Towards quantification of the national water footprint in rice production of China: A first assessment from the perspectives of single-double rice

Increasing Hybrid Rice Yield, Water Productivity, and Nitrogen Use Efficiency: Optimization Strategies for Irrigation and Fertilizer Management

Water and fertilizer are crucial in rice growth, with irrigation and fertilizer management exhibiting synergies. In a two-year field study conducted in Yiyang City, Hunan Province, we examined the impact of three irrigation strategies-wet-shallow irrigation (W1), flooding irrigation (W2), and the "thin, shallow, wet, dry irrigation" method (W3)-in combination with distinct fertilizer treatments (labeled F1, F2, F3, and F4, with nitrogen application rates of 0, 180, 225, and 270 kg ha-1, respectively) on rice yield generation and water-fertilizer utilization patterns. The study employed Hybrid Rice Xin Xiang Liang you 1751 (XXLY1751) and Yue Liang you Mei Xiang Xin Zhan (YLYMXXZ) as representative rice cultivars. Key findings from the research include water, fertilizer, variety, and year treatments, which all significantly influenced the yield components of rice. Compared to W2, W1 in 2022 reduced the amount of irrigation water by 35.2%, resulting in a 42.0~42.8% increase in irrigation water productivity and a 25.7~25.9% increase in total water productivity. In 2023, similar improvements were seen. Specifically, compared with other treatments, the W1F3 treatment increased nitrogen uptake and harvest index by 1.4-7.7% and 5.9-7.7%, respectively. Phosphorus and potassium uptake also improved. The W1 treatment enhanced the uptake, accumulation, and translocation of nitrogen, phosphorus, and potassium nutrients throughout the rice growth cycle, increasing nutrient levels in the grains. When paired with the F3 fertilization approach, W1 treatment boosted yields and improved nutrient use efficiency. Consequently, combining W1 and F3 treatment emerged as this study's optimal water-fertilizer management approach. By harnessing the combined effects of water and fertilizer management, we can ensure efficient resource utilization and maximize the productive potential of rice.

Bactericidal bissulfone B7 targets bacterial pyruvate kinase to impair bacterial biology and pathogenicity in plants

The prevention and control of rice bacterial leaf blight (BLB) disease has not yet been achieved due to the lack of effective agrochemicals and available targets. Herein, we develop a series of novel bissulfones and a novel target with a unique mechanism to address this challenge. The developed bissulfones can control Xanthomonas oryzae pv. oryzae (Xoo), and 2-(bis(methylsulfonyl)methylene)-N-(4-chlorophenyl) hydrazine-1-carboxamide (B7) is more effective than the commercial drugs thiodiazole copper (TC) and bismerthiazol (BT). Pyruvate kinase (PYK) in Xoo has been identified for the first time as the target protein of our bissulfone B7. PYK modulates bacterial virulence via a CRP-like protein (Clp)/two-component system regulatory protein (regR) axis. The elucidation of this pathway facilitates the use of B7 to reduce PYK expression at the transcriptional level, block PYK activity at the protein level, and impair the interaction within the PYK-Clp-regR complex via competitive inhibition, thereby attenuating bacterial biology and pathogenicity. This study offers insights into the molecular and mechanistic aspects underlying anti-Xoo strategies that target PYK. We believe that these valuable discoveries will be used for bacterial disease control in the future.

Effects of acid modified biochar on potassium uptake, leaching and balance in an alternate wetting and drying paddy ecosystem

Straw biochar amended soils reduce fertilizer losses and alleviate soil K-exhaustion, while decrease grain yield due to its high pH. H2SO4-modified biochar has been studied as a means to enhance the advantages of biochar and address yield decrease. However, little information is available on its effects on aboveground K uptake, soil K fixation, K leaching, and utilization in paddy rice systems, especially under water stress. A 3-year field experiment was conducted with two irrigation regimes (continuously flooded irrigation, ICF and alternate wetting and drying irrigation, IAWD) as main plots and 0 (control), 20 t ha-1 biochar (B20), and 20 t ha-1 acid-modified biochar (B20A-M) as subplots. The results showed that IAWD significantly decreased water percolation by 9.26 %-14.74 % but increased K leaching by 10.84 %-15.66 %. Compared to B0, B20 and B20A-M significantly increased K leaching by 32.40 % and 30.42 % in 2019, while decreased it by 11.60 %-14.01 % in 2020 and 2021. Both B20 and B20A-M significantly improved aboveground K uptake by 3.45 %-6.71 % throughout the three years. B20 reduced grain yield in 2019 and increased it in 2020 and 2021, while B20A-M increased grain yield throughout the three years. Apparent K balance (AKB) from pre-transplanting to post-harvest over the three years suggested that IAWD significantly increased the risk of soil K depletion but B20 and B20A-M significantly increased AKB, thereby addressing the depletion of it. IAWDB20A-M have a comparable AKB with ICFB20A-M, but had up to 18.3 % and 21.61 % higher AKB than IAWDB20 and ICFB20. Therefore, the use of H2SO4 modified biochar could produce higher grain yield with lower K leaching for addition in IAWD paddy systems, which is beneficial to mitigate soil K depletion and ensure a sustainable agricultural production.

Evaluating Effects of Medium-Resolution Optical Data Availability on Phenology-Based Rice Mapping in China

The phenology-based approach has proven effective for paddy rice mapping due to the unique flooding and transplanting features of rice during the early growing season. However, the method may be greatly affected if no valid observations are available during the flooding and rice transplanting phase. Here, we compare the effects of data availability of different sensors in the critical phenology phase, thereby supporting paddy rice mapping based on phenology-based approaches. Importantly, our study further analyzed the effects of the spatial pattern of the valid observations related to certain factors (i.e., sideslips, clouds, and temporal window lengths of flooding and rice transplanting), which supply the applicable area of the phenology-based approach indications. We first determined the flooding and rice transplanting phase using in situ observational data from agrometeorological stations and remote sensing data, then evaluated the effects of data availability in this phase of 2020 in China using all Landsat-7 and 8 and Sentinel-2 data. The results show that on the country level, the number of average valid observations during the flooding and rice transplanting phase was more than ten for the integration of Landsat and Sentinel images. On the sub-country level, the number of average valid observations was high in the cold temperate zone (17.4 observations), while it was relatively lower in southern China (6.4 observations), especially in Yunnan–Guizhou Plateau, which only had three valid observations on average. Based on the multicollinearity test, the three factors are significantly correlated with the absence of valid observations: (R2 = 0.481) and Std.Coef. (Std. Err.) are 0.306 (0.094), −0.453 (0.003) and −0.547 (0.019), respectively. Overall, these results highlight the substantial spatial heterogeneity of valid observations in China, confirming the reliability of the integration of Landsat-7 and 8 and Sentinel-2 imagery for paddy rice mapping based on phenology-based approaches. This can pave the way for a national-scale effort of rice mapping in China while further indicating potential omission errors in certain cloud-prone regions without sufficient optical observation data, i.e., the Sichuan Basin.

A Win–Win Scenario for Agricultural Green Development and Farmers’ Agricultural Income: An Empirical Analysis Based on the EKC Hypothesis

Due to severe resource and environmental constraints, agricultural green development is a vital step for the low-carbon development of China. How to achieve the goal of a win–win scenario that simultaneously improves agricultural green total factor productivity (GTFP) and farmers’ agricultural income was the main focus of this study. Based on the panel dataset for 31 provinces in China from 2000 to 2018, this study calculated the agricultural GTFP using the global Malmquist–Luenberger (GML) index to measure the green development of agriculture. Furthermore, this study investigated the relationship between the agricultural GTFP and agricultural income in an environmental Kuznets curve (EKC) framework, together with the key factors affecting agricultural GTFP. The main results show that, first, driven by technical progress, the agricultural GTFP gradually increased across the country, while there existed a certain degree of heterogeneity in the growth of different regions. Second, the relationships between the agricultural GTFP and agricultural income exhibited a significant U-shape for the whole country and the four regions, indicating that a win–win scenario can be achieved between green development and income level. Third, industrialization and urbanization negatively affected agricultural GTFP, capital deepening played a positive role, and due to the mediated effect of capital deepening, the outflow of the agricultural labor force did not cause substantial harm to agricultural GTFP. The findings of our study provide useful policy implications for the promotion and development of agriculture in China.

Multi-source data-based spatial variations of blue and green water footprints for rice production in Jilin Province, China

Rice production consumes more water than the production of other crop species due to the specific growth requirements of this species. Accurately accounting for water consumption during rice production and analyzing the spatio-temporal changes in water consumption are thus necessary. Using the water footprint (WF) as an indicator and combining data from multi-sources, this paper explored the regional differences in rice WFs in Jilin Province at a spatial resolution of 1 km. The results showed that the blue WF was always larger than the green WF, and the total, green and blue WFs were lowest during the humid year. The pixels with high values of total, green and blue WFs were mainly distributed in the eastern region of Jilin Province. Compared with the traditional estimation of the WF based on the data of administrative regions, RS techniques can overcome the administrative boundary and provide near real-time data concerning specific agricultural parameters to extract more accurate results for WF models. The combination of RS data and statistical, observational, and survey data can thus overcome the limitations of weather conditions affecting RS, reduce the incorporation of parameters, and estimate WFs quickly and accurately. This study provides a framework to evaluate crop WFs with multi-source data.