Predicting rainfall using machine learning, deep learning, and time series models across an altitudinal gradient in the North-Western Himalayas.

Predicting rainfall is a challenging and critical task due to its significant impact on society. Timely and accurate predictions are essential for minimizing human and financial losses. The dependence of approximately 60% of agricultural land in India on monsoon rainfall implies the crucial nature of accurate rainfall prediction.

Pollution indices of selected metals in tea (Camellia sinensis L.) growing soils of the Upper Assam region divulge a non-trifling menace of National Highway.

The study investigated the influence of a National Highway (NH) traversing tea estates (TEs) on heavy metal (HM) contamination in the top soils of Upper Assam, India. The dispersion and accumulation of six HMs, viz. cadmium (Cd), copper (Cu), iron (Fe), manganese (Mn), nickel (Ni), and zinc (Zn), within tea-growing soils were assessed using diverse indices: contamination factor (CF), degree of contamination (DC), enrichment factor (EF), geo-accumulation index (I), modified degree of contamination (MDC), Nemerow pollution index (PI), pollution load index (PLI), potential ecological risk factor (E), and potential ecological risk index (RI).

MethSemble-6mA: an ensemble-based 6mA prediction server and its application on promoter region of LBD gene family in Poaceae.

The Lateral Organ Boundaries Domain (LBD) containing genes are a set of plant-specific transcription factors and are crucial for controlling both organ development and defense mechanisms as well as anthocyanin synthesis and nitrogen metabolism. It is imperative to understand how methylation regulates gene expression, through predicting methylation sites of their promoters particularly in major crop species. In this study, we developed a user-friendly prediction server for accurate prediction of 6mA sites by incorporating a robust feature set, viz.

Big Data Analysis in Computational Biology and Bioinformatics.

Advancements in high-throughput technologies, genomics, transcriptomics, and metabolomics play an important role in obtaining biological information about living organisms. The field of computational biology and bioinformatics has experienced significant growth with the advent of high-throughput sequencing technologies and other high-throughput techniques. The resulting large amounts of data present both opportunities and challenges for data analysis.

The Level of Selected Metals in Made Tea and Tea Infusion from the Roadside Tea Plants and Health Risk Assessment.

The effects of human activities are becoming clearer every year, with multiple reports of struggling and eroded ecosystems resulting in new threats of plant and animal extinctions throughout the world. It has been speculated that roadside tea-growing soils impact on metal dynamics from soil to tea plants and subsequently to tea infusion which may be threatened by increasingly unpredictable and dangerous surroundings. Furthermore, heavy metals released from vehicles on the national highway (NH) could be a source of metal contamination in roadside tea soils and tea plants.

Change in the air due to the coronavirus outbreak in four major cities of India: What do the statistics say?

The onset of the novel Coronavirus (COVID-19) has impacted all sectors of society. To avoid the rapid spread of this virus, the Government of India imposed a nationwide lockdown in four phases. Lockdown, due to COVID-19 pandemic, resulted a decline in pollution in India in general and in dense cities in particular.

Estimation of Heritability under Correlated Errors Using the Full-Sib Model.

In plant and animal breeding, sometimes observations are not independently distributed. There may exist a correlated relationship between the observations. In the presence of highly correlated observations, the classical premise of independence between observations is violated.

Climate plays a dominant role over land management in governing soil carbon dynamics in North Western Himalayas.

The soil carbon (C) dynamics is strongly influenced by climate and land-use patterns in the Himalayas. Therefore, soils under five prominent land use [e.g.

Sick or rich: Assessing the selected soil properties and fertility status across the tea-growing region of Dooars, West Bengal, India.

Harnessing the potential yields of evergreen perennial crops like tea ( L.) essentially requires the application of optimum doses of nutrients based on the soil test reports. In the present study, the soil pH, organic carbon (OC), available potassium as KO (AK), and available sulphur (AS) of 7300 soil samples from 115 tea estates spread over the Dooars ranging from 88°52'E to 89°86'E longitude and 26°45'N to 27°00'N latitude of West Bengal, India have been documented.

Application of analytical hierarchical process, multi-influencing factor, and geospatial techniques for groundwater potential zonation in a semi-arid region of western India.

Groundwater resources are alarmingly depleting due to over-exploitation and significant climate changes over time. Therefore, demarcation of groundwater potential zones is essential for addressing the needs of various industries in semi-arid area. Depleting groundwater resources, topography, aquifer features and climatic factors make it necessary to demarcate ground water potential zones in semiarid region of Rajasthan.

Insights into the effects of tea pruning litter biochar on major micronutrients (Cu, Mn, and Zn) pathway from soil to tea plant: An environmental armour.

A field study was conducted from 0 to 360 days to investigate the effect of tea pruning litter biochar (TPLBC) on the accumulation of major micronutrients (copper: Cu, manganese: Mn, and zinc: Zn) in soil, their uptake by tea plant (clone: S.3 A/3) and level of contamination in soil due to TPLBC. To evaluate the level of contamination due to TPLBC, a soil pollution assessment was carried out using the geo-accumulation index (I), enrichment factor (EF), contamination factor (CF), potential ecological risk factor (PERF), individual contamination factor (ICF), and risk assessment code (RAC).

Land-use systems regulate carbon geochemistry in the temperate Himalayas, India.

The Himalayan ecosystem is critical for ecological security and environmental sustainability. However, continuous deforestation is posing a serious threat to Himalayan sustainability. Changing land-use systems exert a tenacious impact on soil carbon (C) dynamics and regulate C emissions from Himalayan ecosystem.

COVID-19 and prices of pulses in Major markets of India: Impact of nationwide lockdown.

The COVID-19 pandemic has impacted almost all the sectors including agriculture in the country. The present paper investigates the impact of COVID-19 induced lockdown on both wholesale and retail prices of major pulses in India. The daily wholesale and retail price data on five major pulses namely Lentil, Moong, Arhar, Urad and Gram are collected for five major markets in India namely Delhi, Mumbai, Kolkata, Chennai and Hyderabad during the period January, 2019 to September, 2020 from Ministry of Consumer Affairs, Food & Public Distribution, Government of India.

Machine learning techniques for forecasting agricultural prices: A case of brinjal in Odisha, India.

Background: Price forecasting of perishable crop like vegetables has importance implications to the farmers, traders as well as consumers. Timely and accurate forecast of the price helps the farmers switch between the alternative nearby markets to sale their produce and getting good prices. The farmers can use the information to make choices around the timing of marketing.

Bioefficacy evaluation of ferrocenyl chalcones against and infestation in tomato.

The present study reports, bioefficacy evaluation of effective compounds against and in pot cultured tomato. The identified five most effective compounds, i.e.