Weeds are the most severe and widespread biological constraint on agricultural production systems and cause damage to cropped and non-cropped lands. They reduce crop yield and degrade the quality of the produce, besides raising the cost of production. The intensification of agriculture in the Green Revolution era attracted chemical fertilizers and dwarf varieties coupled with mono-cropping and irrigation practices, which enhanced crop-associated weeds and the widespread use of herbicides for easy control. Pesticides may kill many organisms, both target and non-target species, in the environment, causing an imbalance in the ecosystem. Despite the significant increase in productivity, the environmental repercussions of industrial agriculture, characterized by the use of high-yielding crop varieties and the extensive application of chemical fertilizers and pesticides, have prompted a quest for more sustainable agricultural practices worldwide. One potential alternative lies in innovative approaches that draw upon ecological insights gleaned from studying natural ecosystems. These approaches aim to create “ecologically intensive” agro-ecosystems. Developing ecologically intensive agro-ecosystems necessitates a deep understanding of the biological dynamics within ecosystems and the integration of traditional agricultural knowledge held by local farmers. Considering the potentiality of appropriate weed management technologies to substantially improve crop productivity, there is an opportunity for the development, popularization, and adoption of effective, economical, and eco-friendly weed management technologies.

Intensive cultivation and excess chemical fertilizer continuous tillage activity have shown that environmental, soil & water degradation in South Asia has produced serious problems in soil health or agricultural development with a rise in population. The desire for renewable alternatives has therefore been underestimated. The effect on cropping efficiency, machine productivity and development economy of two tillage cum (Vermicompost and FYM manure, Urea, and DAP) or two facts regarding the application of foliar spray and without zinc fertilizers were evaluated. Conventional tillage (1 ploughing by tractor drawn disc plough + 2 harrowing + 1 fb cultivator with planking) increased grain yield (10.85 percent) and (7.21), both during the first and second years of experimental plots, over minimum tillage (1 ploughing by tractor drawn rotavator) (MT). The improved grain output of wheat was primarily due to increased tiller development in CT treatments during both the years. Similarly, maximum most of the growth attributes, productivity components and physical quality charcters were recorded in CT tillage practice. In the joint management of inorganic or organic nitrogen, significant and maximum grain (4.63 t/ha) and straw (8.97 t/ha) yield, weight of spike (2.68 g), length of grain (6.49 mm), breadth of grain (3.29 mm) and length: breadth ratio of grain (1.98) were recorded during 2015-16, However purely chemical fertilizer applied treatment recorded during first year significant and maximum number of tillers per hill (3.14), leaf area index (2.31), plant dry matter (13.09 g plant^-1), grain yield (4.00 t ha^-1), straw yield (7.87 t ha^-1), number of grains per spike (42.42) and weight of spike (2.62 g), respectively.Soil cultivation by CT with fertilized fertilizer at the prescribed total dose of nitrogen 120 kg/ha, in which ½ nitrogen through organic (Vermicompost 3000 kg/ha) and ½ through inorganic (Urea, 117.69 kg/ha and (Diammonium phosphate (DAP) 32.60 kg/ha) during second year with foliar applications of zinc (2.50 kg/ha) were found to increase crop productivity and resilience in management.Soil chemical quality status increased after second year of experiment in combined used of MT (1 ploughing by tractor drawn rotavator) and organic (Vermicompost 4500 kg/ha) and inorganic fertilization ½ through inorganic (Urea, 44.16 kg/ha and (Diammonium phosphate (DAP) 48.91kg/ha) with foliar applications of zinc (2.50 kg/ha).

Background: The highly contagious Co rona vi rus d isease (COVID-19) pandemic affected nearly all nations across the world. It was emerged as most swiftly affected disease across the world and more than 2934 lakhs population suffered in four months of the time period as on date April 26, 2020. Its first epicenter was at Wuhan city of China during the month of December 2019. Currently, the most affected people and new epicenter of Coronavirus is at the United States of America (USA). Various nation’s administration including the India government called for the regional and local lockdown. We predicted the confirmed COVID-19 cases for next May-2020 month, map the magnitude of COVID-19 disease for Indian states and model the paucity of COVID-19 disease with statistical confirmatory data analysis model for declining rate for the cases represented for the Indian proportion of population. Method: The ARIMA model used to predict for next short-term cases, based moving average of past confirmed cases. The restriction of COVID-19 pandemic disease analyzed with predicted cases for month May 2020 data at 95 percent confidence is more than 2.5 lakh cases. Results: The confirmatory data analysis model for the time estimation for the paucity of cases it takes in between six to eighteen months of time frame. The Confirmatory model which considers recovery rate, social, economic and government policy. To complete recovery from the COVID-19 cases it takes on an average more than next ten months. Conclusion: The disease impacts also depend upon administrative and local people support for self-quarantine and other measures. The India nation Gross Domestic Product (GDP) based on more than 17% of its agriculture production, due to longer affect of the disease and extended lockdown period it will be severely affected. However, all the economic activities with full of its intensity takes-up after complete paucity of COVID-19 disease spread. Keywords: SARS-CoV-2; Lockdown; GDP; Nobel-Corona; Confirmatory data model