Intensive agriculture is based on the use of high-energy inputs and quality planting materials with assured irrigation, but it has failed to assure agricultural sustainability because of creation of ecological imbalance and degradation of natural resources. On the other hand, intercropping systems, also known as mixed cropping or polyculture, a traditional farming practice with diversified crop cultivation, uses comparatively low inputs and improves the quality of the agro-ecosystem. Intensification of crops can be done spatially and temporally by the adoption of the intercropping system targeting future need. Intercropping ensures multiple benefits like enhancement of yield, environmental security, production sustainability and greater ecosystem services. In intercropping, two or more crop species are grown concurrently as they coexist for a significant part of the crop cycle and interact among themselves and agro-ecosystems. Legumes as component crops in the intercropping system play versatile roles like biological N fixation and soil quality improvement, additional yield output including protein yield, and creation of functional diversity. But growing two or more crops together requires additional care and management for the creation of less competition among the crop species and efficient utilization of natural resources. Research evidence showed beneficial impacts of a properly managed intercropping system in terms of resource utilization and combined yield of crops grown with low-input use. The review highlights the principles and management of an intercropping system and its benefits and usefulness as a low-input agriculture for food and environmental security.

In the face of aggravating environmental challenges, achieving food security while preserving natural ecosystems, the present-day agriculture demands transformative strategies. Intercropping, an age old yet under-recognized practice, offers a promising direction towards sustainable agriculture by elevating biodiversity, optimizing resource use and delivering critical ecosystem services. Intercropping contributes to climate change mitigation by improving soil health and carbon sequestration, reducing greenhouse gas emissions and long-term soil fertility restoration through nutrient cycling. Intercropping system aligns with agroecology principles, integrating biodiversity and ecosystem services into agricultural systems. Intercropping enhances provisioning, regulating, supporting, and cultural ecosystem services through multiple mechanisms. One of its key advantages is the promotion of biodiversity, which is essential for agroecosystem sustainability. By increasing species richness, intercropping nurtures pollinators, beneficial insects, and microbial communities, ultimately boosting productivity and resilience against environmental stressors. Moreover, intercropping represents an ecologically and economically viable alternative to conventional farming, confronting critical global concerns such as soil degradation, biodiversity loss, and climate change. However, challenges such as choosing compatible crops, planning planting patterns, and coordinating harvest schedules pose huge tasks. Research findings on crop combinations, climate-resilient systems, mechanization tools, and region-specific information can help to overcome these issues. The review article focuses on the alignment of an intercropping system with ecosystem services targeting agricultural sustainability.

Rice holds key importance in food and nutritional security across the globe. Nutrient management involving rice has been a matter of interest for a long time owing to the unique production environment of rice. In this research, an artificial neural network-based prediction model was developed to understand the role of individual nutrients (N, P, K, Zn, and S) on different plant parameters (plant height, tiller number, dry matter production, leaf area index, grain yield, and straw yield) of rice. A feed-forward neural network with back-propagation training was developed using the neural network (nnet) toolbox available in Matlab. For the training of the model, data obtained from two consecutive crop seasons over two years (a total of four crops of rice) were used. Nutrients interact with each other, and the resulting effect is an outcome of such interaction; hence, understanding the role of individual nutrients under field conditions becomes difficult. In the present study, an attempt was made to understand the role of individual nutrients in achieving crop growth and yield using an artificial neural network-based prediction model. The model predicts that growth parameters such as plant height, tiller number, and leaf area index often achieve their maximum performance at below the maximum applied dose, while the maximum yield in most cases is achieved at 100% N, P, K, Zn, and S dose. In addition, the present study attempted to understand the impact of individual nutrients on both plant growth and yield in order to optimize nutrient recommendation and nutrient management, thereby minimizing environmental pollution and wastage of nutrients.

Present-day agriculture is under tremendous pressure due to various factors such as climate change, degradation of soil and water quality, and yield plateauing of major food crops. Under these scenarios, there is an urgent need to choose a climate-resilient and ecologically hardy crop which can perform under adverse conditions with low input requirements. In this regard, millets can be suitable crops for agricultural sustainability. Among various millets, finger millet (Eleusine coracana L. Gaertn) is cultivated mainly in India and Africa. However, most farmers grow finger millet with local cultivars, and improved ones can be replaced to enhance productivity. The present investigation conducted at the Post Graduate Research Farm of Centurion University of Technology and Management, Odisha, focused on evaluating suitable cultivars of finger millet. The study revealed that cultivars significantly influenced finger millet growth, productivity, and economics. The physiological growth parameters, namely, crop growth rate, relative growth rate, net assimilation rate and leaf area duration were significantly influenced by finger millet cultivars. The growing degree days (GDD), helio-thermal units (HTU) and photothermal units (PTU) of the finger millet showed a great variation among the cultivars. The Maximum total GDD (2169 °C day), HTU (18141 °C day hours) and PTU (24297 °C day hours) were recorded in the cultivar Hima(w) VR 936. The cultivars Indravathi VR 1101, Sri Chaitanya VR 847 (1.73) and Hima (W) VR 936 (1.60) were superior to other cultivars in expression of the grain yield and economics of finger millet. The study concluded that the cultivation of Indravathi and Sri Chaitanya could be considered as short-duration cultivars; however, Hima can be chosen as long duration crop for successful finger millet cultivation with higher net returns and benefit-cost ratio under hot and sub-humid regions of Odisha.