Identifying resource-conscious and low-carbon agricultural development pathways through land use modelling.

Increasing agricultural production with current resources and technology may lead to increased GHG emissions. Additionally, large population countries like India face substantial challenges in terms of food demand, agro-ecological heterogeneity, carbon footprint and depleting natural resources, thus increasing the decision complexities for policymakers and planners. We aim to examine the potential of producing more food from available agricultural land with low-carbon (reduced GHG emissions) and resource-conscious (optimal resource use) options.

Unraveling the access to the regioselective synthesis of highly functionalized pyranopyrazoles using an ionic liquid catalyst.

An efficient and green strategy for the regioselective synthesis of highly functionalized pyranopyrazole via one-pot condensation of 3-methyl-1-phenyl-5-pyrazolone or EAA and hydrazine hydrate, substituted aromatic aldehydes with NMSM [(E)-N-Methyl-1-(methylthio)-2-nitro-ethenamine] in the existence of IL [(EMIM)Ac] as catalyst with solvent-free condition (SFC) is described. This domino protocol produces biologically substantial heterocycles through Knoevenagel condensation proceeded by Michael addition and O-cyclization with an eradication of methanethiol group, which create the one stereo-center and creation of "C-C, C-N, C-O, C=C, C=N, bonds." The final product is produced by exceptionally easy filtering after the reaction mass was triturated with ethanol.

A new two-decade (2001-2019) high-resolution agricultural primary productivity dataset for India.

The present study describes a new dataset that estimates seasonally integrated agricultural gross primary productivity (GPP). Several models are being used to estimate GPP using remote sensing (RS) for regional and global studies. Using biophysical and climatic variables (MODIS, SBSS, ECWMF reanalysis etc.

Evaluation of multiple satellite precipitation products for rainfed maize production systems over Vietnam.

High-resolution reliable rainfall datasets are vital for agricultural, hydrological, and weather-related applications. The accuracy of satellite estimates has a significant effect on simulation models in particular crop simulation models, which are highly sensitive to rainfall amounts, distribution, and intensity. In this study, we evaluated five widely used operational satellite rainfall estimates: CHIRP, CHIRPS, CPC, CMORPH, and GSMaP.