Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: The marketability of pointed gourd fruit is drastically reduced after harvest due to moisture loss, chlorophyll degradation, yellowing of the skin, and shriveling. The present investigation studied the effect of exogenous salicylic acid (SA) treatment on senescence and fruit quality attributes of pointed gourd during storage under ambient conditions. Fruits were treated by immersing them in different concentrations of SA (1.0 mM, 2.0 mM, and 3.0 mM) and distilled water (control) for 5 minutes. The investigation showed beneficial effects of 3.0 mM SA treatment in lowering weight loss (16.8%), maintaining higher chlorophyll (32.8%) in the skin, and reducing lipid peroxidation (20.2%) compared to the control. SA (3.0 mM)-treated fruits retained 15.3% higher ascorbic acid and about 18% higher total phenol, flavonoids, and radical scavenging activity over pointed gourd fruits in the control group. However, significant difference in the total antioxidant capacity after 6 days of storage was not noted between SA-treated and control fruit. Thus, postharvest salicylic acid treatment can beneficially be used to extend marketability and delay quality deterioration of pointed gourd fruits stored under ambient conditions. PubDate: Fri, 13 May 2022 23:58:02 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: The non-judicious use of pesticides in agro-food poses a severe threat to food safety and human health. As an emerging chromatographic fingerprint provider, surface-enhanced Raman spectroscopy analysis (SERS) sheds bright light on sensitive and nondestructive detection of pesticide residues. This research proposed a novel strategy to detect three-pesticide residues (thiabendazole, carbendazim, and chlorpyrifos) on tomato peel based on the flexible and sticky SERS substrate. After selecting the best commercial adhesive tape (3M9080), the SERS substrate was constructed by optimizing the parameters in the preparation process of AuNPs. Therefore, a new simple “tape-wrapped SERS” way for pesticide residue analysis was established with a simple procedure of “absorption, separation, and drop addition.” Based on chemometrics method, the limit of semiquantitative detection was 20, 36, and 80 ng/cm2 for thiabendazole, carbendazim, and chlorpyrifos, respectively, on tomato surface, which indicated that the proposed method could meet the requirement of actual application with a large prospect in agro-food safety detection. PubDate: Fri, 13 May 2022 09:50:00 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: The goal of this research was to look into how artificial intelligence (AI) and machine learning (ML) techniques are being used in food industry and to come up with future research directions based on that. This study investigates the articles available on several scientific platforms that link both AI and supply chain from one side and ML and food industry from the other side, using a systematic literature review methodology. The findings of this research stated that although AI and machine learning technologies are yet in their beginning, the prospective for them to enhance the performance of the food industry (FI) is quite promising. Various investigators created AI and ML-related models that were verified and found to be effective in optimising FI, and so the use of AI and ML in FI networks provides competitive advantages for improvement. Other academics suggest that AI and machine learning are both now adding value, while others believe that they are still underutilised and that their tools and methodologies can harness the overall value of the food business. According to the findings, AI and machine learning have the potential to reduce economic losses, thereby supporting the food industry's efficiency and responsiveness. PubDate: Thu, 12 May 2022 10:35:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: In the era of digital technology, where innovation and digitization are transforming the business functions, the field of customer relationship management has witnessed sea change in the recent decade. The application of artificial intelligence in food processing has enabled enhancing the availability of food in an effective manner for all the individuals. It has been regarded that the application of labor force tends to play a crucial aspect for the overall execution of things in the different domains related to food manufacturing and processing, which are related to the enhanced involvement of individuals in the processing of food and related products, the industry could not able to meet the growing demand from the customers. So, in order to overcome these critical issues, it is noted that the application of technology such as automation and artificial intelligence is implemented for enhanced processing and enable delivering quality products to the customers at lower cost. The impact of AI in the current business world is becoming more indispensable as companies have started to unleash its potential. The role of AI in food processing is fast changing the manner in which the customer queries are addressed, enabling analysing the needs and requirements, and focus on creating improved packaging, high quality, and better shelf life. This empirical investigation is focusing on analysing the critical factors related to AI in influencing the food processing industry. The researchers intend to apply quantitative analysis using IBM SPSS package, and the results are stated in detail based on the analysis. PubDate: Thu, 12 May 2022 09:05:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: In the modern world, due to the usage of high-power chemical-based cosmetics, climate change, and other major factors, skin cancer has been increasing among individuals. Skin cancer is considered as the most common malignant disorder, and there are more than a million cases being recorded with this disease every year. Extensive studies have already been performed to identify the risk factors and causative agents for skin cancer, including lifestyle changes and eatery patterns among individuals. The most common type of skin cancer is classified into basal cell carcinoma and squamous cell carcinoma. The researcher intends to conduct the research with the primary goal of determining the important factors in blockchain technology in the treatment of skin cancer in senior people. The application of new technologies such as blockchain has enabled offering better promises to health care professionals in addressing skin cancer in a more effective manner. These tools supported in evaluating the nature and severity of psoriasis has been regarded as much support for health care professionals in detecting skin cancer and offer better health care guidance for better living. The detection of melanomas supports the patient in enhancing the prognosis and support in discriminating between the melanomas and less impact lesions. The blockchain-based classification system offers more benefits and reduces the cost of detecting skin cancer in an effective manner. It also helps the medical professionals by assisting them in developing a custom diet plan for each patient on the basis of their health records and food intake. The researchers are focused on applying both the primary data sources and secondary data sources for performing the study. A detailed questionnaire is designed, and it is shared with the participants through university hospitals, support groups, etc. so as to gather the information. Nearly 156 respondents were chosen through nonprobability sampling, and the information was collected. The researcher performs critical descriptive analysis, and correlation analysis is performed to understand the overall association between the variables. The researchers intend to perform the study with the basic goal of understanding the critical factors in blockchain technology in skin cancer for elderly individuals. The major factors involved are enhanced data privacy, support in forecasting patterns, and enhanced medical services to patients complemented with personalized dietary assessment and recommendations. The result demonstrates that artificial intelligence-based blockchain technology allows for the efficient processing of huge amounts of data in order to complete the assigned task and correctly determine and predict the model. PubDate: Wed, 11 May 2022 10:50:02 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: A comparison of concrete solar dryer (CSD) to stainless steel solar dryer (SSSD) in terms of the effect of drying and 10% vinegar pretreatment on antioxidant activities of ginger rhizome using 1,1-diphenyl-2-picrylhydrazyl (DPPH) radical scavenging activity method, Ferric Reducing Antioxidant Power (FRAP) Assay, and total antioxidant methods was investigated. The effect of the two solar dryers and open-sun drying (OSD) on bioactive compound composition of the 10% vinegar pretreated sliced ginger using ethanol and aqueous extracts with GCMS/MS identification was also evaluated. The antioxidant activities of ethanol and aqueous extract of the 10% vinegar pretreated ginger using FRAP, DPPH, and total antioxidant methods were all higher than that of the dried samples, with CSD having the highest antioxidant activities among the dried methods. Drying reduced the main bioactive compound, which is gingerol, from 47.97% in the fresh sample to 32.49% in the OSD sample. The CSD sample demonstrated close likeness to the fresh sample with regard to retaining the highest gingerol and α-zingiberene. Hence, CSD can be adopted for commercial processing of ginger to reduce postharvest losses of the crop. PubDate: Wed, 11 May 2022 04:35:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: The longissimus dorsi muscle of Xinjiang brown cattle and Angus cattle at the age of 3, 7, 12, and 24 months under the same feeding and management conditions were selected to explore the differences of muscle 4 fiber types in this study. The muscle histological and molecular biological reasons for the quality difference between Xinjiang brown cattle and Angus beef were discussed. The morphology of the muscle was compared by ATP enzyme staining and SDH enzyme staining, and its gene expression was detected by qRT-PCR. The mRNA expression levels of Myhc-I in 3-month-old Xinjiang brown cattle were significantly higher than those in Angus cattle of the same age (). The 4 fiber types of 7-month-old Xinjiang brown cattle were significantly lower than those of Angus cattle of the same age (). The expression level of type I and IIb in 12-month-old Xinjiang brown cattle was significantly higher than that in 12-month-old Angus cattle (). Type I and IIa of 24-month-old Xinjiang brown cattle were significantly lower than those of Angus cattle of the same age (). However, in our study, the basic characteristics of longissimus dorsi of Xinjiang brown cattle and Angus cattle, such as color, pH, shearing force, and other characteristics were not detected, which is lacking in this aspect. Overall, with the increase of age, the growth trend of muscle fiber morphology of Xinjiang brown cattle and Angus cattle is roughly the same, but from the point of view of muscle fiber types, the Xinjiang brown cattle are more suitable for the production of early fat calves and to make some reference for improving the quality of beef cattle in China. PubDate: Wed, 11 May 2022 04:35:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Celiac disease causes serious health problems for humans. Therefore, the consumption of gluten-free diets (GFDs) is the only therapy to prevent patients from developing the disease. The objective of the current study was to investigate the proximate analysis, mineral compositions, and antioxidant activities of the quinoa, germinated sweet lupin, fenugreek, and yellow maize, and they were used to develop gluten-free multigrain pan breads. A total of four different grain blend formulations were used to develop the pan bread. The textural properties, color, and sensory evaluation of the developed multigrain pan bread were also determined. The results of the present study showed a significantly higher fat content was found in germinated lupin (13.56%) and quinoa (12.76%), followed by germinated fenugreek and yellow maize (9.68% and 4.67%, respectively). The results indicated that the development of multigrain pan bread with fortification of quinoa, germinated lupin, germinated fenugreek, and yellow maize imparted significant improvement in the nutritional content. Therefore, it could be recommended that the addition of up to 15% of germinated lupin and fenugreek, 60% quinoa, and 10% yellow maize does not negatively affect the sensory characteristics and quality attributes of pan bread. PubDate: Mon, 09 May 2022 17:35:03 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Cassava is a significant contributor to food security and an income source for smallholder farmers in southern Ethiopia. However, little research effort has been done so far based on designing field experiment samples for the biochemical composition of cassava accession at the country level. The study was conducted to assess the biochemical composition of cassava accessions in southwest Ethiopia. Flour samples from the storage roots of 64 cassava accessions were collected and were run in duplicates. Data on 13 biochemical characters were collected and analyzed using standard methods. The analysis of variance showed significant to very highly significant differences among the tested accessions for biochemical composition. The flour moisture ranged from 4.83–10.11%, dry matter (89.89-95.17%), organic matter (86.71–92.65%), ash (2.1–3.96%), fiber (1.14–3.00%), fat (0.26-1.4%), crude protein (1.28-2.86%), starch (65.1–74.2%), carbohydrate (81.29–87.94%), energy (341.44–367.61 kcal/100g DM), and cyanide (1.67–3.14). The highest GCV = 29.54% was shown for crude fat, followed by GCV = 16.94% for crude fiber, and GCV = 16.11% for tannin, whereas, among the characters, dry matter was observed to be the lowest (GCV = 0.84%). The GAM ranged from protein 0.30% to 54.94% for fat, while heritability ranged from flour moisture and dry matter (17.29%) to 84.88% for cyanide. The first five principal components explained 80.1% of the total variation, with PC I accounting for 37%, PC II 15.4%, PC III 11.6%, PC IV 8.4%, and PC V 8.20% of the total variation. This study found the presence of high biochemical variability among the tested accessions’ roots and could be used to select accessions with desirable biochemical composition in future breeding work. PubDate: Mon, 09 May 2022 10:35:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Conventional treatment of sapodilla pulp yields very viscous, turbid, and low juice recovery. Sapodilla processing for juice requires liquefying enzyme that leads to rectifying flow of juice. This study was conducted to optimize the enzymatic pectolytic conditions of sapodilla fruit processing to extract maximum juice using a central composite design (CCD). The effect of processing variables on recovery of juice, total soluble solids (TSS), viscosity, clarity, and L-value along with physicochemical analysis was investigated. The optimized processing conditions were pectinase concentration (0.120%) at 42.02°C for 167.83 min resulting in juice recovery (62.08 ± 0.38%), viscosity (4.81 ± 0.02cP), TSS (21.48 ± 0.19 °Brix), clarity (0.72 ± 0.05%T), and L-value (28.79 ± 0.96). Optimized sapodilla juice showed higher filterability (24.16 ± 1.04 min−1), conductivity (69.46 ± 0.30 S/m), total phenolic content (35.86 ± 0.60 mg/100 mL), ascorbic acid (6.38 ± 0.58 mg/100 mL), moisture content (84.85 ± 0.21% WB), and titratable acidity (0.143 ± 0.0% citric acid) as compared to control sample (60.5 ± 1.80 min−1, 30.43 ± 0.35 S/m, 30.68 ± 0.85 mg/100 mL, 4.64 ± 0.0 mg/100 mL, 83.69 ± 0.18%, and 0.130 ± 0.0%). Optimized sapodilla juice was lower in sedimentation index (0.73 ± 0.11%), turbidity (13.73 ± 1.10 NTU), ash (0.57 ± 0.031%), and β-carotene (0.173 ± 0.008 μg/100 mL) as compared to control sample (1.07 ± 0.02%, 79 ± 0.75 NTU, 0.65 ± 0.031%, and 0.306 ± 0.007 μg/100 mL). The flow behavior index (n) was closer to 1 in both juice samples, which indicated Newtonian-like flow behavior. Conclusively, sapodilla juice extraction at optimal condition (0.120% of pectinase concentration) and 42.02°C/167.83 min would be potentiated to the beverage industry. The use of pectinase might reduce membrane fouling and facilitates processing operation efficiently. PubDate: Sat, 07 May 2022 06:35:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: This work aimed to evaluate the antioxidant and antimicrobial capacities of pineapple peel extract-incorporated chitosan films to establish its utility as an active food packaging film. Total phenol and total flavonoids in ethanolic pineapple peel extract (11.1 ± 0.82 mg GAE/g sample, 3.86 ± 0.4 mg Quercetin/g sample) were determined to be higher than those in methanolic pineapple peel extract (7.98 ± 0.55 mg GAE/g sample, 2.37 ± 0.13 mg quercetin/g sample) and higher antioxidant activity was observed for pineapple peel ethanolic extract (PEE). Similarly, PEE-enriched chitosan film also reported greater antioxidant activity compared to pineapple peel methanolic extract (PME)-incorporated chitosan film. The total phenols, flavonoids, and significant antioxidant activity were accounted due to the contents of ferulic acids, quercetin, and kaempferol in both PEE and PME quantified via triple quadrupole LC/MS/MS system. These alcoholic extracts exhibited significant inhibitory zones against both Gram-positive (Bacillus cereus, Staphylococcus aureus) and Gram-negative (Escherichia coli, Salmonella typhimurium) food-borne bacterial strains. PME exhibited the lowest minimum inhibitory concentration and minimum bactericidal concentration (0.625 mg/ml) against B. cereus. Pure chitosan films at ≥7 log CFU/ml after 24 h showed lower log reduction for all the bacterial organisms, whereas the chitosan-PEE (at ≤5 logs CFU/ml) and chitosan-PME (at ≤6 log CFU/ml) films expressed higher log reduction for all the four bacterial isolates. Thus, this work led to the utilization of the pineapple peel waste as well as provided an alternative to nonbiodegradable packaging films. PubDate: Fri, 06 May 2022 05:20:04 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Deep learning (DL) is a new approach that provides exceptional speed in healthcare activities with greater accuracy. In this regard, “convolutional neural network” or CNN and blockchain are two important parts that together fasten the disease detection procedures securely. CNN can detect and predict diseases like lung cancer and help determine food quality, and blockchain is responsible for data. This research is going to analyze the extension of blockchain with the help of CNN for lung cancer prediction and making food safer. CNN algorithm has been trained with a huge number of images by altering the filters, features, epoch values, padding value, kernel size, and resolution. Subsequently, the CNN accuracy has been measured to understand how these factors affect the accuracy. A linear regression analysis has been carried out in IBM SPSS where the independent variables selected are image dataset augmentation, epochs, features, pixel size (90 × 90 to 512 × 512), kernel size (0–7), filters (10–40), and padding. The dependent variable is the accuracy of CNN. Findings suggested that a larger number of epochs improve the CNN accuracy; however, when more than 12 epochs are considered, the accuracy may decrease. A greater pixel/resolution also improves the accuracy of cancer and food image detection. When images are provided with excellent features and filters, the CNN accuracy improves. The main objective of this research is to comprehend how the independent variables affect the accuracy (dependent), but the reading may not be fully exact, and thus, the researcher has conceded out a minor task, which delivered evidence supportive of the analysis and against the analysis. As a result, it can be determined that image augmentation and a large number of images develop the CNN accuracy in lung cancer prediction and food safety determination when features and filters are applied correctly. A total of 10–12 epochs are desirable for CNN to receive 99% accuracy with 1 padding. PubDate: Fri, 06 May 2022 05:20:04 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Good manufacturing practice (GMP) is the primary sanitary and processing requirement necessary to ensure the production of safe foods. It ensures that the production facilities and processes have the necessary conditions to prevent potential hazards from contaminating foods. However, little is known about its application in the production of a traditionally fermented and well-patronized food like the Ga kenkey. This study was therefore designed to evaluate the knowledge and practices of Ga kenkey producers in GMPs. A self-administered questionnaire was prepared and used to recruit 42 Ga kenkey producers using convenient sampling techniques. Out of the 42 producers, 83.3% were females, between 18 and 33 years (61.9%) and single (42.9%), and have been in the business for about 0 to 5 years (69.1%). A significant number of producers had neither GMP, food safety nor HACCP training. The producers have inadequate knowledge of GMPs since majority of them do not use gloves and consider wearing them unnecessary. Even though the producers agreed that GMPs improve product qualities, the establishment of reputation, and customer satisfaction and identify problems within the production process, they however did not pay attention to any form of hazards during the production process. Therefore, since education, training, and experience had a significant () positive influence on the producers’ knowledge and practices, sufficient training in GMPs coupled with regular supervision should be provided to the producers for the hygienic and safe production of this commonly patronized food. PubDate: Wed, 04 May 2022 13:05:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Numerous studies demonstrated that winter melons (Benincasa hispida) have a long storage life at 20°C without quality and flavor degradation in fruit. However, fruit for processing are frequently handled under refrigerated conditions or exposed to a warehouse without air conditioning. Therefore, this research aimed to evaluate whether a short high- and low-temperature storage of fruit, prior to processing, changes the flavor and nutritional profiles of winter melon juice. Weight loss of 1.71% was recorded subsequent to 20 days of 10°C storage, with 5.15% weight loss at 30°C. Sugar content significantly decreased during storage at 10°C and 30°C, while the soluble solids content slightly increased. Several specific phenolic compounds were detected, and the total concentration of phenolics increased over the storage time at both temperatures. The concentration of sulfur compounds, as well as hexanal and total volatiles that are principally responsible for off-flavor reduced significantly during storage and the reduction was greater at 10°C than at 30°C. The results indicate that preprocessing fruit storage at 10 or 30°C for 20 days will not harm the quality and flavor of winter melon juice. However, longer storage time caused water-soaked spots at 10°C and dry rot at 30°C. PubDate: Mon, 02 May 2022 10:50:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: This study aimed to explore the utilization of modified atmosphere packaging (MAP) for chicken thigh meat pieces (CTMP) during frozen storage periods (FSP) of 1, 30, 60, and 90 days at −18°C. The treatments were divided into seven groups which are control, vacuum, 15% O2/15% N2/70% CO2, 30% N2/70% CO2, 50% O2/50% N2, 30% O2/70% CO2, and 1.5 ml clove essential oil. The results showed that treatment of 30% N2/70% CO2 was associated with a lower pH value than control. The pH, drip loss, TBA, peroxide number, and fatty acid percentage values were significantly () increased as FSP rises. The effect of the MAP and muscle fiber index (MFI) was significantly different () by the FSP. A decrease in the drip loss during storage and cooking when samples were treated with a MAP of 15% O2/15% N2/70% CO2, 30% N2/70% CO2, and clove oil groups were noted. The lowest values of TBA, peroxide number, and fatty acid percentage were recorded using 15% O2/15% N2/70% CO2, 30% N2/70% CO2, and clove oil groups, respectively. There was an improvement in all sensory characteristics of all MAP and clove oil treatments. PubDate: Mon, 02 May 2022 04:05:00 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Agricultural mechanization information in our country has the main problems existing in the management and utilization. The analysis of China’s agricultural mechanization management model and related software is presented based on combining modern science and technology as well as the development of agricultural mechanization management information system based on network software to standardize the management information collection, processing, storage and transmission, agricultural mechanization management information science, standardization, automation, etc. According to the analysis, the output target speed after fusion is more stable, and the stability is increased by 59.59% compared with the single-point GNSS velocity measurement data, and by 18.32% compared with the data measured by the binocular vision velocity measurement system. It has realized the goal of accurate speed measurement from low speed to high speed. In particular, it has solved the problems such as vehicles unable to complete positioning and vehicle skidding caused by trees blocking GNSS satellite signals during field operations. PubDate: Sat, 30 Apr 2022 04:50:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Fertilization, either in the form of organic or inorganic, always affects plant growth, yield, and nutritional quality of fruit crops. Further, the efficacy of fertilizers depends on various factors, including the area, climatic conditions, and cultivars. Rawalakot has ideal climatic conditions for growing strawberries. However, no studies related to the impact of different soil amendments on the growth habit and fruit quality of strawberries have been conducted so far. Therefore, in this study, different combinations of organic (farmyard manure (FYM) and poultry manure (PM)) and inorganic (urea) (N 150 kg/ha) fertilizers were used for comparison of growth pattern and postharvest quality of strawberry cv. Chandler. The organic and inorganic fertilizer regimes showed comparatively better results in terms of all the parameters studied. However, plants grown on soils amended with FYM equivalent to 75 kg N per ha + PM equivalent to 75 kg N per ha and FYM equivalent to 50 kg N per ha + PM equivalent to 50 kg N per ha + urea 50 kg N per ha showed 41% and 28% more survival percentage compared to control. Furthermore, the number of leaves, number of flowers, number of fruits, and yield were significantly high in plants grown on amended soil. Moreover, a significantly high amount of total soluble solids (10.0°Brix), titratable acidity (1.18%), ash (0.84%), fiber (3.03%), total phenols (7.61 μg gallic acid/g fresh weight), total flavonoids (7.93 mmol quercetin/100 g fresh weight), and total antioxidants (0.60 activity of FeSO4 mg/g fresh weight) was noted in comparison with control. Similarly, a combined treatment of FYM, PM, and urea also showed good results in terms of all the growth and fruit quality parameters as compared with other fertilizer regimes as well as control. However, the overall results of this study revealed that strawberries grown on soil amended with a combined dose of FYM equivalent to 75 kg N per ha + PM equivalent to 75 kg N per ha could be a potential dose for maximum yield and better quality fruits of strawberry. PubDate: Sat, 30 Apr 2022 04:05:02 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Medical science in recent times has witnessed the large implications of AI-based IoT approaches that made the clinical process easier than before. However, effective IoT technologies can connect as well as exchange necessary clinical data with other healthcare systems and devices conducted across the vast Internet facilities. With the help of IoT-enabled big data processing technologies, physicians can measure accurate weight, blood pressure, and daily symptoms related to spreading breast cancer cases across the globe. Utilizing IoT is essential for providing proper medical assistance, treatment, and detection at the initial stages within the healthcare environment regulated by the facilities of the Internet of Things. The implementation of IoT-based big data processes food products for supporting the detection and prevention of breast cancer. The study supports in making a critical analysis on the role of IoT in the big data mainly in cancer detection and increasing the quality of food products. The study’s main scope is to employ IoT-enabled big data processing to aid in the identification of breast cancer. However, the research is mainly focused on studying the assistance offered to healthcare professionals and others in identifying the disease effectively. The overall research study is going to investigate the role of IoT in the early detection of breast cancer symptoms. A total of 20 women were studied and certain factors have been identified which are the early symptoms of breast cancer and can potentially cause breast cancer. These include age, family history, breast density, and breast temperature (independent variables). A dependent variable has been selected: probability of breast cancer occurrence. After that, linear regression analysis has been carried out to understand how the independent variables impact the dependent variable. Findings showed that age, family history of cancer, breast density, and breast temperature are some measurable factors for breast cancer detection. The work contributes to a critical investigation of the function of IoT in big data, specifically in cancer detection and improving food product quality. Age acceleration increases the risk of breast cancer development; breast temperature increases slightly during cancer formation, and breast density has a positive impact on cancer development. Lastly, this study has provided a future scope of using IoT in cancer detection and prevention. PubDate: Fri, 29 Apr 2022 08:35:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: The aim of this study was to explore the regional characteristics of soluble sugars, organic acids, and stable isotopes (δ2H, δ18O, and δ13C) in Fuji apple and the viability of tracing the geographical origin. Totally, 181 Fuji apple samples from 2017 and 2018 from three main apple production regions in China, Bohai Bay (BHB), Loess Plateau (LP), and Northwest region (NW) were collected. The parameters of soluble sugars, organic acids, and stable isotopes in samples were analyzed with HPLC, IC, and IRMS, respectively. The results of regional difference analysis, multiway variance analysis, and correlation analysis indicated that sorbitol (Sor), glucose (Glu), fructose (Fru), sucrose (Sucr), δ2H, and δ13C can be used to distinguish the samples from the three regions. Stepwise linear discriminant analysis (SLDA) showed that the correct discriminant rate of samples from the advantageous production areas of apples in China (BHB and LP) was 82.2%, and the most effective indexes were Glu, Fru, Sucr, and δ2H. Moreover, satisfactory classification can be achieved in samples from BHB and NW, with a correct classification rate of 90.0%, and Sor, Glu, and Fru were included in the discrimination model. Furthermore, the validity of the discriminant model was verified by the prediction set. The study also found that organic acids were not suitable to distinguish the apple samples from the three regions. In addition, soluble sugars and stable isotopes could not effectively distinguish LP and NW samples, which was also the reason that the samples from the three main apple production regions could not be distinguished well. PubDate: Thu, 28 Apr 2022 13:35:03 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Wild ornamental plants are beneficial as well as dangerous for the environment. Because the introduction of attractive plants that are not suited to the local ecosystem can result in significant environmental damage, a quick integration strategy based on an enhanced clustering algorithm is proposed for wild ornamental plant resources. The technique is enhanced with density stratification by integrating the k-means distance measurement formula and establishing the objective function of clustering optimization. The cluster termination condition is controlled by the number of clusters k, and the wild plant data categories are continually merged. Uneven density distribution is used to deal with the wild plant distribution dataset. To obtain the distribution of wild ornamental plants in different regions, to estimate the optimal parameters of wild plant samples, to combine with maximum likelihood classification to obtain the plant flora differentiation degree, and to complete the resource integration, remote sensing images were used. Comprehensive survey and systematic sampling were used to conduct a complete survey of the protected area. The heat map of the plant size distribution shows that there is a clear negative correlation between the spatial scale difference and the overall density difference of the plant distribution, that is, it appears spatially. From the experimental analysis, it is observed that the high-density small-scale and low-density large-scale agglomeration distribution characteristics delay is 1.96 s. PubDate: Thu, 28 Apr 2022 12:50:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Biosurfactants are a functionally and structurally heterogeneous group of biomolecules produced by multiple filamentous fungi, yeast, and bacteria, and characterized by their distinct surface and emulsifying ability. The genus Bacillus is well studied for biosurfactant production as it produces various types of lipopeptides, for example, lichenysins, bacillomycin, fengycins, and surfactins. Bacillus lipopeptides possess a broad spectrum of biological activities such as antimicrobial, antitumor, immunosuppressant, and antidiabetic, in addition to their use in skincare. Moreover, Bacillus lipopeptides are also involved in various food products to increase the antimicrobial, surfactant, and emulsification impact. From the previously published articles, it can be concluded that biosurfactants have strong potential to be used in food, healthcare, and agriculture. In this review article, we discuss the versatile functions of lipopeptide Bacillus species with particular emphasis on the biological activities and their applications in food. PubDate: Wed, 27 Apr 2022 11:50:02 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: In order to quickly evaluate the quality of Tremella fuciformis, the volatile components of T. fuciformis from 4 provinces in China, including Hebei, Henan, Fujian, and Sichuan, were analyzed by electronic nose combined with gas chromatography-mass spectrometry (GC-MS), and the key aroma compounds were determined by relative odor activity value (ROAV). The results showed that the electronic nose combined with the principal component analysis method could distinguish the samples from four regions with good discrimination. At least 117 volatile components were detected in T. fuciformis by GC-MS and a total of 58, 59, 62, and 55 volatile components were identified from Hebei, Henan, Fujian, and Sichuan, respectively, of which there were 18 common components. The volatile components in T. fuciformis were mainly hydrocarbons, followed by aldehydes, acids, and esters, while acetic acid and hexanal were relatively rich in T. fuciformis. Based on the ROAV, 8 key components affecting the aroma of T. fuciformis strongly were found. Among them, hexanal, nonanal, and pentanal were the common components of T. fuciformis, while butyrolactone, 1-octen-3-ol, and 2-carene were the unique key aroma components of T. fuciformis in Hebei Province. Besides, octanal and butyrolactone were the special key components absent in the Sichuan and Henan samples, respectively. PubDate: Wed, 27 Apr 2022 03:35:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Food adulteration has become a threat to many countries as most individuals have consumed food items without knowing that it has been adulterated, leaving the consumer with various ailments. This study identifies the degree of adulteration in some commonly used food items bought by consumers and the means of detection. The study comprised 384 women who patronized various food items for food preparation. They were asked if they have come into contact with adulterated food products before and to illustrate how they detect if a food item is adulterated. From the findings of this study, the respondents indicated that they will not consume a food item if they get to know that it has been adulterated, and 50.5% indicated that they have come into contact with adulterated food during preparing food. Various reasons were given by the respondents why they will not consume adulterated food, and the reasons included the following: the food may be dangerous to consume and not healthy for consumption and can cause stomach disorders. Few numbers (11 out of 384) of the respondents also indicated that they will still go ahead and consume adulterated food items since not all adulterants are toxic. Food items that are prone to adulteration as mentioned by the respondent included groundnut paste, chilli pepper, tomato powder, and honey with their adulterants ranging from flour, colour, Sudan IV dye, chalk powder, foam, cola nut powder, avocado pear seed powder, and many more. Means of detecting the presence of adulterants as indicated by the respondent were sensory and textural characteristics due to the cost involved in the use of other advanced techniques. PubDate: Tue, 26 Apr 2022 15:05:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Bioactive compounds are secondary metabolites synthesized by plants for maintaining homeostasis; however, they also modulate metabolic processes and demonstrate valuable effects in the human body. The fig was cherished as food and for its pharmaceutical properties. The presence of a wide range of biologically active compounds such as carotenoids, flavonoids, phenols, and vitamin C is obligated for their functional properties as well as their technological capability as a dietary supplement is responsible for most health impacts. Owing to the rich and diversified composition of biologically active compounds these compounds possess different biological properties such as antioxidant, anti-inflammatory, antidiabetic, antimicrobial, and hepatoprotective activity that implies those bioactive substances might be used in the creation of novel culinary and medicinal products. Fig fruit should be widely recognized as a natural functional product. This systematic and comprehensive review gives the notion of developing figs species as a viable and innovative component for its varied food and nonfood applications as a remarkable and primitive source of medication and nourishment. PubDate: Tue, 26 Apr 2022 11:05:00 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: The aim of this study is to evaluate infected leaf disease images. Precision agriculture's automatic leaf disease detection system employs image acquisition, image processing, image segmentation, feature extraction, and machine learning techniques. An automated disease detection system offers the farmer with a fast and accurate diagnosis of the plant disease. Automation of plant leaf disease detection system is essential for accelerating crop diagnosis. Using machine learning and image processing, this paper describes a framework for detecting leaf illness. An image of a leaf can be used as an input for this framework. To begin, leaf photographs are preprocessed in order to remove noise from their images. The mean filter is used to filter out background noise. Histogram equalization is used to enhance the quality of the image. The division of a single image into multiple portions or segments is referred to as segmentation in photography. It assists in establishing the boundaries of the image. Segmenting the image is accomplished using the K-Means approach. Feature extraction is carried by using the principal component analysis. Following that, images are categorized using techniques such as RBF-SVM, SVM, random forest, and ID3. PubDate: Tue, 26 Apr 2022 09:50:00 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Crop diseases, pest infestations, water shortages, weed infestations, and other issues affect the agriculture sector. Due to existing agricultural techniques, these issues result in significant crop loss, economic loss, and severe environmental hazards. Because agriculture is such a dynamic industry, robotics cannot solve all of its difficulties; instead, a single solution to a specific complex problem is supplied. To assist with these issues and provide a better approach globally, a variety of systems have been developed. Plant protection robots are characterized by complexity, constraint, and nonlinearity. In order to improve the accuracy and reliability of plant protection robots in agricultural job path planning, we propose a path planning method for agricultural plant protection robots based on a nonlinear algorithm. The ant colony algorithm was selected to plan the path distance index according to the working environment, and the feasibility of the simulation system was calculated. The results show that the fastest time used by the nonlinear algorithm is 5.3, and the path planning accuracy is up to 97.8%. Compared with the traditional algorithm, the algorithm has higher accuracy, less computing time, and higher computing efficiency. PubDate: Mon, 25 Apr 2022 11:35:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Pseudomonas aeruginosa (P. aeruginosa) is a pathogenic bacterium and one of the seafood's most common spoilage microorganisms. In this study, 470 fish samples collected randomly were evaluated for the presence of P. aeruginosa, antibiotic resistance, and frequency of virulence factors. Isolation of P. aeruginosa from fish samples was performed on cetrimide agar after an initial enrichment. Representative colonies were selected, and biochemical tests were conducted. An antibiotic resistance test was performed using the disk diffusion method. DNA was extracted, and antibiotic resistance genes, as well as virulence genes, were detected using PCR. Fresh fish showed the highest prevalence of P. aeruginosa (5%). No positive samples contaminated with P. aeruginosa were isolated from frozen fish samples. From smoked, salted, and dried fish, two samples (2.85–4%) were contaminated with P. aeruginosa. The antibiotic resistance against meropenem, imipenem, carbapenem, erythromycin, gentamicin, chloramphenicol, and enrofloxacin was 0%. The lowest antibiotic resistance pattern was observed in fresh fish, and the highest was observed in smoked, salted, and dried fish. Respectively, blaTEM, blaCTX-M, and blaSHV were the most abundant genes encoding antibiotic resistance. The most virulence genes were algD, algU, lasB, toxA, exoS, exoT, and apr. This study suggests that raw seafood could be a source of antibiotic-resistant P. aeruginosa and helps to spread resistance genes through the food chain. It seems that cross-contamination in the fishing, transportation, and supply of seafood can cause increased contamination with Pseudomonas aeruginosa in these products. Therefore, the hygienic principles can effectively reduce contamination by P. aeruginosa. Also, the prophylactic use of antibiotics in these products should be controlled. PubDate: Mon, 25 Apr 2022 04:20:01 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Berries waste is a major issue in Australia’s annual food wastage, which can reach 7.3 million tonnes. This study assessed the phenolic content and antioxidant potential of four fruit berry wastes, including blueberries (Vaccinium corymbosum), blackberries (Rubus spp.), raspberries (Rubus idaeus), and strawberries (Fragaria spp.), followed by their characterization and quantification. Blueberry wastes were high in phenolic content (total phenolic content: 1.97 ± 0.16 mg GAE/gF.W; total flavonoid content: 220.43 ± 13.15 μg QE/gF.W; total tannins content: 16.47 ± 0.98 μg CE/gF.W), and antioxidant potentials are 2,2′-diphenyl-1-picrylhydrazyl: 2.23 ± 0.17 mg AAE/gF.W; 2,2′-azino-bis-(3-ethylbenzothiazoline-6-sulphonic acid): 1.79 ± 0.09 mg AAE/gF.W; ferric reducing antioxidant power: 68.71 ± 11.11 μg AAE/gF.W (total antioxidant capacity: 1.22 ± 0.03 mg AAE/gF.W). The LC-ESI-QTOF-MS/MS analysis identified 87 compounds from blueberry (57), strawberry (40), raspberry (47), and blackberry wastes (27). Indicated by HPLC quantification, blueberry wastes had higher levels of phenolic acid (syringic acid and coumaric acid) and flavonoid (kaempferol and kaempfero l-3-glucoside). Our study reported that phenolics from berry wastes could be utilized in different food, feed, pharmaceutical, and nutraceutical industries. PubDate: Sat, 23 Apr 2022 15:49:15 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: Celiac patients must follow a strict gluten-free diet along the life that leads to many nutritional deficiencies. This study aimed to produce an “all-in-one gluten-free cakemix based on quinoa flour” for celiac patients and other gluten-sensitive people. Nine treatments were provided with quinoa flour (25, 27.5, and 30% of total formula), inulin as a prebiotic, fat replacer and natural sweetener (2.4, 3.2, and 4% of total formula). The content of oil was reduced using oil powder consisting of sunflower oil and wall materials (resistant starch and maltodextrin 50 : 50). Bacillus coagulans was added as a probiotic bacteria. A commercial cakemix was considered as a control sample. The nutritional and chemical properties of cake mixes (percentage of moisture, protein, mineral, carbohydrate, crude fiber, fat, and calorie) and physical and textural properties of cakes (springiness, specific volume, porosity, chewiness, browning reaction, moisture, and water activity) were tested. Data were analyzed by https://graphpad.ir/prism/software using one way analysis of variance (ANOVA). After sensory evaluation, the treatment number 5 was selected as the most acceptable cake among all treatments. Its amino acid profile, fatty acid profile, and peroxide index were determined. The minerals, protein, and fiber of quinoa cake mixes were significantly higher, and the fat, carbohydrate and calorie were lower than control. Addition of quinoa reduced springiness, specific volume, porosity, chewiness, and increased the browning reaction. But these changes did not have a very negative effect in general. The moisture, water activity, and bacteria count changes were followed during four days of cakes preservation in refrigerator. The reduction trend of quinoa cakes moisture and water activity was slower than control. The number of bacteria was enough to be considered as a probiotic product after 4 days. Quinoa flour could improve the nutritional and functional properties of gluten-free cake mixes. PubDate: Sat, 23 Apr 2022 15:49:14 +000
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: The Papaver L. plant (Papaver decaisnei) has ethnobotanical records in many countries including Iraqi Kurdistan. The current study investigates the methanol (99.9%) extracts (10 μg/mL) of roots, leaves, and flowers of Papaver decaisnei in terms of phytochemistry by gas chromatography-mass spectrophotometry GC-MS, in vitro antioxidant activity by radical scavenging and reducing power assays, and finally, the anticancer actions as IC50 (inhibitory concentration at 50%) against human colorectal adenocarcinoma (Caco-2), mammary cancer cells (MCF-7), and human cervical carcinoma (HeLa) cells. The results showed 22, 19, and 17 chemicals for roots, leaves, and flowers of P. decaisnei, respectively. The prevalent organic compounds of P. decaisnei were alkaloids (62.03%), phenolics (55.43%), fatty acids (42.51%), esters (32.08%), terpenoids (25.59%), and phytosterols (15.68%), namely, roemerine (70.44%), 9,12,15-octadecatrien-1-ol (37.45%), hexadecanoic acid (33.72%), decarbomethoxytabersonine (24.49%), and γ-sitosterol (11.22%). The antioxidant activity of plant organs was within 39.1–143.5 μg/mL for DPPH, 135.4–276.4 μg/mL for ABTS, 12.4–34.3 μg/mL for FRAP, and 42.6–75.8 μg/mL for CUPRAC assays. The anticancer of P. decaisnei was found as 125.3–388.4 μg/mL against all tested cell lines (Caco-2, MCF-7, and HeLa). The detected alkaloids and bioactivity of P. decaisnei encourage future isolation of those remarkable alkaloids (reomerine) for potential usage in the pharmaceutical industry. PubDate: Sat, 23 Apr 2022 04:20:01 +000