Impact of Weed Competition on Morphological and Biochemical Traits of Potato: a Review

Potato (Solanum tuberosum L.) is the fourth major crop grown as a staple food worldwide, following rice, wheat, and maize. It is highly susceptible to diseases, nematodes, insect pests, and weeds. Potato yield loss due to weeds varies from 10 to 80% depending on the environment, weed diversity, density, and period of the weed-crop competition. High weed interference may decrease 65% of marketable tuber yield by reducing the number and size of marketable tubers. Weeds not only decrease potato tuber yield but also negatively influence the antioxidant enzymatic activity and primary metabolites of the potato plant. Estimates have shown that the starch content of potato tuber decreases by 10% and protein content by 36% in potato-weed competition. These findings suggest that weed competition can substantially impact potato growth and development and that effective weed management strategies are critical for optimizing potato yields and quality. This review summarizes the recent progress on how potato plants initially respond to weed interference at morphological, biochemical, and physiological levels

Comparative Performance of Various Disc-Type Furrow Openers in No-Till Paddy Field Conditions

Jabran, Khawar/0000-0001-8512-3330WOS: 000406709500072Different furrow openers are required to be evaluated for their suitability to manage rice straw for direct planting of wheat in paddy fields. This study was carried out to assess the straw-cutting ability and draft requirements of four different disc-type furrow openers (notched, toothed, smooth-edge single disc, and double disc) in no-till paddy fields. The openers were attached to an in-field traction rig equipped with S-type load cells, and tested using three operating depths of 30, 60, and 90 mm, and three traveling speeds of 0.1, 0.2, and 0.3 m s(-1). Vertical and horizontal forces acting on the openers were observed using LabVIEW software based data acquisition system. The results of this study indicated that the furrow opener type, operating depth, and speed significantly influenced the horizontal and vertical forces, as well as straw-cutting ability of the furrow openers. The highest draft and vertical force were noted for double disc-type furrow openers. The mean straw-cutting efficiency of notched, toothed, and smooth-edge single disc and double disc furrow openers were 12.4, 46.2, 11.4, and 78.5%, respectively. The double disc furrow opener (DD) produced the lowest level of hair-pinned straw and had the highest straw-cutting efficiency with a value of 88.6% at 90 mm operating depth, and therefore had the best performance in comparison with other furrow openers.HEC, PakistanHigher Education Commission of Pakistan; National Science and Technology [2013BAD08B04]; State Key Special Program of Soil Fertility Improvement and Cropping Innovation for High-Yield Efficiency in Rice Cropping Areas [2016YFD0300900]This manuscript represents a portion of Ph.D. research by the first author. Thanks to the HEC, Pakistan for providing Ph.D. Scholarship to the first author. Additionally, work was sponsored by the National Science and Technology Support Program (2013BAD08B04) and the State Key Special Program of Soil Fertility Improvement and Cropping Innovation for High-Yield Efficiency in Rice Cropping Areas (2016YFD0300900)

Forces and straw cutting performance of double disc furrow opener in no-till paddy soil.

Conservation tillage is an energy efficient and low cost tillage system to improve soil environment compared with conventional tillage systems. However, the rice residue management becomes an "impossible to achieve" task due to high soil moisture content at harvest time and the thickness of rice straw. Disc type furrow openers are used for both seed drilling as well as straw cutting during no tillage sowing. A study was conducted to evaluate the draft requirement and straw cutting performances of different sized furrow openers in no-till paddy soil conditions. Double disc furrow opener was tested on an in-field traction bench for three working depths, i.e. 30, 60 and 90 mm, and three forwarding speeds, i.e. 0.1, 0.2 and 0.3 m/s. The draft and vertical forces on the disc were recorded with load cells. These sensors were connected to a data acquisition system developed with hardware and software. The results revealed that the size of the furrow opener, operating depth and the forwarding speed had significant effects (P<0.05) on the horizontal and vertical forces, and the straw cutting performance. Mean values of the draft were 648.9, 737.2 and 784.6 N for the opener with diameters of 330, 450 and 600 mm respectively, and the vertical forces for similar openers were 904.7, 1553.9 and 1620.4 N, respectively. Furthermore, the mean straw cutting efficiencies for the double disc opener with diameters of 330, 450 and 600 mm were 39.36, 78.47 and 65.46%, respectively. The opener with 450 mm diameter provided higher straw cutting efficiency as compared to 600 mm diameter disc, while lowest straw cutting efficiency was observed with 330 mm diameter disc. The 450 mm diameter opener provided the highest straw cutting efficiency (88.6%) at 90 mm working depth and expressed optimum performance compared with other furrow openers

Economic assessment of conventional and conservation tillage practices in different wheat-based cropping systems of Punjab, Pakistan

Jabran, Khawar/0000-0001-8512-3330; Farooq, Shahid/0000-0002-6349-1404; Farooq, Muhammad/0000-0003-4368-9357WOS: 000413649700051PubMed: 28913583Wheat productivity and profitability is low under conventional tillage systems as they increase the production cost, soil compaction, and the weed infestation. Conservation tillage could be a pragmatic option to sustain the wheat productivity and enhance the profitability on long term basis. This study was aimed to evaluate the economics of different wheat-based cropping systems viz. fallow-wheat, rice-wheat, cotton-wheat, mung bean-wheat, and sorghum-wheat, with zero tillage, conventional tillage, deep tillage, bed sowing (60/30 cm beds and four rows), and bed sowing (90/45 cm beds and six rows). Results indicated that the bed sown wheat had the maximum production cost than other tillage systems. Although both bed sowing treatments incurred the highest production cost, they generated the highest net benefits and benefit: cost ratio (BCR). Rice-wheat cropping system with bed sown wheat (90/45 cm beds with six rows) had the highest net income (4129.7 US$ ha(-1)), BCR (2.87), and marginal rate of return compared with rest of the cropping systems. In contrast, fallow-wheat cropping system incurred the lowest input cost, but had the least economic return. In crux, rice-wheat cropping system with bed sown wheat (90/45 cm beds with six rows) was the best option for getting the higher economic returns. Moreover, double cropping systems within a year are more profitable than sole planting of wheat under all tillage practices.Higher Education Commission of PakistanHigher Education Commission of PakistanAuthors are grateful to Higher Education Commission of Pakistan for financial support for this study

Diabetic Retinopathy Identification from Eye Fundus images using Deep Features

Diabetes  mellitus can cause diabetic retinopathy (DR), which affects the blood vessel networks in the retina of the eye. The symptoms of diabetic retinopathy may be missing or minimal. For the majority of diabetes patients, a serious problem can damage their vision. It takes a lot of effort for competent doctors to identify lesions in the color-fundus pictures that can be used to accurately diagnose the illness required for diabetic retinopathy diagnosis. The existing Diabetic retinopathy therapies can only slow or delay vision degeneration, highlighting the significance of routine scanning with very effective automatic detection techniques to identify patients early. Therefore, early symptom detection may help prevent blindness. The proposed work aimed to create an automated model for recognizing the initial stages of DR detection using retinal pictures. This research paper presents a novel approach to the multi-classification of Diabetic Retinopathy (DR) based on a combination of deep learning and machine learning techniques. Our proposed model incorporates a Convolutional Neural Network (CNN) with an attention mechanism, allowing for the assignment of weights to extracted features depending on their relevance to the classification task. We employ Non-Negative Matrix Factorization (NMF) to further optimize feature selection to identify the most informative features from weighted representations. Then, the input features are classified using a machine learning classifier based on severity levels. The proposed model is assessed using four distinct ML classifiers (Support Vector Machine (SVM), Decision Tree, Naive Bayes, and KNN) and two publicly accessible databases (DDR and APTOS-Kaggle). For model evaluation, FPR, Specificity, Sensitivity, Precision, false positive rate, and Accuracy are selected.  The proposed model's accuracy on DDR is 89.29%, whereas Aptos Kaggle's accuracy on DR grading is 84.1%. KNN classifier performed better than all other classifiers on DDR and Aptos Kaggle datasets with an average accuracy of 89.55%, and 85.78 %respectively for multiclass classification. The findings of the evaluation and experimentation demonstrate that the suggested approach is effective for DR grading accuracy and disease diagnosis at an early stage

Typical nature of the draft and vertical force on the double disc furrow opener in paddy soil.

<p>The blue line represents vertical force and red line corresponds to the draft force.</p

Effect of depth and speed on the straw cutting (%).

<p>The blue diamonds, red squares and green triangles correspond to speed of the tool as 0.1m/s, 0.2 m/s and 0.3 m/s respectively.</p

(a) Test bench with power source (b) Data aqusition system with data acquisition card.

<p>(a) Test bench with power source (b) Data aqusition system with data acquisition card.</p