Salinization of soils and freshwater resources by natural processes and/or human activities has become an increasing issue that affects environmental services and socioeconomic relations. In addition, salinization jeopardizes agroecosystems, inducing salt stress in most cultivated plants (nutrient deficiency, pH and oxidative stress, biomass reduction), and directly affects the quality and quantity of food production. Depending on the type of salt/stress (alkaline or pH-neutral), specific approaches and solutions should be applied to ameliorate the situation on-site. Various agro-hydrotechnical (soil and water conservation, reduced tillage, mulching, rainwater harvesting, irrigation and drainage, control of seawater intrusion), biological (agroforestry, multi-cropping, cultivation of salt-resistant species, bacterial inoculation, promotion of mycorrhiza, grafting with salt-resistant rootstocks), chemical (application of organic and mineral amendments, phytohormones), bio-ecological (breeding, desalination, application of nano-based products, seed biopriming), and/or institutional solutions (salinity monitoring, integrated national and regional strategies) are very effective against salinity/salt stress and numerous other constraints. Advances in computer science (artificial intelligence, machine learning) provide rapid predictions of salinization processes from the field to the global scale, under numerous scenarios, including climate change. Thus, these results represent a comprehensive outcome and tool for a multidisciplinary approach to protect and control salinization, minimizing damages caused by salt stress.

The integrated crop–livestock system (ICLS) is a farming strategy that helps to sustain agrobiodiversity, ecosystem services, and restores environmental sustainability. Furthermore, ICLS provides food and nutritional security to the small and marginal farmers in developing nations. In this context a mass-balanced ecosystem model was constructed for a smallholder ICLS along the Indian west coast to analyze the agro-ecological performance in terms of sustainability, resource use, nutrient balance and recycling. Thirteen functional groups were defined in the ICLS model with trophic levels ranging from 1.00 (detritus and benthic nitrogen fixers) to 3.00 (poultry and ruminants). The total system throughput index was estimated to be 1134.9 kg N ha⁻¹ year⁻¹ of which 60% was from consumption, 15% from exports, 10% from respiration, and the remaining 15% eventually flowing into detritus. The gross efficiency of the ecosystem was estimated to 0.3, which indicated higher growth rates and low maintenance energy costs. The higher food self-sufficiency ration of 7.4 indicated the integration of crop–livestock as an imperative system to meet the food and nutritional requirement of the farm family. The indices such as system overhead (60%), Finn’s cycling index (16.6) and mean path length (3.5) denoted that the ICLS is a small, resource-efficient, stable, maturing and sustainable ecosystem in terms of the ecosystem principles and recycling. The present model will serve as the first model on the ICLS from the humid tropics and will help in the evaluation of the other agro-ecological systems using the Ecopath modelling approach. In conclusion, farm intensification through crop and animal diversification has the highest impact on farm productivity, food self-sufficiency and resource-use-efficiency of the smallholder’s livelihood security.

Salt stress is a major abiotic stress affecting the productivity of rice crop worldwide. This study screened a set of 71 rice genotypes collected from coastal parts of Goa and Karnataka states in India for seedling stage salinity tolerance to identify genotypes alternative to standard salt-tolerant donors Pokkali, FL478, etc. Phenotyping for seedling stage tolerance was carried out under micro plots at an induced salinity of 12 dS/m. For haplotyping, 14SaltolQTL linked simple sequence repeat (SSR) markers on chromosome 1 were utilized. On the basis of the response to salt stress, 10 genotypes were found tolerant, 16 moderately tolerant, 29 sensitive and 15 as highly sensitive. Among the SSR markers, marker RM10871 was the most polymorphic with a polymorphic information content of 0.90, exhibiting 14 different alleles followed by RM10793 (0.84) and RM3412 (0.80) with 8 and 7 alleles, respectively. These markers also exhibited high values for the effective number of alleles (Ne) and gene diversity (I). The haplotype analysis revealed that the allelic constitution of theSaltolregion of 10 tolerant genotypes from our study varied in comparison to the reference tolerant check FL478. Further, the haplotype of three tolerant genotypes, namely, Goa Dhan 2, Panvel 1 and Goa wild rice (GWR) 005 appears to be completely different from the FL478 haplotype indicating tolerance in these genotypes is controlled by genomic region other thanSaltol.These three genotypes with probable novel regions for seedling stage salt tolerance can be considered for enhancing salinity tolerance of rice cultivars.

Crop diversification is essential in lowland rice cropping systems to achieve sustainability, improve soil health, and as a climate-resilient practice to reduce greenhouse gas (GHG) emissions. A life cycle assessment (LCA) was conducted for the farms in the west-coast region of India to assess the environmental impact of the rice–rice and rice–cowpea cropping systems. The life cycle impact assessment (LCIA) was evaluated in a “cradle-to-gate” perspective. A higher energy consumption was found in the rice–rice system (32,673 vs. 18,197 MJ/ha), while the net energy output was higher in the rice–cowpea system (211,071 vs. 157,409 MJ/ha). Energy consumption was 44% lower in the rice–cowpea system, which was coupled with a higher energy efficiency (11.6 vs. 4.8), attributed to the lower energy consumption and the higher energy output. Further, the results indicated an energy saving potentialin the rice–cowpea system due to the higher use of renewable resources such as farmyard manure. Field emissions, fertilizer production, and fuel consumption were the major contributors to the greenhouse gas (GHG) emissions in both cropping systems. The total GHG emissions were 81% higher in the rice–rice system (13,894 ± 1329 kg CO₂ eq./ha) than in the rice–cowpea system (7679 ± 719 kg CO₂ eq./ha). The higher GHG emissions in the rice–rice system were largely due to the higher use of fertilizers, diesel fuel, and machinery. Hence, diversifying the winter rice with a cowpea crop and its large-scale adoption on the west coast of India would provide multiple benefits in decreasing the environmental impact and improving the energy efficiency to achieve sustainability and climate resilience in rice-based cropping systems.