Nanomaterials and biochar mediated remediation of emerging contaminants.

The unrestricted release of various toxic substances into the environment is a critical global issue, gaining increased attention in modern society. Many of these substances are pristine to various environmental compartments known as contaminants/emerging contaminants (ECs). Nanoparticles and emerging sorbents enhanced remediation is a compelling methodology exhibiting great potential in addressing EC-related issues and facilitating their elimination from the environment, particularly those compounds that demonstrate eco-toxicity and pose considerable challenges in terms of removal. It provides a novel technique enabling the secure and sustainable removal of various ECs, including persistent organic compounds, microplastics, phthalate, etc. This extensive review presents a critical perspective on the current advancements and potential outcomes of nano-enhanced remediation techniques such as photocatalysis, nano-sensing, nano-enhanced sorbents, bio/phyto-remediation, which are applied to clean-up the natural environment. In addition, when dealing with residual contaminants, special attention is paid to both health and environmental implications; therefore, an evaluation of the long-term sustainability of nano-enhanced remediation methods has been considered. The integrated mechanical approaches were thoroughly discussed and presented in graphical forms. Thus, the critical evaluation of the integrated use of most emerging remediation technologies will open a new dimension in environmental safety and clean-up program.

Plant breeding for harmony between sustainable agriculture, the environment, and global food security: an era of genomics-assisted breeding.

MAIN CONCLUSION: Genomics-assisted breeding represents a crucial frontier in enhancing the balance between sustainable agriculture, environmental preservation, and global food security. Its precision and efficiency hold the promise of developing resilient crops, reducing resource utilization, and safeguarding biodiversity, ultimately fostering a more sustainable and secure food production system. Agriculture has been seriously threatened over the last 40 years by climate changes that menace global nutrition and food security. Changes in environmental factors like drought, salt concentration, heavy rainfalls, and extremely low or high temperatures can have a detrimental effects on plant development, growth, and yield. Extreme poverty and increasing food demand necessitate the need to break the existing production barriers in several crops. The first decade of twenty-first century marks the rapid development in the discovery of new plant breeding technologies. In contrast, in the second decade, the focus turned to extracting information from massive genomic frameworks, speculating gene-to-phenotype associations, and producing resilient crops. In this review, we will encompass the causes, effects of abiotic stresses and how they can be addressed using plant breeding technologies. Both conventional and modern breeding technologies will be highlighted. Moreover, the challenges like the commercialization of biotechnological products faced by proponents and developers will also be accentuated. The crux of this review is to mention the available breeding technologies that can deliver crops with high nutrition and climate resilience for sustainable agriculture.

Optimizing the phosphorus use in cotton by using CSM-CROPGRO-cotton model for semi-arid climate of Vehari-Punjab, Pakistan.

Crop nutrient management is an essential component of any cropping system. With increasing concerns over environmental protection, improvement in fertilizer use efficiencies has become a prime goal in global agriculture system. Phosphorus (P) is one of the most important nutrients, and strategies are required to optimize its use in important arable crops like cotton (Gossypium hirsutum L.) that has great significance. Sustainable P use in crop production could significantly avoid environmental hazards resulting from over-P fertilization. Crop growth modeling has emerged as an effective tool to assess and predict the optimal nutrient requirements for different crops. In present study, Decision Support System for Agro-technology Transfer (DSSAT) sub-model CSM-CROPGRO-Cotton-P was evaluated to estimate the observed and simulated P use in two cotton cultivars grown at three P application rates under the semi-arid climate of southern Punjab, Pakistan. The results revealed that both the cultivars performed best at medium rate of P application (57 kg ha-1) in terms of days to anthesis, days to maturity, seed cotton yield, total dry matter production, and harvest index during 2013 and 2014. Cultivar FH-142 performed better than MNH-886 in terms of different yield components. There was a good agreement between observed and simulated days to anthesis (0 to 1 day), days to maturity (0 to 2 days), seed cotton yield, total dry matter, and harvest index with an error of -4.4 to 15%, 12-7.5%, and 13-9.5% in MNH-886 and for FH-142, 4-16%, 19-11%, and 16-8.3% for growing years 2013 and 2014, respectively. CROPGRO-Cotton-P would be a useful tool to forecast cotton yield under different levels of P in cotton production system of the semi-arid climate of Southern Punjab.