Prediction of fruit rot disease incidence in Arecanut based on weather parameters

Received: July 19th, 2022 ; Accepted: October 20th, 2022 ; Published: November 22nd, 2022 ; Correspondence: [email protected] occurrence of pests and diseases in arecanut crops has always been an important factor affecting the total production of arecanut. Arecanut is always dependent on environmental factors during its growth. Thus monitoring and early prediction of the occurrence of the disease would be very helpful for prevention and therefore more crop production. Here, we propose artificial intelligence-based deep learning models for fruit rot disease prediction. Historical data on fruit rot incidence in representative areas of arecanut production in Udupi along with historical weather data are the parameters used to develop region-specific models for the Udupi district. The fruit rot disease incidence score value is predicted using recurrent neural network variants (i.e., Vanilla LSTM, Vanilla GRU, stacked LSTM, and Bidirectional LSTM) for the first time. The predictive performance of the proposed models is evaluated by mean square error (MSE) along with the 5-fold cross-validation technique. Further, compared to other deep learning and machine learning models, the Vanilla LSTM model gives 1.5 MSE, while the Vanilla GRU model gives 1.3 MSE making it the best prediction model for arecanut fruit rot disease

Comparative antioxidant and antimicrobial studies of cold and hot bark hydromethanolic extract of Couroupita guianensis Aubl

Couroupita guianensis, known by its common name as cannon ball tree, belongs to Lecythidaceae family, native of south and central America, India and Sri lanka. It’s been in use in traditional medicine and worshipped as sacred tree in india. With the importance of tree in various medicinal aspects as per the reports the present investigation was carried to access the phytochemical components, free radical scavenging and antimicrobial activity of cold and hot hydromethanolic extracts from the barks of medicinally important Couroupita guanensis. Phytochemical screening revealed the presence of total antioxidants, flavonoids, phenols and phytosterols in both cold and hot extracts. Quantitative estimations of the phytochemicals revealed the presence of high contents of total antioxidant activity (598.4 µg/ml), phenol content activity of (417.52 µg/ml) and phytosterols of (133.92 µg/ml) in cold hydromethanolic extracts compared to the hot hydromethanolic extract. The presence of high flavonoid content (417.52 µg/ml) was recorded in hot extract compared to the cold extract. Hot extract gave more scavenging activity with IC50 value (33.5 µg/ml). ABTS radical scavenging activity was found to be more in cold extract with IC50 values (24. µg/ml). Antimicrobial assay showed activity with B. cereus (13.00±0.00mm) and S.aureus (15.00±0.00mm) bacteria showed maximum zone of inhibition compared to the hot extract whereas C. albicans (13.00±O.00mm) showing maximum zone of inhibition compared to the cold extract and was not sensitive to any other fungal forms tested. This investigation pays way to consider Couroupita guianensis, with highly potential antioxidant and antimicrobial components, be used in pharmaceutical companies for the development of phytomedicine for the therapy and treatments

A comparative kinetic study on β-amylase and its antioxidant property in germinated and non germinated seeds of Glycine max. L

Enzyme activity plays a key role in each stage of plant development starting from the initial seed germination responses. A comparative analysis of beta amylase activity was performed, isolated from germinated and non germinated Glycine max seeds, which was partially purified by dialysis. The optimum pH and temperature for germinated seeds was found to be 4.5 and 370 C and that for non germinated seeds were 5.5 and 750 C respectively. MnCl2 and CoCl2 exhibited marked activating effect on the enzyme, while HgCl2 was a potent inhibitor for both seeds. The Km and Vmax value for β-amylase with soluble starch as substrate was found to be 3.03mg/ml and 6.6micromol/min/ml for germinated seed and for non germinated seeds it was found to be 5mg/m and 10micromole/min/ml respectively. The molecular weight of partially purified enzyme was 57±1kDa on SDS PAGE with 1.918 fold purification and 27.98% yield for germinated seeds and for non germinated seeds the purification fold was 1.507 with 26.65% yield. The enzyme showed highest amount of total antioxidant activity of 304µg/ml in partially purified germinated seed. For ABTS free radical scavenging activity, partially purified enzyme from germinated seed showed the highest of 76.09% activity with an IC50 value of 58.20µg/ml. Germinated seeds have highest enzymatic activity which can be considered for several industrial purposes

Tailored for Real-World: A Whole Slide Image Classification System Validated on Uncurated Multi-Site Data Emulating the Prospective Pathology Workload.

Standard of care diagnostic procedure for suspected skin cancer is microscopic examination of hematoxylin & eosin stained tissue by a pathologist. Areas of high inter-pathologist discordance and rising biopsy rates necessitate higher efficiency and diagnostic reproducibility. We present and validate a deep learning system which classifies digitized dermatopathology slides into 4 categories. The system is developed using 5,070 images from a single lab, and tested on an uncurated set of 13,537 images from 3 test labs, using whole slide scanners manufactured by 3 different vendors. The system\u27s use of deep-learning-based confidence scoring as a criterion to consider the result as accurate yields an accuracy of up to 98%, and makes it adoptable in a real-world setting. Without confidence scoring, the system achieved an accuracy of 78%. We anticipate that our deep learning system will serve as a foundation enabling faster diagnosis of skin cancer, identification of cases for specialist review, and targeted diagnostic classifications

Air-Abrasion in Dentistry: A Short Review of the Materials and Performance Parameters

The selection of abrasive material and parameters of the Air-Abrasion device for a particular application is a crucial detail. However, there are no standard recommendations or manuals for choosing these details; the operator must depend on his experience and knowledge of the procedure to select the best possible material and set of parameters. This short review attempts to identify some of the effects that the selection of material and parameters could have on the performance of the Air-Abrasion procedure for a particular application. The material and parameter data are collected from various studies and categorized according to the most popular materials in use right now. These studies are then analyzed to arrive at some inferences on the performance of Air-Abrasion materials and parameters. This review arrives at a few conclusions on the effectiveness of a material and parameter set, and that there is potential for developments in the area of standardizing parameter selection; also, there is scope for further studies on Bio-Active Glass as an alternative to the materials currently used in Air-Abrasion

Determinants of Prakriti, the Human Constitution Types of Indian Traditional Medicine and its Correlation with Contemporary Science

Background: Constitutional type of an individual or prakriti is the basic clinical denominator in Ayurveda, which defines physical, physiological, and psychological traits of an individual and is the template for individualized diet, lifestyle counseling, and treatment. The large number of phenotype description by prakriti determination is based on the knowledge and experience of the assessor, and hence subject to inherent variations and interpretations. Objective: In this study we have attempted to relate dominant prakriti attribute to body mass index (BMI) of individuals by assessing an acceptable tool to provide the quantitative measure to the currently qualitative ayurvedic prakriti determination. Materials and Methods: The study is cross sectional, multicentered, and prakriti assessment of a total of 3416 subjects was undertaken. Healthy male, nonsmoking, nonalcoholic volunteers between the age group of 20-30 were screened for their prakriti after obtaining written consent to participate in the study. The prakriti was determined on the phenotype description of ayurvedic texts and simultaneously by the use of a computer-aided prakriti assessment tool. Kappa statistical analysis was employed to validate the prakriti assessment and Chi-square, Cramer′s V test to determine the relatedness in the dominant prakriti to various attributes. Results: We found 80% concordance between ayurvedic physician and software in predicting the prakriti of an individual. The kappa value of 0.77 showed moderate agreement in prakriti assessment. We observed a significant correlations of dominant prakriti to place of birth and BMI with Chi-square, P < 0.01 (Cramer′s V-value of 0.156 and 0.368, respectively). Conclusion: The present study attempts to integrate knowledge of traditional ayurvedic concepts with the contemporary science. We have demonstrated analysis of prakriti classification and its association with BMI and place of birth with the implications to one of the ways for human classification