Rapidly rising population and climate changes are two critical issues that require immediate action to achieve sustainable development goals. The rising population is posing increased demand for food, thereby pushing for an acceleration in agricultural production. Furthermore, increased anthropogenic activities have resulted in environmental pollution such as water pollution and soil degradation as well as alterations in the composition and concentration of environmental gases. These changes are affecting not only biodiversity loss but also affecting the physio-biochemical processes of crop plants, resulting in a stress-induced decline in crop yield. To overcome such problems and ensure the supply of food material, consistent efforts are being made to develop strategies and techniques to increase crop yield and to enhance tolerance toward climate-induced stress. Plant breeding evolved after domestication and initially remained dependent on phenotype-based selection for crop improvement. But it has grown through cytological and biochemical methods, and the newer contemporary methods are based on DNA-marker-based strategies that help in the selection of agronomically useful traits. These are now supported by high-end molecular biology tools like PCR, high-throughput genotyping and phenotyping, data from crop morpho-physiology, statistical tools, bioinformatics, and machine learning. After establishing its worth in animal breeding, genomic selection (GS), an improved variant of marker-assisted selection (MAS), has made its way into crop-breeding programs as a powerful selection tool. To develop novel breeding programs as well as innovative marker-based models for genetic evaluation, GS makes use of molecular genetic markers. GS can amend complex traits like yield as well as shorten the breeding period, making it advantageous over pedigree breeding and marker-assisted selection (MAS). It reduces the time and resources that are required for plant breeding while allowing for an increased genetic gain of complex attributes. It has been taken to new heights by integrating innovative and advanced technologies such as speed breeding, machine learning, and environmental/weather data to further harness the GS potential, an approach known as integrated genomic selection (IGS). This review highlights the IGS strategies, procedures, integrated approaches, and associated emerging issues, with a special emphasis on cereal crops. In this domain, efforts have been taken to highlight the potential of this cutting-edge innovation to develop climate-smart crops that can endure abiotic stresses with the motive of keeping production and quality at par with the global food demand.

Arsenic (As) is a metalloid prevalent mainly in soil and water. The presence of As above permissible levels becomes toxic and detrimental to living organisms, therefore, making it a significant global concern. Humans can absorb As through drinking polluted water and consuming As-contaminated food material grown in soil having As problems. Since human beings are mobile organisms, they can use clean uncontaminated water and food found through various channels or switch from an As-contaminated area to a clean area; but plants are sessile and obtain As along with essential minerals and water through roots that make them more susceptible to arsenic poisoning and consequent stress. Arsenic and phosphorus have many similarities in terms of their physical and chemical characteristics, and they commonly compete to cause physiological anomalies in biological systems that contribute to further stress. Initial indicators of arsenic’s propensity to induce toxicity in plants are a decrease in yield and a loss in plant biomass. This is accompanied by considerable physiological alterations; including instant oxidative surge; followed by essential biomolecule oxidation. These variables ultimately result in cell permeability and an electrolyte imbalance. In addition, arsenic disturbs the nucleic acids, the transcription process, and the essential enzymes engaged with the plant system’s primary metabolic pathways. To lessen As absorption by plants, a variety of mitigation strategies have been proposed which include agronomic practices, plant breeding, genetic manipulation, computer-aided modeling, biochemical techniques, and the altering of human approaches regarding consumption and pollution, and in these ways, increased awareness may be generated. These mitigation strategies will further help in ensuring good health, food security, and environmental sustainability. This article summarises the nature of the impact of arsenic on plants, the physio-biochemical mechanisms evolved to cope with As stress, and the mitigation measures that can be employed to eliminate the negative effects of As.

In order to sustain life and promote good health, it is essential to have access to adequate quantities of safe and healthy foods. Globally, food contamination affects over 600 million individuals and kills almost 420,000 people annually. Food safety is a scientific approach that describes how to handle, prepare, and store food judiciously to reduce the risk of food-borne illness. Numerous contaminants pose a serious threat to food safety, and these include physical, chemical, and biological contaminants. Risk assessment deals with scientific analysis of known or probable adverse health consequences brought on by human exposure to food-borne risks, according to Codex Alimentarius. It offers a neutral scientific foundation for decision-making to guarantee the safety of the food supply. Methods of risk assessment and management to validate food safety can be improved by establishing standard protocols and policies for food traded nationally and internationally. This chapter highlights how risk assessment can be used to identify significant knowledge gaps. Characterization of the most significant risk factors in food production systems and implementation of risk reduction strategies to establish and secure human health are discussed. Additionally, various steps leading to food safety have been discussed in detail. <!----> <!----> <!----> <!---->