This special issue titled “Advances in precision irrigation management in the twenty-first century” explored novel research in precision irrigation management, with a focus on enhancing water use efficiency and environmental sustainability. Thirteen papers were accepted following a peer review process. Invited contributions developed new approaches for scheduling precision irrigation, leveraging artificial intelligence for water stress management and irrigation application support, optimizing irrigation efficiency through machine learning tools, and developing evidence-based tools for monitoring water stress, water use, and soil water status. Research on the environmental benefits of precision irrigation, contributing to the advancement of sustainable agricultural practices was part of this special issue. This special issue provided a platform for sharing the latest findings, methodologies, and insights on precision irrigation management. Notably, the research in this special issue extended the methodological and technological foundations of the field by addressing several critical challenges, such as irrigation in water-scarce conditions, scalability of monitoring tools, and the environmental implications of irrigation practices. The knowledge and tools presented in this special issue contributed to more robust, evidence-based, resilient, efficient, and environmentally sound irrigation systems, with close relevance to research, practice, and policy in sustainable agriculture.

In the worldwide context of rising salinity issues in agriculture, it is important to understand crop responses to salinity stress. Currently, standing as the second largest oilseed crop, canola (Brassica napus L.) entices continued research focus on such aspects. Thus, this study investigated the genotypic variation in seedling emergence characters under salinity stress. Two growth chamber experiments were conducted in diverse canola genotypes (10 each of winter and spring types) at six salinity levels (0, 2, 4, 6, 8, and 10 dS m⁻¹ EC). Increasing salinity levels reduced the emergence indices (emergence percentage, emergence rate index, corrected emergence rate index, and emergence velocity) and salt tolerance index (STI). An approximate threshold salinity range of 6–8 dS m⁻¹ ECs was determined. Importantly, salinity at ≥8 dS m⁻¹ EC levels substantially reduced seedling emergence indices and delayed emergence by 3–7 days after seeding. Winter genotypes CP1022WC/Chinook and CP320WRR, and spring genotypes Monarch, PI597352, PI601200, and PI432395 had higher STI and emergence indices. Based on cluster analysis, genotype groups were classified as low (Athena, CP115W, Durola, Impress, and Gem), medium (Amanda, Ericka, CP320WRR, Salut, CP225WRR, Clearwater, and Wester), and high salt‐tolerant types (CP1022WC/Chinook, Monarch, PI597352, and PI432395). All emergence indices showed high broad‐sense heritability (H² = 0.82–0.94). Between canola types, spring canola consistently showed greater genetic potential for salt tolerance than winter canola. The results of this study provided useful information for canola seedling establishment under salinity and for further genetic improvement of salt tolerance.

About 90% of the Texas High Plains area depends on the water supply from the Ogallala aquifer. The decline of the Ogallala water table raises a concern for the sustainability of producing the traditional irrigated field crops due to their high water demand. Thus, diversifying cropping systems may be a solution. However, about 70% of the irrigated cropland uses center pivots that may negatively impact specialty crop quality. Thus, a 3‐year experiment was conducted to assess the potential of using mobile drip irrigation (MDI) to produce fresh watermelon compared to center pivot sprinkler irrigation using low‐elevation spray application (LESA), and surface drip irrigation with plastic mulch (DI). The study evaluated the effects of irrigation systems on crop yield, fruit quality, physiological responses, water use efficiency (WUE), and irrigation use efficiency (IUE). On average, plants under MDI had higher yields (106 Mg ha⁻¹) than those under DI (70 Mg ha⁻¹) and LESA (68 Mg ha⁻¹). Plants under MDI and DI also had more fruits per plant (1.9) than those under LESA (1.4). The higher yield was associated with higher biomass and photosynthetic function. In general, fruit quality was not affected by irrigation system. In addition, plants under MDI system showed a higher WUE and IUE, and less water stress than those under LESA and DI systems. Results of this study suggest that irrigating under an MDI system is a good alternative for growers in the Texas High Plains that aim to diversify their cropping system with high‐value vegetable crops such as watermelon (Citrullus lanatus).