Beneficial root-microbiome interactions offer enormous potential to improve crop performance and stress tolerance. Domestication and improvement reduced the genetic diversity of crops and reshaped their phenotypic traits and their associated microbiome structure and function. However, understanding of the genetic and physiological mechanisms how domestication and improvement modulated root function, microbiome assembly and even co-selective patterns remains largely elusive. This review summarizes the current status of how crop domestication and improvement (heterosis) affected root characteristics and their associated microbiome structure and function. Also, it assesses potential mechanisms how crop domestication and improvement reshaped root-microbiome association through gene regulation, root structure and function and root exudate features. A hypothetical strategy is proposed that entangles crop genetics and abiotic interactions with beneficial microbiomes to mitigate the effects of global climate change on crop performance. A comprehensive understanding of the role of crop domestication and improvement in root-associated microbiome interaction will advance future breeding efforts and agricultural management.

Chickens are one of the most important domesticated animals, serving as an important protein source. Studying genetic variations in chickens to enhance their production performance is of great potential value. The emergence of next-generation sequencing has enabled precise analysis of single nucleotide polymorphisms and insertions/deletions in chicken, while third-generation sequencing achieves the accurate structural variant identification. However, the high cost of third-generation sequencing technology limits its application in population studies. The graph-based pan-genome strategy can overcome this challenge by enabling the detection of structural variations using cost-effective next-generation sequencing data. This study constructed a graph-based pan-genome for chickens using 12 high-quality genomes. This pan-genome used linear genome GRCg6a as the reference genome, containing variant information from two commercial and nine native chicken breeds. Compared to the linear genome, the pan-genome provided significant improvements in the efficiency of structural variation identification. On the basis of the graph-based pan-genome, high-frequency structural variations related to high egg production in Leghorn chicken were predicted. Additionally, it was discovered that potential structural variations was associated with highland adaptation in Tibetan chickens according to next-generation sequencing and transcriptomics data. Using the pan-genome graph, a new strategy to identify structural variations related to traits of interest in chickens is presented.

The development of Internet information technology has given digital agricultural technology extension services advantages over earlier agricultural technology extension models, rendering them more conducive to the pursuit of sustainable and environmentally friendly agricultural development. This study leveraged survey data from 1167 farmers in Shaanxi and Gansu Provinces and used the propensity score matching method to elucidate the impact and mechanism of the digital agricultural technology extension service on the adoption of organomineral fertilizer. The results indicate that farmers who had used digital agricultural technology extension services had a 7.2% to 10.2% increase in the probability of adopting organomineral fertilizer compared with their non-user counterparts. In addition, adoption intensity increased from 7.0% to 9.9%. Secondly, digital agricultural technology extension services indirectly influence farmer adoption behavior by shaping their perceptions of benefits and reducing transaction costs. Also, this study examined the heterogeneity in the adoption of organomineral fertilizer facilitated by digital agricultural technology extension services. The findings of this study provide policy recommendations for advancing the use of digital agricultural technology extension services and enhancing organomineral fertilize adoption rates of farmers.

To efficiently obtain P from soil, most terrestrial plants form symbiosis with arbuscular mycorrhizal (AM) fungi and thus have two P uptake pathways, i.e., the direct pathway (DP) via roots, particularly root hairs, and the mycorrhizal pathway (MP) via AM fungal hyphae. AM fungi form an extraradical hyphal network to expand their contact area with soil and release carbon-rich compounds, which provide a high-energy habitat for soil bacteria. The bacteria affected by AM fungi support P nutrition of AM fungi by secreting extracellular phosphatases. During the P acquisition process, both DP and MP function and require C fixed by plant photosynthesis to maintain P transport. Plants make trade-offs between DP and MP based on C inputs and P benefits. This review first systematically explores the potential trade-offs between plant C inputs and P gains of DP and MP as well as the factors that influence such trade-offs. Then the response of AM fungi to soil nutrient heterogeneity and the mechanisms by which AM fungi select bacteria to mineralize organic P and increase the P contribution of MP were analyzed. Future studies need to apply emerging methods and technologies to accurately quantify the contribution of DP and MP to plant P absorption under different conditions and provide the theoretical basis for optimizing sustainable agricultural production systems.

Plant roots are crucial for nitrogen uptake. To efficiently acquire N, root system architecture (RSA), which includes the length and quantity of primary roots, lateral roots and root hairs, is dynamically regulated by the surrounding N status. For crops, an ideotype RSA characterized by enhanced plasticity to meet various N demands under fluctuating N conditions is fundamental for high N utilization and subsequent yield. Therefore, exploring the genetic basis of N-dependent RSA, especially in crops, is of great significance. This review summarizes how plants sense both local and systemic N signals and transduce them to downstream pathways. Additionally, it presents the current understanding of genetic basis of N-dependent root plasticity in Arabidopsis and major crops. Also, to fully understand the mechanisms underlying N-dependent root morphogenesis and effectively identify loci associated with an ideotype RSA in crops, more attention should be paid to non-destructive, in situ phenotyping of root traits, cell-type-specific exploration of gene functions, and crosstalk between root architecture, environment and management in the future.

In response to the demand of automatic fruit identification and harvesting, this paper presents a human-robot collaborative picking robot based on somatosensory interactive servo control. The robot system mainly consisted of four parts: picking execution mechanism, hand information acquisition system, human-machine interaction interface, and human-robot collaborative picking strategy. A six-degree-of-freedom robotic arm was designed as the picking execution mechanism. The D-H method is employed for both forward and inverse kinematic modeling of the robotic arm. A four-step inverse kinematic optimal solution selection method, including mechanical interference, correctness, rationality, and smoothness of motion, is proposed. The working principle and use of the Leap Motion controller for hand information acquisition were introduced. Data from three types of hand movements were collected and analyzed. Spatial mapping method between the Leap Motion interaction space and operating range of the robotic arm was proposed to achieve a direct correspondence between the cubic interaction box and the cylindrical space of the fan ring of the robotic arm. The test results demonstrated that the average response time of the double-click picking command was 332 ms. The average time consumption for somatosensory control targeting was 6.5 s. The accuracy rate of the picking gesture judgment was 96.7%.

With the development of smart agriculture, accurately identifying crop diseases through visual recognition techniques instead of by eye has been a significant challenge. This study focused on apple leaf disease, which is closely related to the final yield of apples. A multiscale fusion dense network combined with an efficient multiscale attention (EMA) mechanism called Incept_EMA_DenseNet was developed to better identify eight complex apple leaf disease images. Incept_EMA_DenseNet consists of three crucial parts: the inception module, which substituted the convolution layer with multiscale fusion methods in the shallow feature extraction layer; the EMA mechanism, which is used for obtaining appropriate weights of different dense blocks; and the improved DenseNet based on DenseNet_121. Specifically, to find appropriate multiscale fusion methods, the residual module and inception module were compared to determine the performance of each technique, and Incept_EMA_DenseNet achieved an accuracy of 95.38%. Second, this work used three attention mechanisms, and the efficient multiscale attention mechanism obtained the best performance. Third, the convolution layers and bottlenecks were modified without performance degradation, reducing half of the computational load compared with the original models. Incept_EMA_DenseNet, as proposed in this paper, has an accuracy of 96.76%, being 2.93%, 3.44%, and 4.16% better than Resnet50, DenseNet_121 and GoogLeNet, respectively, proved to be reliable and beneficial, and can effectively and conveniently assist apple growers with leaf disease identification in the field.

Interplant communication is of vital importance for plant performance in natural environments. Mycorrhizal fungi have emerged as key contributors to the below ground communication between plants. These mutualistic fungi form connections between the roots of plants via their hyphae, known as common mycorrhizal networks (CMNs). These hyphal networks are thought to be important ways for the exchange of signals between plants. This paper reviews the evidence for CMN-based transfer of semiochemicals between plants upon exposure to pathogen infection, herbivory or mechanical damage. Potential transport routes are explored, asking whether the fungi can actively contribute to the distribution of such signals within the network and discussing potential drivers for signal exchange. It is concluded that identification of the signals that are exchanged remains an important challenge for the future.

The achievement of global food security faces exceptional challenges due to the rapid population growth, land degradation and climate change. Current farming practices, including mineral fertilizers and synthetic pesticides, alone are becoming insufficient to ensure long-term food security and ecosystem sustainability. The lack of robustness and reliability of conventional approaches warrants efforts to develop novel alternative strategies. Bio-based management strategies offer promising alternatives for improving soil health and food productivity. For example, microbial inoculants can enhance nutrient availability, crop production and stress resistance while also remediating contaminated soils. Nanobiotechnology is a promising strategy that has great potential for mitigating biotic and abiotic stresses on plant toward sustainable agriculture. Biochar (including modified biochar) serves as an effective microbial carrier, improving nutrient availability and plant growth. Also, biochar amendments have been demonstrated to have great potential facilitating soil organic carbon sequestration and mitigating greenhouse gas emissions and therefore contribute to climate change mitigation efforts. This review examines the integration of microbial inoculants, nano-fertilizers and biochar, which demonstrates as a promising strategy to enhance soil health, crop productivity and environmental sustainability. However, overcoming challenges related to their mass production, application and potential risks remains crucial. Future research should focus on optimizing these bio-amendment strategies, evaluating their economic viability and developing robust regulatory frameworks to ensure safe and effective agricultural implementation.

Adequate dietary zinc intake remains a public health challenge in China. Also, there is a lack of information on the relationship between Zn intake and food consumption patterns across provinces and over time. In this study, data from the China Health and Nutrition Survey 2004–2011 (21,266 individuals) was used to explore associations between dietary Zn intake and sociodemographic factors. Zn intake per person declined from 11.1 mg·d⁻¹ in 2004 to 9.89 mg·d⁻¹ in 2011, with reduction in cereal consumption the greatest contributor to this. However, the reduction resulting from the lower cereal consumption was only partly compensated by an increase in consumption of Zn-rich foods. The percentage of the study population with inadequate Zn intake increased from 23% in 2004 to 37% in 2011. While Zn intake was positively associated with income levels in each survey year, the time trend for all income levels was a gradually reducing Zn intake. In all years, males had an average higher dietary Zn intake, whereas no significant difference was found between living areas. In conclusion, this study shows that dietary Zn inadequacy was high and has increased over the studied period. Remediation could be sought by shifting dietary patterns toward more Zn-dense food or by enhancing Zn concentration through biofortification.