Natural plant roots enrich a diverse array of soil microbes, collectively known as the root microbiota. This microbiota interacts synergistically with plants, modulating various physiological processes, including nutrient utilization, which influences plant growth and health. Environmental nutrient conditions and plant nutrient-related genes have been reported to regulate the composition of the root microbiota. Innovative analytical methods, such as microbiome genome- and microbiome-wide association studies, have advanced understanding of the relationships between plants and root microbiota. These methods systematically reveal the interactions between root microbiota and plant nutrient utilization, providing a theoretical foundation for applying root microbiota in agriculture.

Artificial intelligence-based automatic systems can reduce time, human error and post-harvest operations. By using such systems, food items can be successfully classified and graded based on defects. For this context, a machine vision system was developed for fruit grading based on defects. The prototype consisted of defective fruit detection and mechanical sorting systems. Image processing algorithms and deep learning frameworks were used for detection of defective fruit. Different image processing algorithms including pre-processing, thresholding, morphological and bitwise operations combined with a deep leaning algorithm, i.e., convolutional neural network (CNN), were applied to fruit images for the detection of defective fruit. The data set used for training CNN model consisted of fruit images collected from a publicly-available data set and captured fruit images: 1799 and 1017 for mangoes and tomatoes, respectively. Subsequent to defective fruit detection, the information obtained was communicated to microcontroller that further actuated the mechanical sorting system accordingly. In addition, the system was evaluated experimentally in terms of detection accuracy, sorting accuracy and computational time. For the image processing algorithms scheme, the detection accuracy for mango and tomato was 89% and 92%, respectively, and for CNN architecture used, the validation accuracy for mangoes and tomatoes was 95% and 94%, respectively.

The escalating recognition of sustainable agriculture and food systems is a response to the multifaceted challenges of food insecurity, climate change, environmental deterioration and economic pressures. In this review, sustainable agriculture is characterized as an array of farming practices that effectively address immediate demands, while simultaneously safeguarding the potential of future generations to fulfill their needs. The primary objectives include sustained productivity, pollution reduction, and economic viability and sustainability. Sustainable food systems incorporate dimensions beyond production, including processing, distribution, consumption patterns, and waste management along the entire food supply chain. An abundance of research underscores the manifold benefits offered by sustainable agriculture and food systems to society at large. These advantages include fostering climate resilience, curbing greenhouse gas emissions, enhancing water quality, promoting biodiversity, enriching soil fertility, fortifying rural livelihoods and nurturing community well-being. Nevertheless, the path toward sustainability is strewn with significant challenges. These include substantial costs involved in transitioning, conflicts in policy objectives, and the pervasive influence of traditional methods. Achieving sustainability requires the execution of holistic strategies that traverse various sectors and scales. Accelerating this progress can be facilitated through the adoption of diverse strategies, including agroforestry, agroecology, urban agriculture, farmer knowledge exchange, ecosystem service payments and supply chain shortening. However, the success of these strategies hinges on the provision of appropriate policies and incentives. Further research is vital to ascertain the ideal conditions for implementing specific interventions and to assess the comprehensive expenses and benefits linked to them. This review emphasizes the assertion that widespread adoption of sustainable practices in agriculture and interconnected food systems has positive impacts in terms of community nutrition, conservation of natural resources and long-term economic progress.

● Analyzes the current situation of planted forests construction in China.

Tree plantations are an important forest resource that substantively contributes to climate change mitigation and carbon sequestration. As the area and standing volume of tree plantations in China have increased, issues such as unreasonable structure, low productivity, limited ecological functionality and diminishing ecological stability have occurred, which hinder the ability of tree plantations to enhance carbon sequestration. This study outlined the trajectory of carbon sequestration and its associated benefits in tree plantations by examining the current state of tree plantation establishment and growth, elucidated the strategies for advantages of carbon sequestration and climate change mitigation in planted forests, and summarized the existing problems with tree plantations. This paper underscores the pressing need for concerted efforts to boost carbon sequestration within planted forests and proposes management and development strategies for Chinese tree plantations. In the future, it will be necessary to apply scientific theories to practice and develop multi-objective management optimization models for the high-quality development of tree plantations. This will involve establishing a cohesive national carbon trading market, improving the prediction of carbon sequestration, and identifying priority zones for afforestation and reforestation, to better serve China’s national strategy for achieving peak carbon and carbon neutrality.

Localized fertilization strategies (banding fertilizers) developed to minimize nutrient fixation by soil are used widely in intensive agricultural production. Localized fertilization encourages root foraging for heterogeneously distributed soil nutrients. This review focuses on the advances in root growth and nutrient acquisition of heterogeneously distributed soil resources. It is proposed that the incremental amplification of root foraging for nutrients induced by localized fertilization: (1) increased absorption area due to altered root morphology, (2) enhanced mobilization capacity underpinned by enhanced root physiological processes, and (3) intensified belowground interactions due to selective stimulation of soil microorganisms. The increase in root proliferation and the nutrient mobilization capacity as well as microbiome changes caused by localized fertilization can be amplified stepwise to synergistically enhance root foraging capacity, nutrient use efficiency and improve crop productivity. Engineering the roots/rhizosphere through localized, tailored nutrient application to stimulate nature-based root foraging for heterogeneously distributed soil nutrients, and scaling up of the root foraging capacity and nutrient acquisition efficiency from the rhizosphere to the field offers a potential pathway for green and sustainable intensification of agriculture.

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.

Biochar, a carbon-rich material produced by biomass pyrolysis, is valued for soil amendment, carbon sequestration and environmental remediation. Optimum biochar production depends on understanding key factors, including feedstock characteristics, pyrolysis conditions and modification methods. This review examines various pyrolysis techniques, ranging from well-established to new methods, assessing their mechanisms, strengths and limitations for large-scale production. It emphasizes the importance of feedstock selection, pyrolysis conditions and modification methods in affecting biochar yield and properties. By synthesizing current research findings, this review aims to provide insights into optimizing biochar production for sustainable utilization of lignocellulosic biomass resources.

● The main impediments to low-carbon development of livestock sector are recognized.

Rapid growth and a vast transition of Chinese livestock industry driven by economic incentives make it become an important contributor on climate change over the last four decades. This study first analyzes the evolving low-carbon livestock development policies and regulations, then an assessment and explanations of the achievements and non-achievements are provided. The findings reveal that China began to pay attention to low-carbon development policy starting in the early 1990s. However, only after the cyclic and green concept became the main sustainable development policy, China began to move seriously toward low-carbon livestock development. Several policy instruments were introduced, including moderate scale, feed optimization, manure resource utilization, facility and equipment allocation rate, energy conservation and substitution. Overall, achievements were made in introducing such policies. However, due to the large share of standard agriculture and regional resources, and environmental diversity, such policies may have little effect in practice. The divergence between the policies and actual practices are explained, and important policies applicable to all developing countries are also recommended.

Weed management is a crucial aspect of modern agriculture as invasive plants can negatively impact crop yields and profitability. Long-established methods of weed control, such as manual labor and synthetic herbicides, have been widely used but come with their own set of challenges. These methods are often time-consuming, labor-intensive, and pose environmental risks. Herbicides have been the primary method of weed control due to their efficiency and cost-effectiveness. However, over-reliance on herbicides has led to environmental contamination, weed resistance, and potential health hazards. To address these issues, researchers and industry experts are now exploring the integration of machine learning into chemical weed management strategies. As technology advances, there is a growing interest in exploring innovative and sustainable weed management approaches. This review examines the potential of machine learning in chemical weed management. Machine learning offers innovative and sustainable approaches by analyzing large data sets, recognizing patterns, and making accurate predictions. Machine learning models can classify weed species and optimize herbicide usage. Real-time monitoring enables timely intervention, preventing invasive species spread. Integrating machine learning into chemical weed management holds promise for enhancing agricultural practices, reducing herbicide usage and minimizing environmental impact. Validation and refinement of these algorithms are needed for practical application.

● Methane led China’s growth in net greenhouse gas emissions over the pandemic.

To study the impact of the COVID-19 pandemic on agricultural carbon emissions in China, the greenhouse gas emissions generated by crop and livestock production, and agricultural material and energy inputs in China from 2019 to 2021 were systematically calculated. It was found that from 2019 to 2021, Net greenhouse gas emissions (NGHGE) from agriculture in China had an increasing trend. Methane emissions ranked first in NGHGE, with an annual proportion exceeding 65% and an increasing annual trend. CH₄ emissions were primarily influenced by enteric fermentation and rice production. Nitrous oxide emissions accounted for around 22% of annual NGHGE and decreased from 2019 to 2021. The main sources of N₂O emissions were the use of nitrogen fertilizers and manure management. Carbon dioxide emissions accounted for about 18% annually, with diesel and agricultural electricity use contributing to over 60% of CO₂ emissions. Soil carbon sequestration represented about a 6.1% lowering of NGHGE. The combined proportion of CH₄ emissions from enteric fermentation and rice production accounted for over 50% of total GHG emissions. The changes in NGHGE were mainly caused by disturbance of the livestock industry during the pandemic.

Amid the escalating frequency of climate extremes, it is crucial to determine their impact on agricultural water scarcity to preserve agricultural development. Current research does not often examine how different spatial scales and compound climate extremes influence agricultural water scarcity. Using an agricultural water scarcity index (AWSI), this study examined the effects of precipitation and temperature extremes on AWSI across secondary and tertiary river basins in China from 1971 to 2010. The results indicated a marked increase in AWSI during dry years and elevated temperatures. The analysis underscores that precipitation had a greater impact on AWSI than temperature variation. In secondary basins, AWSI was about 26% higher than the long-term average during dry years, increasing to nearly 49% in exceptionally dry conditions. By comparison, in tertiary basins, the increases were 28% and 55%, respectively. In hot years, AWSI rose by about 6.8% (7.3% for tertiary basins) above the average, surging to about 19.1% (15.5% for tertiary basins) during extremely hot periods. These results show that AWSI assessment at the tertiary basin level better captured the influence of climate extremes on AWSI than assessments at the secondary basin level, which highlights the critical importance of a finer spatial scale for a more precise assessment and forecast of water scarcity within basin scales. Also, this study has highlighted the paramount urgency of implementing strategies to tackle water scarcity issues under compound extreme dry and hot conditions. Overall, this study offers an in-depth evaluation of the influence of both precipitation and temperature variation, and research scale on water scarcity, which will help formulate better water resource management strategies.

● Research on heavy metal passivation and nitrogen emissions is necessary for the pig industry.

The widespread use of feed additives in intensive and large-scale pig farming has resulted in high levels of heavy metals in pig manure. The long-term application of organic fertilizers containing high levels of heavy metals leads to the accumulation of heavy metals in the soil, which not only causes heavy metal pollution in the soil, and also affect food safety and endanger human health. Composting is an economical and effective technical measures to achieve environmentally-sustainable treatment of pig manure and is a practical method to reduce the problem of heavy metals and to improve the resource value of pig manure. The composting process is accompanied by high temperatures and the production and emission of gases, and also lead to changes in the nitrogen content of the compost and provide opportunity for heavy metal passivation additives. This paper summarizes the forms and types of heavy metals present in pig manure and reviews the progress of research as well as the techniques and problems of in the composting process, and provides recommendations for research on heavy metal passivation and nitrogen retention in pig manure composting.

Seed aging adversely affects agricultural productivity by reducing germination rates and seedling vigor, leading to significant costs for seed banks and companies due to the need for frequent seed renewals. This study demonstrated the use of plasma-activated water (PAW), generated by a solar-powered corona dielectric barrier discharger, to enhance germination rates of spinach seeds that had been stored at 4 °C for 23 years. Treating seeds with PAW at 17 kV for 15 min improved germination (by 135%) and seedling growth compared to untreated seeds. Through detailed analysis, beneficial PAW properties for seed development were identified, and a molecular mechanism for this rejuvenation is proposed. The solar-powered microreactor used in this study is considered to represent a significant advancement in seed treatment technology, offering a sustainable solution to meet growing food demands while addressing environmental and resource sustainability challenges.

2′-Deoxymugineic (DMA), a phytosiderophore secreted by Poaceae species, can improve iron nutrition in plants. However, little is known about how DMA influences beneficial bacteria in rhizosphere microecosystem. To address this gap, the DMA analog proline-2′-deoxymugineic (PDMA) was used to evaluate its positive effect on peanut rhizobacterial communities and network structure. This study demonstrated that PDMA can promote the absorption of several mineral nutrients in plants and activate micronutrients in the rhizosphere. Specifically, PDMA led to significant impact on the bacterial community structure in the peanut rhizosphere, resulting in a substantial increase in the relative abundance of Actinobacteriota with six beneficial rhizobacterial genera in this phylum. The Cellulosimicrobium and Marmoricola of Actinobacteriota recruited by PDMA may enhance micronutrient availability both to peanut plants and in soil. PDMA application led to the development of a tight, stable microbial network, as indicated by higher topological parameters and a greater variety of keystone genera. Functional prediction revealed that PDMA fosters microbial communication in the rhizosphere. Overall, PDMA was shown to recruit beneficial bacteria and to modulate bacterial network structure in the peanut rhizosphere. It is concluded that these findings demonstrate that phytosiderophore might promote plant growth and nutrition absorption by regulating plant–soil microecosystem.

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.

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.

● Isolation of potential PGPR from rhizosphere sandy BRIS soil of Acacia mangium .

This study has isolated, characterized, and identified potential plant growth-promoting rhizobacteria (PGPR) with multiple PGP characteristics (N₂-fixation, P- and K-solubilization, IAA, and siderophores production) from the rhizosphere BRIS soil of Acacia mangium. A total of 24 pure colonies were isolated and only 8 colonies were selected for further evaluation of the growth rate in 5% organic molasses medium supplemented with 2% KNO₃. Based on the biochemical, potential PGP characteristics and growth performance, 3 superior PGPR strains were selected and identified as Paraburkholderia unamae (UA1), Bacillus amyloliquefaciens (UA6), and Enterobacter asburiae (UAA2) by partial sequencing of the 16S rRNA gene. The selected bacterial strains either in single or mixed (UA1 + UA6 + UAA2) cultures have shown a significant biochemical estimation of the PGP characteristics. Each strain has its own PGPR traits superiority with UA1 showing the best PGP characteristic followed by UA6 and UAA2. The use of mixed bacterial strains was beneficial as it showed the best performance in N₂-fixation, siderophores production, and significant effect on corn phenology, growth and yield compared to using a single strain. These types of microbes showed potential to be used as biofertilizer and should be exploited more.

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.

● Production, distributions and environmental risks of LM in Shaanxi were studied.

Shaanxi is a leading province in animal husbandry (AH) in China. However, the lack of provincial information on the characteristics and utilization potential of livestock manure (LM) hinders crucial management decisions. Therefore, we investigated the spatiotemporal distribution, availability and biogas potential of LM in Shaanxi, and examine the carbon emission reduction potential of AH. There has been a 1.26-fold increase in LM quantities in Shaanxi over the past 35 years, reaching 4635.6 × 10⁴ t by 2021. LM was mainly concentrated in northern Shaanxi and the eastern part of Hanzhong. Cattle and pig manure were the primary sources of LM, with the average LM land-load of 14.57 t·ha⁻¹ in 2021. While the overall AH in Shaanxi has not exceeded the environmental capacity, the actual scales of AH in Ankang and Hanzhong have already surpassed the respective environmental capacities, posing a higher risk of N and P pollutions. In 2021, the estimated biogas energy potential of LM was 1.2 × 10¹¹ MJ. From 2012 to 2021, the average carbon emission reduction potential in Shaanxi was 22%, with an average potential scale of 10%. The results of this research provide valuable data and policy recommendations for promoting the intensive use of LM and reducing carbon emissions in Shaanxi.

Bean (Phaseolus vulgaris) yields in Africa can be increased through the application of phosphorus and nitrogen fertilizers, as both nutrients are low in African soils. However, using greener technologies is preferred to mineral fertilizers for maintaining soil health. In this study, Rhizobium inoculation and moderate P supply (0, 10, 20, and 30 kg·ha⁻¹) to two bean cultivars were evaluated in consecutive years at Hawassa for their effects on plant growth, nodulation, and grain yield. The results showed that, relative to the uninoculated control, the two bean cultivars responded strongly to Rhizobium inoculation, with strain HB-429 outperforming strain GT-9 in both 2012 and 2013. Shoot biomass, nodule number and nodule dry matter per plant were increased by 9%, 40%, and 54%, respectively, in 2012, and by 20%, 39%, and 13% in 2013 with strain HB-429 inoculation. This resulted in increased pod number per plant, seed number per pod and grain yield by 56%, 51%, and 49% in 2012, and by 38%, 25%, and 69% in 2013, respectively, with strain HB-429 inoculation. Bean inoculation with GT-9 also increased grain yield by 35% and 68% in 2012 and 2013, respectively. Applying 10–30 kg·ha⁻¹ P to bean cultivars increased shoot biomass, nodule number, and nodule dry matter per plant by 7% to 39%, 23% to 59%, and 59% to 144% in 2012, respectively, and by 10% to 40%, 21% to 43%, and 12% to 35% in 2013, respectively. Relative to the zero-P control, adding only 10 kg·ha⁻¹ P increased pod number per plant, seed number per pod, and grain yield by 10%, 30%, and 61% in 2012, and by 11%, 11%, and 38% in 2013, respectively. The combined use of Rhizobium inoculation with low P application (20 kg·ha⁻¹) was found to increase bean production in Ethiopia and is thus recommended to resource-poor farmers.

● It is crucial to comprehensively summarize remediation technologies and identify future development directions.

Metal(loid) pollution has emerged as a pressing environmental issue in agriculture, garnering extensive public attention. Metal(loid)s are potentially toxic substances that infiltrate the soil through diverse pathways, leading to food chain contamination via plant uptake and subsequent animal exposure. This poses a serious threat to environmental quality, food security, and human health. Hence, the remediation of metal(loid)-contaminated agricultural soil is an urgent concern demanding immediate attention. Presently, the majority of research papers concentrate on established, isolated remediation technologies, often overlooking comprehensive field management approaches. It is imperative to provide a comprehensive summary of remediation technologies and identify future development directions. This review aims to comprehensively summarize a range of soil remediation and enhancement technologies, incorporating insights from multiple disciplines including physics, chemistry, biology, and their interdisciplinary intersections. The review examines the mechanisms of action, suitable scenarios, advantages, disadvantages, and benefits associated with each remediation technology. Particularly relevant is the examination of metal(loid) sources, as well as the mechanisms behind both established and innovative, efficient remediation and enhancement technologies. Additionally, the future evolution of remediation technologies are considered with the aim of offering a scientific research foundation and inspiration to fellow researchers. This is intended to facilitate the advancement of remediation technologies and establish a robust foundation for sustainable development of soil.

● First report of bacteria Paenarthrobacter nitroguajacolicus for effective control of cucumber corynespora leaf spot and promotion of cucumber growth.

Currently, the disease control in cucumber mainly depends on agrochemicals, which is not an environmentally benign strategy. Biocontrol bacteria not only resist plant pathogens but also promote plant growth, which is ecofriendly and sustainable option. A biocontrol bacterial strain BJ-5 was screened using Corynespora cassiicola as the target pathogen, and BJ-5 was determined to be Paenarthrobacter nitroguajacolicus by morphological and molecular methods. The effect of BJ-5 on C. cassiicola was studied, including the spore germination, cell membrane permeability and infected cucumbers. BJ-5 inhibited the germination of C. cassiicola spores in vitro and led to atrophy and deformation of the C. cassiicola budding tubes. BJ-5 caused the relative extracellular conductivity of C. cassiicola mycelia to increase compared with the control. Additionally, BJ-5 reduced the severity of cucumber corynespora leaf spot of cucumber infected with C. cassiicola. The inhibition efficacy of BJ-5 suspension as a foliar spray against cucumber corynespora leaf spot reached 63% inhibition, which is higher than a 5000-fold dilution of Luna-Son SC fungicide. In addition, BJ-5 was tested on the emergence of cucumber seedlings, recording the biomass and photosynthesis of cucumber during the growth period. BJ-5 at 1.5 × 10⁵ CFU·mL⁻¹ promoted the germination of cucumber seeds and increased biomass and photosynthesis at the adult plant stage. Also, the secondary metabolites of BJ-5 were determined. BJ-5 could produce chitinases, siderophore, cellulase, amylase and protease in the respective medium. Finally, adaptation assay of BJ-5 showed good salt tolerance and good adaptability in alkaline conditions, and that BJ-5 retains inhibition of fungi activity at higher temperatures. This is the first report of the biocontrol by P. nitroguajacolicus with antagonism to C. cassiicola and promote cucumber growth. This study indicates that P. nitroguajacolicus may serve as potential biocontrol agents against cucumber corynespora leaf spot fungus.

The study emphasizes the significance of biochar-based nanocomposites (BNCs) in tackling waste management challenges and developing valuable materials for environmental remediation and energy generation. BNCs have enhanced adsorption and catalytic properties by incorporating nanoparticles into a charcoal matrix, offering a dual benefit for waste treatment and environmental preservation. Using waste biomass for BNC production repurposes resources and reduces the ecological impact of waste disposal. This study also addresses the existing research gaps and uncertainties hindering the widespread use of biochar and BNCs. After almost a decade of extensive research, it is crucial to address and fill the gaps in knowledge, such as long-term impacts, carbon sequestration rates, potential deforestation and economic viability. Thoroughly analyzing the entire system and establishing adaptable governance is need to realize the full benefits of BNCs. This article discusses the urgent need for sustainable technology and solutions to solve global concerns, including waste management, water quality, soil health, climate change and renewable energy. Its aim is to improve existing research by providing a comprehensive overview of the potential of biochar and BNCs in achieving sustainability objectives. It also identifies research gaps and challenges that must be addressed, directing future research directions. It extensively reviews biochar-based nanocomposites derived from waste biomass as a sustainable solution for wastewater treatment and renewable bioenergy. The constraints and future research directions have been highlighted, offering essential perspectives on the potential of biochar and BNCs in addressing global sustainability issues.

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.

Fisheries in coastal and lakeside regions are increasingly facing sustainability challenges. This predicament has compelled these regions to shift toward economic diversification, with tourism emerging as a feasible alternative economic activity. This study focuses on a rural community adjacent to Erhai Lake in Dali City, Yunnan Province, China, examining its shift from a fishing-based economy to tourism over several decades. Employing an adaptive sustainable livelihood framework, this study assessed the livelihood transformation across various stages over an extended period, from both institutional and action-oriented perspectives, analyzing factors influencing sustainable livelihood transformation in lakeside communities and their subsequent effects. This research revealed several key insights. Firstly, tourism, as an alternative industry to fishing, not only faces increasingly stringent environmental protection policies but also confronts multiple challenges from the community level. Secondly, the improvement of the physical assets of locals within the tourism development, which can increase property-based income, has the potential to facilitate a sustainable transformation of their livelihoods. Thirdly, analysis identifies the pivotal role of human capital in the current transition process, with the influence of talent and innovative livelihood industry management models gaining prominence to ensure sustainability of this transformation.

Organic inputs are key to increasing soil organic carbon in agricultural soils. This study aimed to unravel the process of mineralization and humification of chicken manure (CM) and composted kitchen waste (KW) using an in situ litter-bag incubation experiment. The results indicated that over 50%, 64% to 72%, and 62% to 85% of the initial mass, carbon and nitrogen, respectively, were lost through incubation with a marked loss occurring during the first 28 days. Increased humic acids (HAs), humus (HS) and degree of humification, along with a decrease in the level of fulvic acids and precursors for humic substances were observed through incubation. By comparison, CM demonstrated higher carbon and nitrogen conservation efficiencies and greater humification compared to KW. Additionally, a higher degree of humifaction and larger quantities of HAs and HS were not favorable for carbon and nitrogen conservation. Further structural equation modeling indicated that microbial community had a strong effect on carbon loss and nitrogen release, while stoichiometric properties of organic inputs were the main determinant of the mineralization and humification processes. These findings will enhance understanding of litter decomposition in soils and provide valuable references for soil carbon sequestration with organic inputs.

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.

● Sugarcane and sugar beet yield and carbon footprint rose with time but profit declined

Climate change mitigation is a major challenge of human society. Currently, to this end, many countries including China are committed to achieving carbon neutrality within a few decades. China is a major sugarcane and sugar beet producing country and has one of the largest carbon footprint for sugarcane and sugar beet production globally. A comprehensive study was conducted on sugarcane and sugar beet crops grown in China for greenhouse gas (GHG) emissions mitigation potential, economic crop production from a sustainable sugar production perspective. Long-term trend analysis showed that yield and GHG emissions of sugarcane and sugar beet crops increased but the ratio of income to cost declined. Structural equation model analysis revealed nitrogen fertilizer and labor as the major drivers of GHG emissions for both sugarcane and sugar beet. For sugarcane and sugar beet, the path coefficient of N fertilizer were ‒0.964 and ‒0.835 and that of labor were 0.771 and 0.589, respectively. By transitioning the current cropping system to an improved model with optimized labor, N input and machinery use, the GHG emissions and total annual cost of sugarcane and sugar beet production can be reduced by 32% and 24%, respectively, by 2030, compared to a business-as-usual scenario. This is the first integrated and comparative study of environmental and economic sustainability of sugarcane and sugar beet production in China. These findings will enable all stakeholders of Chinese sugarcane and sugar beet industries to transform them into environmentally and economically sustainable sugar production.

This research explored a novel multimodal approach for disease management in cauliflower crops. With the rising challenges in sustainable agriculture, the research focused on a patch spraying method to control disease and reduce crop losses and environmental impact. For non-destructive disease assessment, a spectral sensor was used to collect spectral information from diseased and healthy cauliflower parts. The spectral data sets were analyzed using decision tree and support vector machine (SVM) algorithms to identify the most accurate model for distinguishing diseased and healthy plants. The chosen model was integrated with a low-volume sprayer (50‒150 L·ha^‒1), equipped with an electronic control unit for targeted spraying based on sensor-detected regions. The decision tree model achieved 89.9% testing accuracy, while the SVM model achieved 96.7% accuracy using hyperparameters: cost of 10.0 and tolerance of 0.001. The research successfully demonstrated the integration of spectral sensors, machine learning, and targeted spraying technology for precise input application. Additionally, the optimized sprayer achieved a 72.5% reduction in chemical usage and a significant time-saving of 21.0% compared to a standard sprayer for black rot-infested crops. These findings highlight the potential efficiency and resource conservation benefits of innovative sprayer technology in precision agriculture and disease management.