Integrated farming systems (IFS) entail a holistic approach to farming aimed at meeting the multiple demands (impart farm resilience, farmer livelihoods, food security, ecosystem services, and making farms adaptive and resilient, etc.). IFS are characterized by temporal and spatial mixing of crops, livestock, fishery, and allied activities in a single farm. It is hypothesized that these complex farms are more productive at a system level, are less vulnerable to volatility, and produce less negative externalities than simplified farms. Thereby, they cater the needs of small and marginal farmers, who are the backbone of agriculture in India. Our review of literature shows that IFS have the potential to improve farm profitability (265%) and employment (143%) compared to single enterprise farms. The literature showed that IFS enhance nutrient recycling through composting, mulching, and residue incorporation and, as a consequence, have the capacity to reduce the external purchase of inputs. The nutrient recycling in turn helps to increase the soil quality indicators such as soil nutrient availability and also improves soil microbial activity. The IFS play a major role in biodiversity conservation through adoption of diversified cropping system and through integration of indigenous livestock breeds. IFS also played important role in improving soil organic carbon from 0.75 to 0.82%. Due to increased carbon sequestration, biomass production by trees, reduced consumption of fertilizers, and pesticides the greenhouse gas emission could be reduced significantly. This results in a linked system making it sustainable and climate‐resilient. The main challenge associated with adoption of IFS is it requires skill, knowledge, resources, labor, and capital which are not always available with small and marginal farmers. There is a need for integrating productivity, profitability, and environmental sustainability variables in a single evaluation framework to effectively generate information toward enhancing adaptability of IFS.

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Adoption of an integrated farming system (IFS) is essential to achieve food and nutritional security in small and marginal holdings. Assessment of IFS to know the resource availability and socio-economic condition of the farm household, farm typology plays a critical role. In this regard, a sample survey of 200 marginal households practicing mixed crop-livestock agriculture was conducted during 2018–2019 at Southern Coastal Plains, which occupies 19,344 ha in Thiruvananthapuram district, Kerala, India. Farming system typology using multivariate statistical techniques of principal component analysis and cluster analysis characterized the diverse farm households coexisting within distinct homogenous farm types. Farming system typology identified four distinct farm types viz. resource constrained type-1 households with small land owned, high abundance of poultry, very low on-farm income, constituted 46.5%; resource endowed type-2 households oriented around fruit and vegetable, plantation crop, with a moderate abundance of large ruminant and poultry, high on-farm income, constituted 12.5%; resource endowed type-3 household oriented around food grain, extensive use of farm machinery, with a moderate abundance of large ruminant, low on-farm income, constituted 21.5%; and resource endowed type-4 household oriented around fodder, with high abundance of large ruminant, medium on-farm income, constituted 19.5% of sampled households. Constraint analysis using constraint severity index assessed the severity of constraints in food grain, horticulture, livestock, complementary and supplementary enterprises in each farm type, which allowed targeted farming systems interventions to be envisaged to overcome soil health problems, crops and animal production constraints. Farming system typology together with constraint analysis are therefore suggested as a practical framework capable of identifying type-specific farm households for targeted farming systems interventions.

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A coconut-based integrated farming system (IFS) model suited for lowlands was developed at the Integrated Farming System Research Station (IFSRS), Karamana, Kerala State, India, under Kerala Agricultural University. The area of the model was decided as 0.2 ha, matching the average per capita land availability of a marginal farmer in the State. Apart from the major crop coconut, intercrops, such as vegetables, fruit crops, spices, fodder and tuber crops were included in the model. The allied enterprises integrated were livestock, azolla, and agroforestry. Tree components of the model comprised of teak, jack, breadfruit, garcinia and mango. Research data for five years revealed that the model generated food products above the requirement of a four-member family, and the surplus production could contribute to farmer’s income. The productivity under the IFS model was enhanced ten-folds compared to that under the sole crop of coconut for the same area. Plant nutrients were generated within the farm through organic recycling, which contributed to the substantial saving of chemical fertilizers. The system was found climate-smart because of reduced use of chemical fertilizers and net negative emission of greenhouse gases mostly achieved through agroforestry. This IFS model could also ensure considerable employment generation. The model could be adopted by farmers of lowland tracts of Kerala having similar agro-climatic features for better economic returns and environmental benefits.

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A field investigation was carried out at the Instructional farm, College of Agriculture, Vellayani during 2000-2001 to assess the effect of spacing and weed management practices on the performance of basmati rice. The treatments comprised of three spacings (15x15, 20x10 and 15x10 cm) and five weed control treatments (weed free check, unweeded control, hand weeding twice at 20 and 40 DAT, anilofos+2,4-DEE (readymix) 0.40+0.53 kg ha at 6 DAT supplemented with hand weeding at 20 DAT and anilofos+2,4-DEE (readymix) 0.40+0.53 kg ha' at 6 DAT supplemented with 2,4-D sodium salt 1 kg ha at 20 DAT). Grasses were the predominant weed species observed in the experimental field. Unchecked weed competition reduced grain yield to the tune of 46%. Herbicides were most effective in controlling the weeds. The results revealed that with 20x1 Ocm spacing (50 hills m2), pre-emergence application of anilofos+2,4-DEE (readymix) 0.40+0.53 kg ha supplemented with 2,4-D sodium salt 1 kg ha¹ could result in maximum grain yield and minimum weed competition.