China is the largest producer of faba bean with a total harvested area of 8.11×10⁵ ha and a total production of 1.69 ×10⁶ tons (dry beans) in 2020, accounting for 30% of the world production. Faba bean is grown in China for both fresh pods and dry seed. East China cultivates large seed cultivars for food processing and fresh vegetables, while northwestern and southwestern China grow cultivars for dry seeds, with an increased production of fresh green pods. Most of the faba bean is consumed domestically, with limited exports. The absence of unified quality control measures and simple traditional cultivation practices contributes to the lower competitiveness of the faba bean industry in international markets. Recently, new cultivation methods have emerged with improved weed control, as well as better water and drainage management, resulting in higher quality and income for producers. Root rot disease in faba bean is caused by multiple pathogens, including Fusarium spp., Rhizoctonia spp., and Pythium spp. Fusarium spp. is the most prevalent species causing root rot in faba bean crops and is responsible for severe yield loss, with different species causing the disease in different regions in China. The yield loss ranges from 5% to 30%, up to 100% in severely infected fields. The management of faba bean root rot disease in China involves a combination of physical, chemical, and bio-control methods, including intercropping with non-host crops, applying rational nitrogen, and treating seeds with chemical or bio-seed treatments. However, the effectiveness of these methods is limited due to the high cost, the broad host range of the pathogens, and potential negative impacts on the environment and non-targeted soil organisms. Intercropping is the most widely utilized and economically friendly control method to date. This review provides an overview of the current status of faba bean production in China, the challenges faced by the industry due to root rot disease, and the progress in identifying and managing this disease. This information is critical for developing integrated management strategies to effectively control root rot in faba bean cultivation and facilitating the high-quality development of the faba bean industry.

Faba bean is considered one of the most prominent grain legumes, with high protein content for human food consumption and livestock feed. The present study evaluated the nature of gene action and determined the genetic diversity among different populations of three crosses for resistance to foliar diseases at the molecular level. Analysis of variance exposed significant differences among the generations for all measured traits. Both dominance and additive gene effects were essential, but dominance genes, for the most part, exhibited greater effects than additive ones. This indicates an essential role for dominant genes alongside the additives one in inheriting such traits. The third cross (Marina × Giza 40) gave desired significant and positive (additive × additive) values for the number of pods/plant, seeds/plant, and seed yield/plant, in addition to desirable negative values for chocolate spot and rust characteristics. Furthermore, assessing the lines under study using seven SCoT primers disclosed three bands with recorded molecular weights of 260, 207, and 178 bp, generated by SCoT-1, SCoT-4, and SCoT-7 primers, respectively. These bands exist in the resistant parent (Marina), which could be attributed to the high-disease-resistance phenotypes, and they are absent in the sensitive parent (Giza 40) and other putative sensitive lines. Based on the molecular profiles and the genetic similarity between parents and the selected lines, the highest similarity value (0.91) was detected between Marina genotype and BC₁, revealing a high foliar disease resistance. Meanwhile, Giza 40 (susceptible to foliar diseases) exhibited the maximum value (0.93) with F₂. Additionally, cluster analysis based on genetic relationships was performed, and a high level of correlation between the results of PCR-based SCoT analysis and the foliar disease reactions was observed in the field. Consequently, this study concluded that SCoT markers created reliable banding profiles for evaluating genetic polymorphism among faba bean lines, which could be a foundation for developing an efficient breeding program.

Drought is a major environmental challenge that significantly limits crop productivity, and its impact varies based on the severity and timing of water scarcity. Soybean [Glycine max (L.) Merr.] faces considerable yield constraints under water-deficit conditions. This study evaluated the performance of eight soybean genotypes characterized by different levels of drought tolerance compared with the drought-tolerant world genotype PI416937 under normal [100% of crop evapotranspiration (ETc)] and deficit irrigation (60% ETc) conditions during the 2021 and 2022 seasons at Sakha Agricultural Research Station. Under deficit irrigation, the promising line H4L4 produced 92% (4.07 t/ha) of its productivity under normal irrigation, compared with 89% (2.12 t/ha) for the drought-tolerant genotype PI416937 in an average of two seasons. Applying deficit irrigation saved 37.54% and 38.61% of applied irrigation water across two seasons, whereas genotype H4L4 achieved the highest crop water use efficiency (0.95 and 0.90 kg seeds/m³) in the respective seasons, highlighting its potential for sustainable production under water-limited conditions. The promising line H4L4 also exhibited the highest stability and adaptability for seed yield across diverse environments, as confirmed by GGE biplot analysis. Furthermore, the drought susceptibility index (DSI) proved the superiority of H4L4 followed by PI416937, Giza 22, and DR101 for drought tolerance. Additionally, anatomic studies highlighted that PI416937 and H4L4 exhibited superior tolerance by maintaining thicker primary and secondary xylem tissues along with better stem and leaf integrity under irrigation levels. These resilient genotypes, thriving under water-deficit conditions, have significant potential as valuable genetic resources for breeding programs to enhance soybean productivity and sustainability. Additionally, H4L4 may be well-suited for widespread cultivation in water-deficit areas.

Food legumes play a pivotal role in China’s food security, nutritional health, and green development strategies due to their unique advantages. This paper presents an empirical study on the economic evaluation of scientific research on pest and disease control for food legumes. Using panel data from 31 Chinese provinces from 2008 to 2023, we employ a Double Machine Learning (DML) approach to identify the impact of investment in plant protection research on food legume outputs. The results indicate a steady increase in China’s investment in this field, with an average annual growth rate of 5.19% from 2008 to 2023, and the total investment in 2023 was 2.14 times that of 2008. Investment in plant protection research effectively mitigates output losses and leads to significant production increases. Specifically, a 1% increase in research investment corresponds to a 0.2% increase in food legume output. This effect remains robust across various algorithms, time windows, and control variable settings. Based on these findings, we recommend: (1) increasing financial support and talent acquisition for research on food legume pests and diseases to enhance the stability and sustainability of research investment; (2) strengthening cooperation mechanisms between research institutions and enterprises to leverage their respective strengths and promote the commercialization of research outcomes and regional variety extension; (3) establishing a diversified research investment system that explores a co-construction model guided by the government, involving enterprises, and utilizing public–private partnerships to reconcile the conflict between long research cycles and market demands; (4) fostering a dual-track linkage between regional technological innovation and enterprise product commercialization to improve the efficiency of technology transfer and application; and (5) strengthening R&D in cutting-edge fields like Artificial Intelligence to improve the efficiency and precision of pest and disease control.