus) and Penicillum species (P. oxalicum and P. chrysogenum) and Fusarium species (F. accuminatum, F. oxysporum, F. eqiuseti and F. moniliforme, F. solani, F. dimerum). All isolated fungi were pathogenic to the different fruits and vegetables from the result of pathogencity tests carried out.

Nitrate Residues in Fruits, Vegetables and Bread Samples and Their Health Consequences

Application of mineral fertilizers such as Nitrate or urea derivatives to crops is an essential agricultural step for fruits and vegetable production. This step may lead to accumulation of Nitrate levels in fruit and vegetables creating health risks such as cancer. This study aimed to determine nitrate residues in beard, fruits, vegetable and water samples collected from different locations and to correlate them with potential cancer cases in Gaza. Results showed elevated levels of Nitrate in some breads samples and all fruits, vegetable and water samples. This suggests high potential risk of population to cancer cases. So far, the growing incidence of cancer cases in Gaza strip may be attributed to high level of nitrate contents in bread, fruits, vegetable and water samples. It is recommended to exclude nitrate fertilization from agricultural process or replace it with other N-fertilizer source.

Polyphenols in Fruits and Vegetables and Its Effect on Human Health

Polyphenols represent a group of chemical substances common in plants, structurally characterized by the presence of one or more phenol units. Polyphenols are the most abundant antioxidants in human diets and the largest and best studied class of polyphenols is flavonoids, which include several thousand compounds. Numerous studies confirm that they exert a protective action on human health and are key components of a healthy and balanced diet. Epidemiological studies correlate flavonoid intake with a reduced incidence of chronic diseases, such as cardiovascular disease, diabetes and cancer. The involvement of reactive oxygen species (ROS) in the etiology of these degenerative conditions has suggested that phytochemicals showing antioxidant activity may contribute to the prevention of these pathologies. The present review deals with phenolic compounds in plants and reports on recent studies. Moreover, the present work includes information on the relationships between the consumption of these compounds, via feeding, and risk of disease occurrence, i.e. the effect on human health. Results obtained on herbs, essential oils, from plants grown in tropical, subtropical and temperate regions, were also reported.

Purchasing Patterns and Consumer Level Waste of Fruits and Vegetables in Urban and Peri-Urban Centers in the Philippines

Fruits and vegetables are inherently perishable hence they are considered as one of the most wasted categories of food. While several studies have been conducted to assess consumer level waste of fruits and vegetables, few have been conducted in developing countries like the Philippines. A survey, using a pre-tested questionnaire, and involving 500 respondents, was conducted in selected urban and peri-urban areas in the Philippines, to ascertain consumer level fruit and vegetable waste. The quantities of fruits and vegetables wasted by supermarket shoppers and those who purchased fruits in wet markets were comparably low at 3% - 4%. This low level of consumer fruit and vegetable waste was attributed to the small quantities (250 to 500 grams per purchase) purchased by consumers in both categories of markets. Consumer level fruit and vegetable waste, showed a positive correlation to household size. The level of fruit waste was positively related to household income, and negatively related to shopper’s age. Consumers who shopped in supermarkets, purchased larger quantities of fruit when compared to those who shopped in wet markets. Wet market shoppers on the other hand, purchased large quantities of vegetables. Decay, and quality loss manifested by shriveling, wilting, toughening, browning and softening were the main characteristics of fruits and vegetables discarded by consumers. The underlying causes of this waste, cited by respondents included “forgot to eat”, “poor quality”, “forgot to cook” and “overbuying”. Consumer efforts to minimize waste include buying enough for consumption, consuming or using immediately after purchase, planning their menus, improving storage and purchasing produce that is of good quality.

Food Functionality of Popular and Commonly Consumed Indigenous Vegetables and Fruits from Bangladesh

Functional food can be either natural or processed. Food contains known biologically active compounds, which provides clinically proven and documented health benefit. So far, no database is available in Bangladesh regarding the functionality of the indigenous foods. As a primary step, this study had been conducted with an aim to identify and characterize functionality of the indigenous foods of Bangladesh. Eight fruits and vegetables, which are very popular for their taste, price and easy availability, have been selected for in vitro screening of their functionality. High levels of fat and sugar binding capacity were observed in Pineapple (500% and 270.891% respectively). High nuplli mortality rate was found in cytotoxicity test with Pomelo extract (100%), which also contained high level of vitamin C (155 mg/100g). Pomelo contained the highest level of antioxidant among all these foods (0.674 nMol/100μl/mg protein). Red amaranth contained highest amount of protein (4.31 g/100g). In stem amaranth, Iron level was highest (1855.67 mg/kg). Total phenolics content of Water spinach and Stem amaranth were found higher than the other samples (59.339 and 55.728 mg GAE/g respectively). All these experiments showed these vegetables and fruits have high health impacts and can be act as potential functional foods.