Plants are sessile in nature and phenotypic developmental plasticity has an important role in plant–environment interactions under fluctuating climatic situations. Plants are very sensitive to these circumstances and endeavor to acclimatize or adapt via modulating their phenotypic and genotypic characteristics. In this aspect, the development of climate-resilient crops is essential to accelerate production and meet global food security. These goals can be achieved by the application of high-throughput phenotyping, molecular breeding, and new advance biotechnological approaches, which will hasten the breeding cycle of a crop plant. Recent researches suggested 2that high-throughput phenotyping, micro-RNA-mediated developmental plasticity, phytohormones signaling, circadian clock, the molecular basis of eco-evolutionary phenological diversified functional traits, prediction of genotypic × environment interactions through next-generation sequencing and molecular markers, growth and development modeling, bioinformatics and omics approaches accelerates can be useful for deep understanding of plant–environment interaction. Therefore, considering before mentioned this chapter elaborates on crucial mechanisms (plant physiological, biochemical, genetical, molecular, and evolutionary) for further understanding of plant– environment interactions and developing climate resilient and smart crop varieties under extreme climatic events.

Light is crucial environmental factor for primary resource and signalling in plants and provide optimum fitness under fluctuating environments from millions of year. However, due to urbanization, and human development activities lot of excess light generated in environment during night time and responsible for anthropogenic generated pollution (ALAN; artificial night light pollution). This pollution has cause for serious problem in plants as it affects their processes and functions which are under the control of light or diurnal cycle. Plant biorhythms mostly diurnal rhythms such as stomatal movements, photosynthetic activity, and many more metabolic processes are under the control of period of light and dark, which are crucially affected by artificial light at night. Similarly, the crucial plant processes such as pollination, flowering, and yield determining processes are controlled by the diurnal cycle and ALAN affects these processes and ultimately hampers the plant fitness and development. To keep in mind the effect of artificial light at night on plant biorhythm and eco-physiological processes, this chapter will focus on the status of global artificial night light pollution and the responsible factors. Further, we will explore the details mechanisms of plant biorhythm and eco-physiological processes under artificial light at night and how this mechanism can be a global threat. Then at the end we will focus on the ANLP reducing strategies such as new light policy, advanced lightening technology such as remote sensing and lightening utilisation optimisation.

Uptake of excess iron by lowland rice plants causes iron toxicity, which is a major problem in the affected areas. This study investigated molecular diversity, genetic structure, and marker–trait associations for tolerance to iron toxicity in a panel of germplasm lines using microsatellite markers. The studied population showed a moderate to high degree of genetic diversity, as revealed by the estimated molecular diversity parameters and principal component, cluster and box plot analyses. The landraces Mahipal, Dhusura, Dhabalabhuta, Champa, Sunapani and Kusuma were identified as suitable for cultivation in the areas affected by high iron levels. The landraces Dhusura, Kusuma, Kendrajhali, Ranisaheba, Panjabaniswarna, Mahipal, Dhinkisiali, Champa, Kalamara and Ratanmali, which showed low scores for tolerance, were considered good donors for iron toxicity tolerance improvement programs. Utilizing STRUCTURE software, a total of four genetic structure groups were detected in the panel germplasm of lines. These structural subgroups exhibited good correlations among their members for iron toxicity tolerance and other yield-related traits. Marker–trait association analysis validated the reported iron toxicity tolerance QTLs qFeTox 4.2 and qFeTox 4.3, which are useful for marker-assisted improvement. A new QTL, qFeTox 7.1, located on chromosome 7, was detected as controlling iron toxicity tolerance in rice.