TOMATO DISEASE DETECTION MODEL BASED ON DENSENET AND TRANSFER LEARNING

Plant diseases are a foremost risk to the safety of food. They have the potential to significantly reduce agricultural products quality and quantity. In agriculture sectors, it is the most prominent challenge to recognize plant diseases. In computer vision, the Convolutional Neural Network (CNN) produces good results when solving image classification tasks. For plant disease diagnosis, many deep learning architectures have been applied. This paper introduces a transfer learning based model for detecting tomato leaf diseases. This study proposes a model of DenseNet201 as a transfer learning-based model and CNN classifier. A comparison study between four deep learning models (VGG16, Inception V3, ResNet152V2 and DenseNet201) done in order to determine the best accuracy in using transfer learning in plant disease detection. The used images dataset contains 22930 photos of tomato leaves in 10 different classes, 9 disorders and one healthy class. In our experimental, the results shows that the proposed model achieves the highest training accuracy of 99.84% and validation accuracy of 99.30%

Effects of hospital facilities on patient outcomes after cancer surgery: an international, prospective, observational study

Background Early death after cancer surgery is higher in low-income and middle-income countries (LMICs) compared with in high-income countries, yet the impact of facility characteristics on early postoperative outcomes is unknown. The aim of this study was to examine the association between hospital infrastructure, resource availability, and processes on early outcomes after cancer surgery worldwide.Methods A multimethods analysis was performed as part of the GlobalSurg 3 study-a multicentre, international, prospective cohort study of patients who had surgery for breast, colorectal, or gastric cancer. The primary outcomes were 30-day mortality and 30-day major complication rates. Potentially beneficial hospital facilities were identified by variable selection to select those associated with 30-day mortality. Adjusted outcomes were determined using generalised estimating equations to account for patient characteristics and country-income group, with population stratification by hospital.Findings Between April 1, 2018, and April 23, 2019, facility-level data were collected for 9685 patients across 238 hospitals in 66 countries (91 hospitals in 20 high-income countries; 57 hospitals in 19 upper-middle-income countries; and 90 hospitals in 27 low-income to lower-middle-income countries). The availability of five hospital facilities was inversely associated with mortality: ultrasound, CT scanner, critical care unit, opioid analgesia, and oncologist. After adjustment for case-mix and country income group, hospitals with three or fewer of these facilities (62 hospitals, 1294 patients) had higher mortality compared with those with four or five (adjusted odds ratio [OR] 3.85 [95% CI 2.58-5.75]; p<0.0001), with excess mortality predominantly explained by a limited capacity to rescue following the development of major complications (63.0% vs 82.7%; OR 0.35 [0.23-0.53]; p<0.0001). Across LMICs, improvements in hospital facilities would prevent one to three deaths for every 100 patients undergoing surgery for cancer.Interpretation Hospitals with higher levels of infrastructure and resources have better outcomes after cancer surgery, independent of country income. Without urgent strengthening of hospital infrastructure and resources, the reductions in cancer-associated mortality associated with improved access will not be realised

Enrichment of Zinc and Iron Micronutrients in Lentil (<i>Lens culinaris</i> Medik.) through Biofortification

Biofortification of pulse crops with Zn and Fe is a viable approach to combat their widespread deficiencies in humans. Lentil (Lens culinaris Medik.) is a widely consumed edible crop possessing a high level of Zn and Fe micronutrients. Thus, the present study was conducted to examine the influence of foliar application of Zn and Fe on productivity, concentration, uptake and the economics of lentil cultivation (LL 931). For this, different treatment combinations of ZnSO4·7H2O (0.5%) and FeSO4·7H2O (0.5%), along with the recommended dose of fertilizer (RDF), were applied to the lentil. The results of study reported that the combined foliar application of ZnSO4·7H2O (0.5%) + FeSO4·7H2O (0.5%) at pre-flowering (S1) and pod formation (S2) stages was most effective in enhancing grain and straw yield, Zn and Fe concentration, and uptake. However, the outcome of this treatment was statistically on par with the results obtained under the treatment ZnSO4·7H2O (0.5%) + FeSO4·7H2O (0.5%) at S1 stage. A single spray of ZnSO4·7H2O (0.5%) + FeSO4·7H2O (0.5%) at S1 stage enhanced the grain and straw yield up to 39.6% and 51.8%, respectively. Similarly, Zn and Fe concentrations showed enhancement in grain (10.9% and 20.4%, respectively) and straw (27.5% and 27.6% respectively) of the lentil. The increase in Zn and Fe uptake by grain was 54.8% and 68.0%, respectively, whereas uptake by straw was 93.6% and 93.7%, respectively. Also the benefit:cost was the highest (1.96) with application of ZnSO4·7H2O (0.5%) + FeSO4·7H2O (0.5%) at S1 stage. Conclusively, the combined use of ZnSO4·7H2O (0.5%) + FeSO4·7H2O (0.5%) at S1 stage can contribute significantly towards yield, Zn and Fe concentration, as well as uptake and the economic returns of lentil to remediate the Zn and Fe deficiency

In vitro study of ivermectin efficiency against the cattle tick, Rhipicephalus (Boophilus) annulatus, among cattle herds in El-Beheira, Egypt

Background and Aim: Ivermectin (IVM) has been used in veterinary practice to control different parasitic infestations over the past two decades. This study aimed to re-assess the acaricidal effects of IVM, as well as to evaluate its efficacy against Rhipicephalus (Boophilus) annulatus by determining the mortality rate, γ-aminobutyric acid (GABA) level, and oxidative/ antioxidative homeostasis (malondialdehyde [MDA] levels and glutathione S-transferase [GST] activities). Materials and Methods: Adult females of Rhipicephalus (Boophilus) annulatus were picked from cattle farms in El-Beheira Governorate, Egypt. Ticks were equally allocated to seven experimental groups to assess the acaricidal potential of IVM chemotherapeutics in controlling R. (B.) annulatus. IVM was prepared at three concentrations (11.43, 17.14, and 34.28 μM of IVM). Results: Mortality rate was calculated among the treated ticks. In addition, GABA, GST, and MDA biomarker levels were monitored. The data revealed a noticeable change in GST activity, a detoxification enzyme found in R. (B.) annulatus, through a critical elevation in mortality percentage. Conclusion: IVM-induced potent acaricidal effects against R. (B.) annulatus by repressing GST activity for the initial 24 h after treatment. Collectively, this paper reports the efficacy of IVM in a field population of R. (B.) annulatus in Egypt