With the rapid development of new-generation cyber–physical system (CPS) technologies, the smart operation and management of the broad bean harvesting system are enabled. This paper proposed a smart broad bean harvesting system (SBHS) and a self-adaptive control method based on CPS technologies. Firstly, the overall architecture of the SBHS is designed, which consists of four main components, namely optimal intelligent perception environment configuration, digital twin model construction, virtual simulation and real-time optimization, self-adaptive adjustment and control. Then, three key enabling technologies are discussed in detail, namely, intelligent perception environment configuration for the SBHS, digital twin model construction for the SBHS, colored Petri net (CPN)-based self-adaptive analysis and control of the harvesting system. Lastly, a proof-of-concept experiment based on a cooperative company is presented to illustrate the main work logic and advantage of the proposed SBHS. After the edge–cloud cooperative intelligent harvesting environment is configured, the CPN model for the workflow of the SBHS is created to analyze and optimize the harvesting processes. In addition, a management and control platform are developed to further illustrate the implementation of the proposed SBHS and the self-adaptive control method.

Against the backdrop of intelligent and precision agriculture, mechanized harvesting of pulses is crucial for improving productivity and addressing the challenges posed by the changing agricultural workforce structure. However, the biological characteristics of pulses—such as susceptibility to grain breakage, pod shattering, and asynchronous maturity—impose far more stringent demands on threshing and cleaning performance than those for cereal crops. Existing grain combines, when directly applied to pulses, commonly cause high grain breakage during threshing, high cleaning losses, and poor adaptability. This paper systematically reviews the current status and development trends of threshing and cleaning technologies in mechanized pulse harvesting. The core challenges are analyzed from three perspectives: crop biology, technical bottlenecks, and external operational factors. Research progress and breakthrough pathways in low-damage threshing are reviewed in terms of physical and biomechanical properties, flexible threshing elements, multi-stage cylinder structures, multi-field coupled simulation, intelligent control, and energy consumption analysis. Key achievements and breakthrough pathways in high-efficiency cleaning are summarized from aspects of airflow–screen coupling optimization, screening system innovation, numerical simulation, and intelligent detection and control. Based on typical machine models, the structural characteristics and operational applicability of general-purpose and specialized combine harvesters are compared and analyzed. Finally, future development directions are discussed from four perspectives: multifunctionality and generalization, simplification and adaptability, intelligence and precision, and greening and energy efficiency. This paper aims to provide a systematic theoretical reference and technical support for the development, improvement, and industrial application of low-damage, high-efficiency pulse harvesting equipment.

Advances in crop breeding techniques and economic evaluation are critical to ensuring and improving crop yields and sustainable development. Based on the provincial data on food legumes breeding (FLB) in China from 2001 to 2020, the research and development (R&D) expenditure distribution, FLB contribution rate, and R&D expenditure on FLB were estimated. The economic benefits of output per unit area and R&D expenses were evaluated, and relevant policy suggestions were put forward. The study found that: (i) the R&D expenditure on FLB’s showed a significant upward trend, and the development can be divided into a starting, stable, and rapid growth period. There were significant differences in R&D expenditures across eight provinces of China with relatively high R&D expenditures for FLB; (ii) the R&D expenditure on FLB had a significant lag in the improvement of per mu yield (1 mu = 0.067 hectares). For every 10,000 yuan increase in R&D funding for FLB, the yield per mu will increase by 0.145 kg/mu in the next five years, and the regional spillover effect of breeding costs is significant; and (iii) the marginal revenue of R&D expenditures FLB from 2008 to 2020 is 34.91 yuan, that is, every 1 yuan invested in breeding R&D can bring a short-term marginal revenue of 34.91 yuan and a long-term marginal revenue of 337.23 yuan. Based on the above analysis, some recommendations were proposed and discussed, including further increasing the R&D investment of FLB, strengthening industry–university–research cooperation in breeding, improving the breeding research system, and promoting the multi-dimensional development of FLB industry–university–research services.

Pelletization of the loose rice straw is an attractive option to produce renewable fuels. In this paper, we focus on the problem of how to improve this pelletization process, especially to reduce energy consumption and improve product quality. In detail, we first pretreat rice straw, and then investigate the densification characteristics of the pretreated materials. Pretreatment methods of the materials include hydrothermal treatment and adding a certain proportion of economic additives, such as rapeseed meal and waste engine oil respectively. In addition, the pretreated rice straw was pelletized by using a biomass densification platform, meanwhile energy consumption and pellet quality were tested. Experimental results indicate that the hydrothermal pretreatment played an important role in reducing energy consumption and improving the product quality, and waste engine oil has a better effect than the rapeseed meal. We also observe that the obtained pellet quality reaches the standard of middle-grade coal, and the proposed pretreatment method realizes the comprehensive utilization of waste agricultural resources.