Mulching: A viable option to increase productivity of field and fruit crops

Mulching plays an important role in production of agricultural and horticultural crops in the current scenario of declining water table, soil degradation and climate change. The main objectives of mulching are to prevent loss of water by evaporation, prevention of soil erosion, weed control, to reduce fertilizer leaching, to promote soil productivity, to enhance yield and quality of field and fruit crops. So, mulching is useful to save our underground water resource, soil and environment for sustainable crop production. In this review paper, the literature clearly shows pronounced effects of mulching on soil health by improving the soil structure, soil fertility, biological activities, avoid soil degradation in addition to moisture conservation, regulating temperature, encouraging change in favourable micro-climate, check weed growth and ultimately increasing the productivity, quality, profitability and sustainability of crops and cropping systems irrespective of the system/situation

COMPARATIVE ANALYSIS OF SENSILLA ON ANTENNAE AND MOUTHPARTS OF LARVAE IN TWO SPECIES OF DITRYSIAN MOTHS (LEPIDOPTERA)

Systematics encompasses two more narrowly defined but highly interdependent fields. The first is taxonomy and the second field is phylogenetics. In modern systematics, taxonomy aims to reflect evolutionary history. The morphological traits of immature stages remain largely unresolved for a vast majority of the lepidopteran species worldwide, although they have potential to be applied in lepidopteran classification and systematic studies. The larval instars in Lepidoptera are signature examples of agricultural pests. The present study deals with SEM investigation of ultrastructure of different instars of two lepidopteran pest species i.e., Somena scintillans Walker 1856 and Trabala vishnou Lefebvre 1827. These findings will not only help in enriching taxonomic database but will also act as an aid for future studies aimed at devising pest control methods

Studies on physico-mechanical properties of W. Murcott mandarin

The post-harvest physico-mechanical properties of fruits is important in adoption and design of varioushandling, packaging, storage and transportation systems. These are important for sizing and grading the fruit beforemarketing as well as demarcate their end use. Geometric, gravimetric and textural properties were determined forthe fresh samples of W. Murcottmandarin. The results show that W. Murcottfruit diameter varies from 81.82-68.97mm, equatorial length varies from 86.51-68.43 mm, and length varies from 61.33-52.08 mm. The specific mean areais 57.591 with the sphericity of 0.90. The L, a, b values were 53.37, 42.9 and 49.68 respectively. The firmness variedfrom 1.351-1.650 kgf. These physical attributes can be taken into consideration while designing the grading andprocessing equipment

Exogenous application of salicylic acid regulates antioxidant enzyme activities and quality attributes of Umran ber (Ziziphus mauritiana) fruits under cold storage

The present study was carried out to observe the influence of pre-harvest application of salicylic acid (1, 2 and 3 mM) on shelf life and quality attributes of ber fruits cv. Umran (Ziziphus mauritiana Lamk.) under cold storage conditions (7.5±10C and 90–95% RH). The cold-stored fruits were assessed for various physico-chemical attributes and enzymatic activities at 7 days interval up to 28 days of storage. Above study revealed that fruits treated with salicylic acid @3 mM resulted in reduced physiological loss in fruit weight, spoilage and increased firmness, soluble solids content, antioxidant activity and carotenoids. Furthermore, it suppressed activities of cell wall degrading enzymes like PG, PPO, PME and increased the activity of superoxide dismutase peroxidase and catalase enzymes. It was concluded that pre-harvest spray of salicylic acid @3 mM was more effective in regulating enzymatic activities, thereby improving quality attributes and shelf life of ber fruits up to 21 days at cold storage

A Hybrid Machine Learning Technique For Feature Optimization In Object-Based Classification of Debris-Covered Glaciers

Object-based features like spectral, topographic, and textural are supportive to determine debris-covered glacier classes. The original feature space includes relevant and irrelevant features. The inclusion of all these features increases the complexity and renders the classifier’s performance. Therefore, feature space optimization is requisite for the classification process. Previous studies have shown a rigorous exercise in manually selecting the best combination of features to define the target class and proven to be a time consuming task. The present study proposed a hybrid feature selection technique to automate the selection of the best suitable features. This study aimed to reduce the classifier’s complexity and enhance the performance of the classification model. Relief-F and Pearson Correlation filter-based feature selection methods ranked features according to the relevance and filtered out irrelevant or less important features based on the defined condition. Later, the hybrid model selected the common features to get an optimal feature set. The proposed hybrid model was tested on Landsat 8 images of debris-covered glaciers in Central Karakoram Range and validated with present glacier inventories. The results showed that the classification accuracy of the proposed hybrid feature selection model with a Decision Tree classifier is 99.82%, which is better than the classification results obtained using other mapping techniques. In addition, the hybrid feature selection technique has sped up the process of classification by reducing the number of features by 77% without compromising the classification accuracy

Pervasiveness and Epidemiological Profile of SARS-CoV-2 Infection among the Population of Majha Region of Punjab,India

Introduction: There are many types of coronaviruses that causes respiratory and intestinal infection in humans. Among these coronaviruses, is a group of Severe Acute Respiratory Syndrome (SARS)-like bat coronavirus, including both SARSCoV and SARS-Cov-2 that comprise a unique clade under the subgenus Sarbecovirus. The SARS-CoV-2 strains in India are more closely related to bat-CoVRaTG13 (93% homology) than pangolin CoV (83.5% homology). India reported its first case of Coronavirus Disease 19 (COVID-19) on January 30, 2020. Punjab, a state in northwestern India comprises of 22 districts which are classified into three major distinct regions viz. Majha, Malwa and Doaba. Four districts of Majha region of Indian state of Punjab are Amritsar, Tarn Taran, Gurdaspur and Pathankot. Aim: The present study describes the SARS-CoV-2 epidemiology based on samples tested for this virus; received at Viral Research and Diagnostic Laboratory (VRDL), Government Medical College, Amritsar-Punjab, India. Materials and Methods: This epidemiological study was designed taking into consideration three main factors i.e. the gender, the age groups and the factor whether the individual has any symptoms or not. To study their context of applicability and its interpretation, a total of 3,47,418 samples from period of 01st April 2020 to 31st October 2020 were included in this study. Ribonucleic Acid amplification by Reverse Transcriptase Polymerase Chain Reaction (RT-PCR) of SARS-CoV-2 from nasopharyngeal/oropharyngeal swabs of all individuals revealed confirmation of 17,920 positive samples. Total 2,29,310 males and 1,18,108 females were tested for the COVID-19 infection. Social science statistics online tool (https://www.socscistatistics.com/ tests/) was used for χ2 test to analyse different parameters. Results: Maximum number of COVID-19 positive patients was detected in 21 to 30 years age group (p<0.05). Highest positivity ratio of samples was observed in individuals exceeding the age of 50 years. Number of asymptomatic individuals was found to be quite higher than symptomatic individuals in total population. Overall percent positivity of asymptomatic individuals was 4.81% (p<0.00001), which accounts to 4.71% of total number of tested individuals in this study. Conclusion: COVID-19 is an evolving disease and data from this study elucidates the epidemiological profile of the SARSCoV-2 infection among population of Majha region of Punjab state of Indian subcontinent