The inconsistency of the Indian monsoon has constantly threatened the country’s food production, especially key food crops such as rice. Crop planning measures based on rainfall patterns during the rice-growing season can significantly improve the sustainable water usage for water-intensive crops such as rice. This study examines the variability of Indian monsoonal rainfall in rainfed and irrigated rice-cultivating regions to improve rainfall utilization and irrigation water-saving practices. Two distinct rice-growing conditions in southern peninsular India are chosen for this study. The preliminary seasonal rainfall analysis (1951–2015) showed anomalies in the Sadivayal (rainfed rice) region compared to the Karaikal (irrigated rice). The dry-spell analysis and weekly rainfall classification suggested shifting the sowing date to earlier weeks for the Thaladi season (September–February) and Kar season (May–September) to avoid exposure to water stress in Sadivayal. Harvesting of excess rainwater during the wet weeks is proposed as a mitigation strategy for Karaikal during the vegetative stage of the Kuruvai season (June–October) and Late Thaladi season (October–February), where deficit rainfall is expected. Results showed that an adaptation strategy of early sowing is the most sustainable measure for rainfed rice cultivation. However, harvesting the excess rainwater is an ideal strategy to prevent water stress during deficient rainfall periods in irrigated rice farming. This comparative study proposes a comprehensive rainfall analysis framework to develop sustainable water-efficient rice cultivation practices for the changing rainfall patterns.

Weeds cause significant yield and economic losses by competing with crops and increasing production costs. Compounding these challenges are labor shortages, herbicide resistance, and environmental pollution, making weed management increasingly difficult. In response, precision weed control (PWC) technologies, such as robots and unmanned aerial vehicles (UAVs), have emerged as innovative solutions. These tools offer farmers high precision (±1 cm spatial accuracy), enabling efficient and sustainable weed management. Herbicide spraying robots, mechanical weeding robots, and laser-based weeders are deployed on large-scale farms in developed countries. Similarly, UAVs are gaining popularity in many countries, particularly in Asia, for weed monitoring and herbicide application. Despite advancements in robotic and UAV weed control, their large-scale adoption remains limited. The reasons for this slow uptake and the barriers to widespread implementation are not fully understood. To address this knowledge gap, our review analyzes 155 articles and provides a comprehensive understanding of PWC challenges and needed interventions for scaling. This review revealed that AI-driven weed mapping in robots and UAVs struggles with data (quality, diversity, bias) and technical (computation, deployment, cost) barriers. Improved data (collection, processing, synthesis, bias mitigation) and efficient, affordable technology (edge/hybrid computing, lightweight algorithms, centralized computing resources, energy-efficient hardware) are required to improve AI-driven weed mapping adoption. Specifically, robotic weed control adoption is hindered by challenges in weed recognition, navigation complexity, limited battery life, data management (connectivity), fragmented farms, high costs, and limited digital literacy. Scaling requires advancements in weed detection and energy efficiency, development of affordable robots with shared service models, enhanced farmer training, improved rural connectivity, and precise engineering solutions. Similarly, UAV adoption in agriculture faces hurdles such as regulations (permits), limited payload and battery life, weather dependency, spray drift, sensor accuracy, lack of skilled operators, high initial and operational costs, and absence of standardized protocol. Scaling requires financing (subsidies, loans), favorable regulations (streamlined permits, online training), infrastructure development (service providers, hiring centers), technological innovation (interchangeable sensors, multipurpose UAVs), and capacity building (farmer training programs, awareness initiatives).

Climate change elements including elevated atmospheric carbon dioxide (CO₂) concentration and soil salinity significantly impact weed biology and management. In this study, we evaluated the performance of a highly invasive plant species, parthenium weed (Parthenium hysterophorus L.) grown at various soil salinity levels (ranging from 0 to 16 dS m⁻¹) at two CO₂ concentrations (ambient: 400 ppm and elevated: 700 ppm). The CO₂ concentration and soil salinity individually affected various early growth attributes of parthenium weed. The interaction between CO₂ and salinity was significant for chlorophyll index, stem dry weight and phenolics content. Parthenium weed plants grew taller (13%), achieved greater leaf area (28%) and produced more dry weight (24%) when raised under elevated as compared with the ambient CO₂. Soil salinity had a dose-dependent, negative effect on various growth attributes, chlorophyll index, relative water content and phenolics content. Even the modest levels of salinity (4.2 to 4.6 dS m⁻¹) caused 50% reduction in dry weights of leaves, roots and whole plants. Sodium ion (Na⁺) concentration peaked at the highest salinity level (16 dS m⁻¹) as compared with the lower salinity levels (0 to 12 dS m⁻¹). Overall, salinity had a negative effect on different growth variables but elevated CO₂ improved growth and phenolics content regardless of the salt stress regime. Hence, parthenium weed could benefit from future atmospheric CO₂ concentration and may invade some salt-affected areas.

A field experiment was conducted to compare the Unmanned Aerial Vehicle (UAV) and knapsack herbicide application on the diverse weed flora, growth and yield attributes of dry-direct seeded rice in randomized block design replicated thrice during 2023 at Pandit Jawaharlal Nehru College of Agriculture & Research Institute, Karaikal, Puducherry UT, India. Grasses dominated the weed flora, with 80.5% relative density of Echinochloa colona. UAV spray volume at 50 L/ha with application of pendimethalin + penoxsulam on 3 DAS 625 g/ha fb bispyribac-sodium on 20 DAS 25 g/ha reduced total weed density (39.4/m²) and biomass (23.4 g/m²), resulted better rice growth (plant height and tillers/plant), yield parameters (panicle weight and 1000 grain weight) and yield (3.87 t/ha). Negative linear relationship was observed between rice grain yield and total weed biomass at harvest stage. Uncontrolled weeds caused 65.6% yield loss in dry-DSR of the coastal deltaic ecosystem.

A field experiment was conducted during October 2020–January 2021 at Pandit Jawaharlal Nehru College of Agriculture and Research Institute, Karaikal, Puducherry to study the effect of different seeding rates of [Sesbania bispinosa (Jacq.) W. Wight] (Sesbania) in rice co-culture along with suitable post-emergence herbicides for brown manuring on crop productivity and energetics in wet seeded rice (Oryza sativa L.). The experiment consisted of 10 treatments, viz. T1 ,Sesbania seeding rate for brown manuring (BM) @15 kg/ha with 2,4-D 0.5 kg/ha; T2 , Sesbania seeding rate for BM @20 kg/ha with 2,4-D 0.5 kg/ha; T3 , Sesbania seeding rate for BM @25 kg/ha with 2,4-D 0.5 kg/ha; T4 , Sesbania seeding rate for BM @15 kg/ha with bispyribac sodium 25 g/ha; T5 , Sesbania seeding rate for BM @20 kg/ha with bispyribac sodium 25 g/ha; T6 , Sesbania seeding rate for BM @25 kg/ha with bispyribac sodium 25 g/ha; T7 , rice alone with 2,4-D 0.5 kg/ha; T8 , rice alone with bispyribac sodium 25 g/ha; T9 , hand weeding twice at 20 and 40 DAS (days after sowing); T10, unweeded control in a randomized block design (RBD) with three replications. Sesbania seeding rate for brown manuring (BM) @25 kg/ha + 2,4-D 0.5 kg/ha recorded significantly lower total weed density (73.3 no./m2) and weed dry weight (37.0 g/m2). Significantly higher crop growth rate (CGR) (528.2 g/m2 /day), plant height (132.8 cm) and rice yield (4823 kg/ha) were observed under Sesbania seeding rate for BM @25 kg/ha + 2,4-D 0.5 kg/ha which was comparable with Sesbania seeding rate for BM @25 kg/ha + bispyribac sodium 25 g/ha but superior to treatments without BM and eventually resulted in higher energy productivity (0.59 to 0.60 kg/MJ), energy profitability (7.74 to 7.77 kg/MJ) and the energy use efficiency (8.74 to 8.77). Thus, Sesbania seeding rate @25 kg/ha along with spraying either 2,4-D 0.5 kg/ha or bispyribac sodium 25 g/ha for brown manuring could be recommended in wet seeded rice.

Field experiments were conducted during 2021 and 2022 with twelve treatments on sandy clay loam soil in randomized block design (RBD), replicated thrice. The treatment consisted of rice co-culture with Sesbania bispinosa (Sesbania) and applied with different formulations of 2,4-D sodium salt, ethyl-ester and amine at varied levels (0.50, 0.75 and 1.0 kg/ha), hand weeding twice, weed free and unweeded control. Application of 2,4-D ethyl-ester 1.0 kg/ha proved effective in weed management by exhibiting significantly lower densities of grass (70.7/m²), sedges (14.7/m²), and broad-leaved weeds (0.0/m²) with higher weed control efficiency of 74.3% at 60 DAS. Brown manuring through application of 2,4-D ethyl-ester 1.0 kg/ha led to higher grain yield (3.62 t/ha) and B:C ratio (2.03) and it was followed by 2,4-D sodium salt 1.0 kg/ha. Therefore, 2,4-D ethyl-ester 1.0 kg/ha can be recommended for effective brown manuring and eco-friendly weed management in rice, which would provide higher rice grain yield and B: C ratio. The next best treatment was rice co-culture with dhaincha and applied with 2,4-D sodium salt 1.0 kg/ha in wet seeded rice of deltaic coastal ecosystem.