Search

Cultivation studies evaluating land-use histories and coevolutionary dynamics between humans and plants focus predominantly on domesticated species. Traditional anthropological divisions of "foragers" and "farmers" have shaped our understanding of ancient cultivation practices but have several limitations, including how people stewarded and managed nondomesticated species. To investigate the long-term effects of plant management in the Pacific Northwest, this study focuses on beaked hazelnut ( Corylus cornuta ) which has a long, precolonial history of management, transportation, and cultivation in British Columbia (BC, Canada). In particular, isolated hazelnut populations in northwestern BC are thought to be the result of historical transplanting and management. We sampled individual hazelnuts (n = 219) representing three distinct regions in and assessed 9,650 genome-wide SNPs identified with nextRAD genotyping-by-sequencing libraries to test for population genetic structure. We used linear measurements of individuals to assess morphological phenotypes and to identify variation between individuals and lineages. These data reveal shared genetic clusters in distant and disjunct northwestern and interior regions consistent with the movement of humans across the landscape. We also find several small genetically distinct populations in the northwestern region. The Genetic structure of hazelnut in the previously labeled "disjunct" region in Gitxsan, Ts'msyen, and Nis g a'a homelands is consistent with the enduring influence of people on the distribution of purportedly "wild" plant species. Our results support the hypothesis that hazelnut was likely transplanted long distances and also managed in situ. This study highlights the often-overlooked agency of Indigenous Peoples in shaping species range distributions in North America., Competing Interests: Competing interests statement:The authors declare no competing interest.

Sugar is the largest agricultural crop by mass and has seen a rapid increase in consumption around the world. There are widespread public health efforts to curb sugar intake through targeted policies given its association with noncommunicable diseases. Although curbing sugar intake aligns with sustainable diets that meet essential environmental and health targets, such a shift may be challenging from a political economy perspective. Utilizing sugar for other purposes such as the production of microbial protein, biofuels, and bioplastics, or using sugar lands to grow other food items, or rewilding could provide health and environmental win-wins that could be more politically palatable. Here, we explore several potential scenarios to illustrate the option space from which national and international stakeholders could choose locally appropriate pathways for alternative utilization of sugar or its lands. While beneficial, such alternative pathways would require the integration of environmental, economic, and health policies to provide a smoother diet transition that reduces stakeholder tensions. Given the trade in sugar as a commodity crop, international approaches that compensate sugar producers for avoided production or incentivize them for redirecting sugars to other uses will be needed. Such approaches could borrow concepts from Just Transition Partnerships that have been applied to energy system transitions in ensuring a transition for major exporters of sugar cash crops across low- and middle-income nations., Competing Interests: Competing interests statement:The authors declare no competing interest.

Nitrogen (N) fertilizer is often used in production practice to effectively maintain crop productivity; however, low nitrogen use efficiency (Nue) has always been a problem. Specifically, the transformation and utilization of nitrogen fertilizer by biochar and the driving mechanisms remain unclear. We used four biochar application rates (0, 3750, 7500, and 11,250 kg·ha -1 ) and analyzed the effects of biochar on nitrogen fertilizer utilization, residue, and loss over three years using 15 N isotope tracer technology. The results showed that (1) biochar improved the nitrogen use efficiency of maize plants, reduced total nitrogen loss, and increased the maize yield. Compared to the control treatment in the same year, the application of 7500 kg·ha -1 biochar increased the nitrogen use efficiency by 24.27 %, 27.77 %, and 35.82 %, and the yield increased by 21.1 %, 26.7 %, and 24.5 %, respectively. (2) Biochar increased the proportion of mineral nitrogen supplied by fertilizer in the mineral nitrogen pool. The application of 7500 kg·ha -1 biochar increased mineral nitrogen by 3.05 %, 3.22 %, and 3.8 %, respectively, compared to the control treatments in the same year. Biochar promoted the transformation of nitrogen in the 0-40 cm soil layer to three different soil nitrogen pools, especially the organic nitrogen pool. (3) Biochar significantly improved the soil bacterial community and increased the abundances of N transformation functional genes. The redundancy analysis (RDA) showed that the gdhA mineralization gene was the driving factor of nitrogen fertilizer transformation, contributing 43.6 % of the variance. In summary, the application of 7500 kg·ha -1 of biochar for two consecutive years was conducive to maintaining farmland soil fertility, while its use would not be recommended for more than three consecutive years., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Flooding of paddy fields enhances methane (CH 4 ) emissions and arsenic (As) mobilisation, which are crucial issues for agricultural greenhouse gas emissions and food safety. Birnessite (δ-MnO 2 ) is a common natural oxidant and scavenger for heavy metals. In this study, birnessite was applied to As-contaminated paddy soil. The capacity for simultaneously alleviating CH 4 emissions and As mobility was explored. Soil microcosm incubation results indicated that birnessite addition simultaneously reduced CH 4 emissions by 47 %-54 % and As release by 38 %-85 %. The addition of birnessite decreased the dissolved organic carbon (DOC) contents and altered its chemical properties. Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS) results showed that birnessite reduced the labile fractions of proteins, carbohydrates, lignins, tannins, and unsaturated hydrocarbons, however, increased the abundance of condensed aromatic structures, suggesting the polymerisation of dissolved organic matter (DOM) by birnessite. The degradation of labile fractions and the polymerisation of DOM resulted in an inventory of recalcitrant DOM, which is difficult for microbes to metabolise, thus inhibiting methanogenesis. In contrast, birnessite addition increased CH 4 oxidation, as the particulate methane monooxygenase (pmoA) gene abundance increased by 30 %. The enhanced polymerisation of DOM by birnessite also increased As complexation with organics, leading to the transfer of As to the organic bound phase. In addition, the decrease in ferrous ion [Fe(II)] concentrations with birnessite indicated that the reductive dissolution of Fe oxides was suppressed, which limited the release of arsenite [As(III)] under reducing conditions. Furthermore, birnessite decreased As methylation and shaped the soil microbial community structure by enriching the metal-reducing bacterium Bacillus. Overall, our results provide a promising method to suppress greenhouse gas emissions and the risk of As contamination in paddy soils, although further studies are needed to verify its efficacy and effectiveness under field conditions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The environmental impact of livestock is often evaluated separately from the other agricultural activities involved in an integrated system, such as that of the rearing of Piemontese cattle in the area of origin of the breed. The most frequently used assessment methods (e.g. Footprint approaches or a Life Cycle Assessment) are in fact often used, through a product-based approach, to analyse a single productive process, but such methods do not consider the production of agro-ecological services, and they neglect the interactions that characterise complex systems. Moreover, such methods often only consider the negative aspects of the environmental impact and misrepresent less intensive agriculture practices. However the current gaps in knowledge about the carbon sequestration of agricultural ecosystems, which are complex and integrated systems, require further investigation and other types of analysis tools. A carbon (C) balance of 1223 Piemontese breed beef farms, located in North-West Italy, has been calculated to evaluate whether such a method could be applied to overcome the aforementioned limitations, to evaluate whether it could be used to describe a complex and integrated system, to highlight the relationships that exist between rearing and agricultural activities and to characterise their environmental roles. Conducting a mass balance involves considering the input and output material flows and their accumulation within a system. Thus, the data necessary to quantify the C input, output and internal fluxes of a system at the farm gate, pertaining to the vegetable and animal production processes (productive factors, crop yields, animal performances, productions and sales, reuses), were collected from official documentation, and were then completed and verified through site visits. The mass balance of the system was transformed into C fluxes using stoichiometric coefficients. The fluxes evaluated for the balance were then used to estimate the changes in the C stocks to highlight not only the C emissions or losses from the system, but also their contributions towards reducing environmental hazards. A sensitivity analysis was carried out to evaluate the uncertainty and the robustness of the obtained results. The net C exchange from plants was the flux that contributed the most, amounting to 94.3 % of the inputs, and this was followed by soil losses and animal gases released through respiration and enteric fermentation, which amounted to 42.8 and 36.2 % of the outputs, respectively. The C stored and released by the considered system was calculated considering the C fluxes. Plant, animal and soil storage sites were included in the system, whereas the air site was left out. A constant C content was assumed for the soil. The productive activities of the selected group of beef farms in the Consortium were calculated to remove 96.1 10 3  t of C from the atmosphere (air site) over a period of one year, and that this amount of C was transferred to plant growth and agricultural products (plant site) and to an increase in live weight (LW) of the animals (animal site). The rates of the stored C to agricultural and wooded areas and to the LW of the animals slaughtered in one year were 1.18 t ha -1 and 2.24 t C t -1 LW, respectively. The sensitivity analysis demonstrated that the C balance was always positive, even for the worst scenario. This study has shown that the examined beef production system, when analysed as an integrated and complex system, can be considered an important C sink and that it is necessary to reconsider the role that livestock, and ruminants in particular, play in the global greenhouse effect., Competing Interests: Declaration of competing interest The authors have no competing interests to declare that are relevant to the content of this article., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Since their discovery, the prolonged and widespread use of antibiotics in veterinary and agricultural production has led to numerous problems, particularly the emergence and spread of antibiotic-resistant bacteria (ARB). In addition, other anthropogenic factors accelerate the horizontal transfer of antibiotic resistance genes (ARGs) and amplify their impact. In agricultural environments, animals, manure, and wastewater are the vectors of ARGs that facilitate their spread to the environment and humans via animal products, water, and other environmental pathways. Therefore, this review comprehensively analyzed the current status, removal methods, and future directions of ARGs on farms. This article 1) investigates the origins of ARGs on farms, the pathways and mechanisms of their spread to surrounding environments, and various strategies to mitigate their spread; 2) determines the multiple factors influencing the abundance of ARGs on farms, the pathways through which ARGs spread from farms to the environment, and the effects and mechanisms of non-antibiotic factors on the spread of ARGs; 3) explores methods for controlling ARGs in farm wastes; and 4) provides a comprehensive summary and integration of research across various fields, proposing that in modern smart farms, emerging technologies can be integrated through artificial intelligence to control or even eliminate ARGs. Moreover, challenges and future research directions for controlling ARGs on farms are suggested., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The importance for multi-dimensional priority-setting of agricultural innovations is growing, given that agricultural technologies usually play multiple roles for smallholder farmers. This study assesses agricultural technologies based on their multi-dimensional impacts in the drylands of sub-Saharan Africa and South Asia. The study applies the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) to a set of promising agricultural technologies and uses three outcome criteria: the benefit-cost ratio, poverty reduction, and nutrition security. The technologies are related to important cereals and grain legumes grown in these regions: sorghum, pearl millet, and finger millet; groundnut, cowpea, chickpea, lentil, pigeon pea, and soybean. The results show that the top technologies based on individual criteria can differ from the top technologies identified using a combination of criteria. For example, in semi-arid southern Africa, a promising technology which involves integrated pest management for cowpea ranks among the top five technologies which can reduce poverty. However, the analysis involving TOPSIS shows that nutrition security is more important in that region compared to poverty. As such, the top 5 technologies with the highest multi-dimensional impact for semi-arid southern Africa do not involve a cowpea technology; rather, they are all related to pigeon pea, a nutritious grain legume which is currently more consumed in that region compared to cowpea. One limitation of this study is that it did not consider all the roles of agricultural technologies in the drylands of sub-Saharan Africa and South Asia; this should be considered in future studies involving TOPSIS or other MCDM techniques. Nevertheless, the study shows that TOPSIS can successfully be used for multi-dimensional ex-ante impact assessment of agricultural technologies, and thus can support the prioritization of investments targeting agricultural research for development., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Gbegbelegbe et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The integration of IoT (Internet of Things) devices has emerged as a technical cornerstone in the landscape of modern agriculture, revolutionising the way farming practises are viewed and managed. Smart farming, enabled by interconnected sensors and technologies, has surpassed traditional methods, giving farmers real-time, granular information into their farms. These Internet of Things devices are responsible for collecting and sending greenhouse data (temperature, humidity, and soil moisture) for the required destination, to provide a comprehensive awareness of environmental factors critical to crop growth. Therefore, ensuring that the received data are accurate is a challenge, thus this paper investigates the optimization of Agriculture IoT communication, proposing a complete strategy for improving data transmission efficiency within smart farming ecosystems. The proposed model intends to maximize energy efficiency and data throughput in the context of essential agricultural factors by using Lagrange optimization and a Deep Convolutional Neural Network (DCNN). The paper focus on the ideal communication required distance between IoT sensors that measure humidity, temperature, and water levels and central control systems. The investigation emphasizes the critical necessity of these data points in guaranteeing crop health and vitality. The proposed technique strives to improve the performance of agricultural IoT communication networks through the integration of mathematical optimization and cutting-edge deep learning. This paradigm change emphasizes the inherent link between precise achievable data rate and energy efficiency, resulting in resilient agricultural ecosystems capable of adjusting to dynamic environmental conditions for optimal crop output and health., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Alturif et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

The world aims to ensure environmental sustainability and consolidate agricultural factor productivity, yet the excruciating impact of climate change coincides and remains a persistent threat. Therefore, the study aims to estimate the technical efficiency of cereal crop yields and investigate the impacts of climate change on agricultural factor productivity. For this purpose, panel data from 35 sub-Saharan African countries between 2005 and 2020 was employed. For analysis, the pooled OLS and stochastic frontier models were employed. The results revealed that in the region, the average efficiency score for producing cereal crops between 2005 and 2020 was 83%. The stochastic frontier model results showed that labour contributed 51.5% and fertilizer contributed 5.7% to raising the technical efficiency of cereal crop yields, whereas arable land per hectare reduced the technical efficiency of cereal yields by 44.7%. The pooled OLS regression result showed that climate change proxies (CO2 and methane emissions) diminish land, labour, and fertilizers productivity at a 1% significance level, whereas GDP per capita boosts significantly the total factor productivity in agriculture. This confirmed how climate change reduced land, labour, and fertilizer input productivity. The results concluded that the region had a high level of technical efficiency; of which labour and fertilizer inputs contributed the largest share; however, their productivity has dwindled due to climate change. To increase cereal crop yield efficiency and limit the adverse effects of climate change on agricultural input productivity, the region should combine skilled and trained labour and fertilizer with sophisticated agriculture technologies, as well as adopt climate resistance technologies (weather- resistant variety seed and planting revolution mechanisms)., Competing Interests: the authors have no any computing interest, (Copyright: © 2024 Alemu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Water is a fundamental necessity for humans and a critical resource in agriculture. However, water scarcity poses a significant challenge, especially considering that agriculture accounts for a substantial portion of freshwater usage. The inadequate monitoring resources in agriculture lead to unnecessary wastage of water, affecting crop growth and the water supply. This challenge has spurred us to focus on the agricultural domain, aiming to conserve water by imparting intelligence into irrigation systems by converging IoT and machine learning technologies. Our study has proposed a Smart Irrigation System (SIS), designed to operate remotely, leveraging open-source IoT platforms. Utilizing IoT and machine learning methodologies can effectively optimize water usage in irrigation practices. The designed system comprises hardware and software tools, where comprehensive data is monitored through an application interface. The sensor's interface with a 32-bit microcontroller is used to gather data such as environmental temperature, humidity, and soil moisture and temperature. The user (farmer) continuously receives real-time updates about the condition of the farmland through the Blynk app. The app triggers a notification advising the user to start or stop watering based on pre-set threshold values of soil moisture. Additionally, users can control the water pump remotely through the app. The data collected from the deployed smart irrigation system was used to train a machine learning algorithm incorporating weather parameters and soil temperature to predict soil moisture content. This trained model aims to offer guidance for future assessments of unknown soil samples based on the weather conditions., Competing Interests: Declarations. All authors have read, understood, and have complied as applicable with the statement on "Ethical responsibilities of Authors" as found in the Instructions for Authors and are aware that with minor exceptions, no changes can be made to authorship once the paper is submitted. Conflict of interest: The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

The Palmer Drought Severity Index (scPDSI) and the Standardized Precipitation Evapotranspiration Index (SPEI) are two of the most commonly used drought indices. However, scPDSI and SPEI at a specific scale are often used interchangeably to characterize meteorological drought, agricultural drought, or terrestrial water availability, leading to potential inaccuracies in research outcomes. This study thus presents a global-scale assessment of the applications of scPDSI and SPEI at various timescales (SPEIs) in these contexts. Our findings indicate that scPDSI is more suitable for monitoring agricultural drought than meteorological drought, and highlight the effectiveness of SPEI at one month scale (SPEI01) for meteorological drought. Additionally, SPEI at nine months scale (SPEI09) is more appropriate for agricultural drought. Regarding their relationship with vegetation water stress, scPDSI and SPEI09 are more closely associated with root-zone soil moisture, while SPEI01 is most closely linked to vapor pressure deficit. Furthermore, we evaluate the capability of scPDSI and SPEI in representing terrestrial water availability by analyzing the responses of diverse vegetation indicators to them, including the Normalized Difference Vegetation Index (NDVI), Leaf Area Index (LAI), Solar-Induced Chlorophyll Fluorescence (SIF), and Gross Primary Productivity (GPP). All four vegetation indicators show the highest sensitivity of negative response to SPEI01 in cold climate regions, suggesting SPEI01 is most applicable in these regions. In drylands, vegetation indicators exhibit higher sensitivity of positive responses to SPEI at six months scale (SPEI06) and SPEI09, indicating SPEI06 and SPEI09 effectively characterize water availability in such areas. These findings enhance the understanding of scPDSI and SPEI, providing clearer guidelines for their global-scale applications in meteorological drought, agricultural drought, and terrestrial water availability., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Biochar application to amend acidified tobacco-soils can enhance tobacco quality and reduce nitrous oxide (N 2 O) emissions. Microplastics from agricultural mulch are commonly found in cash-crop farmland soils and, together with biochar, affect soil N 2 O emissions. In this study, we applied three types of microplastics (polyethylene, PE; polylactic acid, PLA; polybutylene adipate terephthalate, PBAT) and rice biochar alone or in combination to acidified tobacco planting soil in central China to investigate their effects on soil N 2 O emissions, soil chemical properties, nitrogen-cycle-related functional genes, and microbial functional diversity during a 35-day laboratory incubation period. Significant increases in N₂O emissions were observed with PE and PLA, which raised emissions by 15.96 % and 21.52 %, respectively. Additionally, different microplastics affected soil N₂O emissions through distinct regulatory pathways. Co-application of microplastics and biochar suppressed N 2 O emissions compared to microplastics alone. Biochar mitigates N 2 O emissions mainly by increasing the abundance of the nosZ gene. It can remediate soil contaminated by microplastics and reduce their negative impacts on the soil environment. This study provides deeper insight into the effects of microplastics on soil nitrogen cycling and biochar-mitigated remediation of microplastic-contaminated soil., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Lettuce is an established food commodity in the UK increasingly facing supply challenges in winter due to adverse weather events and rising energy costs. We investigate whether an agroecologically grown salad mix of lettuce and underutilised leafy greens produced in the Azores, Portugal, could be part of a sustainable solution. We performed a Life Cycle Assessment to compare the environmental impacts of this salad mix with four other value chains for winter salad supply to the UK: conventional open-field lettuce production chains in Spain using (1) current irrigation practices; (2) 100 % desalinated irrigation water; or hydroponic controlled environment agriculture within the UK powered by (3) the national electricity mix; (4) 100 % wind-generated electricity. Results indicated that the leafy-greens agroecological value chain incurred the smallest environmental burdens across 7 to 11 of 16 impact categories studied. Substituting Spanish winter salad supply with agroecological leafy green production in the Azores, if well managed, could reduce many environmental burdens whilst diversifying leafy greens intake. Nevertheless, all winter value chains were associated with larger environmental burdens than conventional open-field production of lettuce in the UK summer, pointing to the importance of seasonal consumption and wider adoption of agroecological techniques to effectively reduce environmental impact., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The environmental and multi-sectoral challenges faced by small islands requires consideration of sustainability issues. The sustainability challenges in these regions involve in particular the achievement of a greater autonomy through the development of local resources. This is a complex system that encompasses interconnections between the resources available and the land use. In this article we focus on the study of the Water-Energy-Food (WEF) nexus, and propose an integrated and systemic approach to do so. Our contribution consists in studying food system sustainability of small islands by exploring the reciprocal influences between the valorization of local WEF resources and land use competition for various integrated WEF scenarios. Additionally, we integrate dietary behaviors and demonstrate their close interlinking with land use practices, and thus their impact on the potential for transitioning towards a more sustainable food system. To achieve this, we present a generic combined Geographical Information Systems (GIS) and robust optimization model. This model is then applied to Reunion island using collected real data. Our approach aims to assist local policymakers, at the island scale, by constructing insightful scenarios to facilitate informed decision-making. Our results highlight the need to save land space when developing local resources through effective land use management policies combined with a shift in food practices. This shift would imply in particular, to convert some of the sugarcane areas into subsistence farming. Furthermore, the results emphasize the importance of transitioning consumption practices under various integrated WEF scenarios, showcasing our model as an insightful decision-support tool., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Authier et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Long-term continual straw return can enhance soil quality and increase crop yields by perpetually altering the soil environment. However, little is known about how different straw return methods affect soil physicochemical properties, enzymatic processes, and crop yields. The study aims to determine how different straw return practices improve soil structure, nutrients, enzyme activities, and maize yields. In this experiment, a field trial was conducted in 2021-2022 in the irrigated area of the Tumochuan Plain Irrigation District to determine the effects of four different straw returns on soil structure, nutrients, enzyme activities, soil quality, and maize yields. The four types of straw return included straw incorporation with deep tillage (DPR), straw incorporation with subsoiling (SSR), no-tillage mulching straw return, and farmer's shallow rotation (CK). Our results showed that DPR and SSR enhanced water retention capacity by reducing the bulk weight of the 0-45 cm soil layer. DPR and SSR significantly increased soil organic C (12.76%), total nitrogen (25.32%), and available nutrients (i.e. AP, NO 3 - -N) in the 0-45 cm soil layer compared to CK, whereas there were no differences between straw-returned treatments in the 0-15 cm soil layer. Finally, maize yield was significantly increased by 13.14% and 11.41% in the second year of DPR and SSR, respectively, compared to CK. This study demonstrated that DPR and SSR are effective at enhancing the agricultural utilization of crop residues and represent feasible strategies for improving physical, chemical, and biological processes in continuous maize cropping systems, leading to increased crop productivity., Competing Interests: Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Integrating native ornamental plants with substrate amended with lignocellulosic biomass and biochar in vertical sub-surface flow constructed wetlands offers a novel and effective approach to wastewater treatment. This study evaluates the potential of mesocosm constructed wetland systems using native ornamental plants (Canna indica, Lilium wallichianum, and Tagetes erecta) grown in substrates amended with lignocellulosic biomass and biochar. The influent and effluent were analyzed for pH, total dissolved solids (TDS), biochemical oxygen demand (BOD), chemical oxygen demand (COD), phosphorus (PO 4 -P), and nitrogen forms, i.e., ammonia (NH 4 -N) and nitrate (NO 3 -N) for 5 weeks. Investigated mesocosms showed an average removal efficiency of 49.21% for BOD, 53.76% for COD, 40.64% for NH 4 -N, 41.76% for NO 3 -N, and 21.53% for PO 4 -P. Canna indica demonstrated the highest removal efficiencies, achieving 58.19% for BOD and 64.49% for COD, followed by Lilium wallichianum with 56.12% for BOD and 62% for COD, while Tagetes erecta showed lower efficiencies of 49.63% for BOD and 52.24% for COD. The result shows that the designed mesocosms are a promising nature-based alternative to the technologically complex and expensive conventional technologies, with numerous additional ecological benefits. This study also indicates that the locally available organic materials are effective substrate components for constructed wetlands and after their use in wetlands; these digested organic materials may further be used as an effective source of nutrient-rich fertilizers or soil amendments in agriculture., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Crop foraging by primates is a prevalent form of human-wildlife conflict, especially near protected areas. This behavior poses significant economic challenges for subsistence farmers, jeopardizing both livelihoods and conservation efforts. This study aimed to assess patterns of primate crop-foraging events and estimate maize damage in protected and unprotected fields in southern Ethiopia. Data were collected over 12 months between 2020 and 2021 in the Sodo Zuriya and Damot Gale districts of Southern Ethiopia. A team of six field experts and 25 farmers participated in the study, during which maize damage inflicted by primates was assessed using 25 deployed camera traps. Linear mixed models were used to explore the relationship between maize damage by primates and spatio-temporal variables. Olive baboons and grivet monkeys were found to target maize more frequently during June, July, and August. Olive baboons forage in the morning, while grivet monkeys do so in the afternoon. The average maize yield losses due to primate damage were 43.1% in protected fields and 31.4% in unprotected fields. Of the total damage, 43.1% occurred in protected fields situated 50 meters from the forest edge. Conversely, unprotected fields experienced lower rates of damage: 14.4%, 13.2%, 3.7%, and 0.1% at distances of 50 m, 100 m, 200 m, and 300 m from the forest edge, respectively. Camera traps captured 47 photos of baboons, 21 photos of grivet monkeys, and documented eight primate crop-foraging events. This study revealed that maize fields within 50 meters of the forest edge faced significant damage. Despite the use of wire mesh fencing, it was largely ineffective in deterring olive baboons and grivet monkeys. Additionally, while human guarding is often considered an effective protective strategy, these findings suggest its ineffectiveness due to inconsistent implementation. Overall, this study provides valuable insights for promoting primate conservation and mitigating human-primate conflicts., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Deneke et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Herbicide use is widespread in agricultural production to control weeds prior to and after planting and to "burndown" weeds in the spring for conservation tillage. Whether conservation tillage adoption leads to higher herbicide usage has been a question of policy relevance for decades in the United States. Older U.S. studies using standard statistical and economic techniques have not consistently demonstrated higher herbicide usage levels among producers practicing conservation tillage, but these studies did not fully account for other practices, economic, or agronomic factors. To provide a more timely and comprehensive understanding of the importance of herbicides to conservation tillage, this study achieves two objectives with the most recent, nationally representative data from the US Department of Agriculture. First, it describes trends and compares conservation tillage and herbicide usage among field corn and soybean producers, similar to previous studies using standard economic techniques. Second, a Classification and Regression Tree (CART) model is employed-a novel methodology relative to previous studies that offers distinct advantages over traditional regression modeling-to evaluate the importance of herbicide use for conservation tillage adoption while accounting for other factors. Pairwise mean comparisons for field corn and soybeans indicated that herbicide usage pre-emergence was significantly higher with conservation tillage, but there was no consistent, significant differences in herbicide usage post-emergence. The CART analysis (with prediction accuracy ranging from 68-72%) also showed that pre-emergent use of glyphosate was the strongest predictor (with predicted probabilities from 0.83-0.86) of conservation tillage for field corn in 2016 and soybeans in 2018. Other factors such as the use of crop rotations, highly erodible land, region, and farm size were also strong predictors of conservation tillage. These findings highlight the importance and complexity of herbicide use in the adoption of conservation tillage for U.S. field corn and soybeans., Competing Interests: Authors report no competing interests., (Copyright: This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.)

The sunflower crop is one of the most pro sources of vegetable oil globally. It is cultivated all around the world including Haryana, in India. However, its mapping is limited due to the requirement of huge computation power, large data storage capacity, small farm holdings, and information gap on appropriate algorithms and spectral band combinations. Thus, the current work has been done to identify an appropriate machine learning (ML) algorithm (after comparing random forest (RF) and support vector machine (SVM) reported as the best classifiers for land use and land cover) and best band combinations (among the six combinations (including Sentinel-Optical, Sentinel-SAR, and combined-Optical-SAR in single data and time series manner) for Sunflower crop mapping in Ambala and Kurukshetra districts of Haryana using Google Earth Engine (GEE) cloud platform. GEE cloud-computing system combined with RF and SVM provided Sunflower map with an accuracy ranging from 0.0% to 90% in various bands and classifiers combinations but was the highest for the RF with single date optical data. The SVM classifier tuned with parameters like kernel type, degree, gamma, and cost provided better overall accuracy for the classification of land use and land cover along with Sunflower ranging from 98.09% to 98.44% and Kappa coefficient ranging from 0.96 to 0.97 for optical data and combination of SAR and optical time series. The platform is efficient and applicable for a larger part of the country to map Sunflower and other crops with currently identified combinations of satellite data and methodology due to the availability of satellite images, advanced ML algorithms, and analytical modules on a single platform., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Shifting cultivation, an age-old agricultural practice, is a major factor in forest cover change across Southeast Asia, where repeated cycles of vegetation disturbance and regrowth lead to far-reaching environmental and socio-economic impacts. The present study aims to assess the spatio-temporal patterns of vegetation disturbance and regrowth caused by shifting cultivation in Tripura state of India, over the past three decades, utilizing temporal segmentation of time-series Landsat data. The study analyzed vegetation disturbance and regrowth patterns in a shifting cultivation landscape from 1991 to 2020 using normalized burn ratio trends through LandTrendr, validated by the TimeSync tool. Six land use and land cover classes, viz., forests and trees outside forests, rubber plantation, shifting cultivation, water bodies, agriculture, and settlements, were mapped with an accuracy of 83.08% using a random forest classifier. This classification enabled the identification of the effective study area, which included forest areas with shifting cultivation patches. The analysis revealed that 2533.96 km 2 of the study area remained undisturbed, 568.43 km 2 experienced low-magnitude disturbance, 1501.11 km 2 were moderately disturbed, and 184.82 km 2 were highly disturbed. The shifting cultivation cycles in the study area show considerable variation. Low-magnitude disturbance indicates a single slash-and-burn event in the past three decades, moderate-magnitude disturbance involves fallow periods of over 10 years, and high-magnitude disturbance occurs with fallow periods of less than 8 years. The study revealed a shift from traditional shifting cultivation to more permanent agricultural practices in parts of Tripura. In response to incentives for commercial crops, cultivators are increasingly adopting long-term cultivation, including the growing of pineapple, areca nut, and rubber, as well as intercropping with papaya, banana, lemon, tapioca, pepper, and ginger. These plots are, however, abandoned if the yields become economically unviable. The expansion of monoculture cultivation significantly reduces the available area for shifting cultivation, thereby compelling jhum cultivators to revisit their jhum patches more frequently. This study is a first-of-its-kind attempt in the Indian context and sheds light on changing patterns in an age-old agricultural practice., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

At the dawn of new millennium, policy makers and researchers focused on sustainable agricultural growth, aiming for food security and enhanced food quality. Several emerging scientific innovations hold the promise to meet the future challenges. Nanotechnology presents a promising avenue to tackle the diverse challenges in agriculture. By leveraging nanomaterials, including nano fertilizers, pesticides, and sensors, it provides targeted delivery methods, enhancing efficacy in both crop production and protection. This integration of nanotechnology with agriculture introduces innovations like disease diagnostics, improved nutrient uptake in plants, and advanced delivery systems for agrochemicals. These precision-based approaches not only optimize resource utilization but also reduce environmental impact, aligning well with sustainability objectives. Concurrently, genetic innovations, including genome editing and advanced breeding techniques, enable the development of crops with improved yield, resilience, and nutritional content. The emergence of precision gene-editing technologies, exemplified by CRISPR/Cas9, can transform the realm of genetic modification and enabled precise manipulation of plant genomes while avoiding the incorporation of external DNAs. Integration of nanotechnology and genetic innovations in agriculture presents a transformative approach. Leveraging nanoparticles for targeted genetic modifications, nanosensors for early plant health monitoring, and precision nanomaterials for controlled delivery of inputs offers a sustainable pathway towards enhanced crop productivity, resource efficiency, and food safety throughout the agricultural lifecycle. This comprehensive review outlines the pivotal role of nanotechnology in precision agriculture, emphasizing soil health improvement, stress resilience against biotic and abiotic factors, environmental sustainability, and genetic engineering., Competing Interests: Declarations Consent for publication Not applicable. Conflict of interest The authors declare no competing interests. Consent to participate Not applicable. Ethics approval Not applicable., (© 2024. The Author(s).)

This paper presents a novel approach to agricultural disease diagnostics through the integration of Deep Learning (DL) techniques with Visual Question Answering (VQA) systems, specifically targeting the detection of wheat rust. Wheat rust is a pervasive and destructive disease that significantly impacts wheat production worldwide. Traditional diagnostic methods often require expert knowledge and time-consuming processes, making rapid and accurate detection challenging. We drafted a new, WheatRustDL2024 dataset (7998 images of healthy and infected leaves) specifically designed for VQA in the context of wheat rust detection and utilized it to retrieve the initial weights on the federated learning server. This dataset comprises high-resolution images of wheat plants, annotated with detailed questions and answers pertaining to the presence, type, and severity of rust infections. Our dataset also contains images collected from various sources and successfully highlights a wide range of conditions (different lighting, obstructions in the image, etc.) in which a wheat image may be taken, therefore making a generalized universally applicable model. The trained model was federated using Flower. Following extensive analysis, the chosen central model was ResNet. Our fine-tuned ResNet achieved an accuracy of 97.69% on the existing data. We also implemented the BLIP (Bootstrapping Language-Image Pre-training) methods that enable the model to understand complex visual and textual inputs, thereby improving the accuracy and relevance of the generated answers. The dual attention mechanism, combined with BLIP techniques, allows the model to simultaneously focus on relevant image regions and pertinent parts of the questions. We also created a custom dataset (WheatRustVQA) with our augmented dataset containing 1800 augmented images and their associated question-answer pairs. The model fetches an answer with an average BLEU score of 0.6235 on our testing partition of the dataset. This federated model is lightweight and can be seamlessly integrated into mobile phones, drones, etc. without any hardware requirement. Our results indicate that integrating deep learning with VQA for agricultural disease diagnostics not only accelerates the detection process but also reduces dependency on human experts, making it a valuable tool for farmers and agricultural professionals. This approach holds promise for broader applications in plant pathology and precision agriculture and can consequently address food security issues., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Biological control has been effectively exploited by mankind since 300 CE. By promoting the natural regulation of pests, weeds, and diseases, it produces societal benefits at the food-environment-health nexus. Here we scrutinize biological control endeavours and their social-ecological outcomes through a holistic 'One-Health' lens, recognizing that the health of humans, animals, plants, and the wider environment are linked and interdependent. Evidence shows that biological control generates desirable outcomes within all One Health dimensions, mitigating global change issues such as chemical pollution, biocide resistance, biodiversity loss, and habitat destruction. Yet, its cross-disciplinary achievements remain underappreciated. To remedy this, we advocate a systems-level, integrated approach to biological control research, policy, and practice. Framing biological control in a One Health context helps to unite medical and veterinary personnel, ecologists, conservationists and agricultural professionals in a joint quest for solutions to some of the most pressing issues in planetary health., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Emission reduction, heat mitigation, and improved access to water and food provision are increasingly critical challenges for urban areas in the context of global climate change adaptation and mitigation. The revival of local agricultural production is often lauded as a potential nature-based solution. However, an expansion of peri-urban agriculture (peri-UA) may entail significant ecosystem trade-offs. This study explores the impacts on the food-water-climate nexus of different scenarios of peri-urban agricultural expansion in a semi-arid, Mediterranean climate, addressing local food provision, freshwater use, local temperature regulation, global climate change mitigation, and the trade-offs thereof. We estimate food provision and irrigation water requirements based on a georeferenced urban metabolism approach along with atmospheric and biosphere models to examine four land-use scenarios in the Metropolitan Area of Barcelona. Our study reveals that a 31 % (+17.27 km 2 ) and 115 % (+64.25 km 2 ) increase in the current peri-UA in the AMB, results in an increase in local food production of 24 % (+16,503 tons year -1 ) and 86 % (+58,940 tons year -1 ), and irrigation water requirements by 10.0 % (+3.2 hm 3 ) and 43.5 % (+14.1 hm 3 ), respectively. The expansion of irrigated peri-UA potentially reduces near-surface temperatures by 0.7 °C, albeit temperature reductions in the densest urban areas are minimal. Since the additional peri-UA is achieved by replacing natural non-forested and forest areas, the simulations predict reductions in the net ecosystem productivity of up to 18.5 % and total carbon stocks by 3.3 %. This integrated approach combining urban metabolism and atmospheric modelling to determine the trade-offs appears to be a promising tool for informing land-use decision-making in the context of urban climate adaptation and mitigation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

This study explores the integration of crop phenology models and machine learning approaches for predicting rice phenology across China, to gain a deeper understanding of rice phenology prediction. Multiple approaches were used to predict heading and maturity dates at 337 locations across the main rice growing regions of China from 1981 to 2020, including crop phenology model, machine learning and hybrid model that integrate both approaches. Furthermore, an interpretable machine learning (IML) using SHapley Additive exPlanation (SHAP) was employed to elucidate influence of climatic and varietal factors on uncertainty in crop phenology model predictions. Overall, the hybrid model demonstrated a high accuracy in predicting rice phenology, followed by machine learning and crop phenology models. The best hybrid model, based on a serial structure and the eXtreme Gradient Boosting (XGBoost) algorithm, achieved a root mean square error (RMSE) of 4.65 and 5.72 days and coefficient of determination (R 2 ) values of 0.93 and 0.9 for heading and maturity predictions, respectively. SHAP analysis revealed temperature to be the most influential climate variable affecting phenology predictions, particularly under extreme temperature conditions, while rainfall and solar radiation were found to be less influential. The analysis also highlighted the variable importance of climate across different phenological stages, rice cultivation patterns, and geographic regions, underscoring the notable regionality. The study proposed that a hybrid model using an IML approach would not only improve the accuracy of prediction but also offer a robust framework for leveraging data-driven in crop modeling, providing a valuable tool for refining and advancing the modeling process in rice., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Soil microbial communities are major drivers of cycling of soil nutrients that sustain plant growth and productivity. Yet, a holistic understanding of the impact of abandoned agricultural land reclamation on the soil microbe is still poorly understood, especially for the microbial community assembly mechanisms. Here, we investigated the influence of reclamation on the relative importance of stochastic and deterministic processes in shaping microbial community assembly. After reclaiming abandoned cropland for corn and soybean cultivation, the fungal community assembly was shifted to stochastic processes, while bacterial communities remained predominantly influenced by stochastic processes. Our study revealed that reclamation did not significantly affect bacterial diversity, community niche breadth, and community similarity. In contrast, fungal communities exhibited lower alpha diversity, narrower niche breadths, greater niche overlap and higher community similarity in corn and soybean cultivation treatment in response to reclamation. Moreover, soil pH and soil available phosphorus were the most important environmental factors influencing fungal richness, niche breadths, community assembly processes, and community similarity. Together, the reclamation of abandoned cropland promoted the transformation of the fungal community assembly from deterministic process to a stochastic process, leading to decreased fungal diversity and broader ecological niche width, ultimately resulting in greater similarity among fungal communities. This finding provides insight into the varied responses of microbial diversity and ecological process to abandoned cropland reclamation, offering valuable guidance for the conservation and sustainable management of abandoned cropland in future land-use practices., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

The mechanism by which algal organic matter (AOM) affects the clogging of ceramic emitters remains unclear, which partially reduces the operational life of agricultural water distribution systems. This paper systematically investigated the clogging phenomenon of ceramic emitters under three different AOM concentrations. The results of irrigation tests revealed that the AOM significantly affects the degree of clogging of ceramic emitters, with higher AOM concentrations leading to faster flow reduction. By analyzing the original irrigation water and effluent and characterizing the clogged emitter surface, it was demonstrated that AOM was intercepted by the ceramic emitter, forming a dense biofilm. Infrared spectroscopy analysis revealed that polysaccharides and humic substances were the main clogging components. The clogging kinetics showed that as the AOM concentration increased, the clogging of the filter cake layer gradually become dominant. Further, the mechanism of interaction between AOM and silica ceramic emitters was explored from a microscopic perspective using molecular dynamics (MD) simulation with bovine serum albumin (BSA), sodium alginate (SA), and humic acid (HA) as model clogging substances in AOM. The simulation results indicated a strong interaction between AOM molecules and silica molecules dominated by electrostatic attraction, with the strength of the interaction as SA > HA > BSA. It was hypothesized that early clogging was mainly formed by polysaccharides and humic substances combining with silica molecules, while BSA was retained later by combining with organics on the clogging layer or through size exclusion. This study provides insights into bio-clogging in microporous ceramic emitters and may offer a theoretical basis for developing measures to control emitter clogging., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Enhancement of microbial assimilation of inorganic nitrogen (N) by straw addition is believed to be an effective pathway to improve farmland N cycling. However, the effectiveness of differently pretreated straws on soil N 2 O emissions and soil N-acquiring enzyme activities remains unclear. In this study, a pot experiment with four treatments (I, no addition, CK; II, respective addition of maize straw, S; III, composted maize straw under no fungi inoculation, SC; and IV, composted maize straw under fungi inoculation, SCPA) at the same quantity of carbon (C) input was conducted under the same amount of inorganic N fertilization. Results showed that the seasonal cumulative N 2 O emissions following the SCPA treatment were the lowest at 4.03 kg N ha -1 , representing a significant reduction of 19 % compared with the CK treatment. The S and SC treatments had no significant effects on N 2 O emissions. The decrease of soil N 2 O emissions following the SCPA treatment was mainly attributed to the increase of microbial N assimilation and the increased abundance of functional genes related to N 2 O reductase. The SCPA treatment significantly decreased soil alkaline phosphatase (ALP) activity and increased leucine aminopeptidase (LAP) activity at the basal fertilization, while increased soil ALP and LAP activity, decreased soil N-Acetyl-β-D-Glucosidase (NAG) activity at harvest. Compared with the CK treatment, the S, SC, and SCPA treatment significantly increased soil β-glucosidase (β-GC) activity at harvest. The decrease in the (NAG+LAP)/ALP ratio following the SCPA treatment indicated that the composted maize straw under fungi inoculation alleviated microbial N limitation at harvest. Moreover, PICRUSt analysis also suggested that the SCPA treatment increased the abundance of bacterial genes associated with N assimilation and N 2 O reduction, whereas the S and SC treatment did not significantly affect the abundance of N 2 O reduction genes compared with the CK treatment. Our results suggest that the composted maize straw under fungi inoculation would reduce the risk of N 2 O emissions and effectively mitigate the microbial N limitation in dryland wheat system., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Arsenic pollution in paddy fields has become a public concern by seriously threatening rice growth, food security and human health. In this review, we delve into the biogeochemical behaviors of arsenic in paddy soil-rice system, systemically revealing the complexity of its migration and transformation processes, including the release of arsenic from soil to porewater, uptake and translocation of arsenic by rice plants, as well as transformation of arsenic species mediated by microorganism. Especially, microbial processes like reduction, oxidation and methylation of arsenic, and the coupling of arsenic with carbon, iron, sulfur, nitrogen cycling through microbes and related mechanisms were highlighted. Environmental factors like pH, redox potential, organic matter, minerals, nutrient elements, microorganisms and periphyton significantly influence these processes through different pathways, which are discussed in this review. Furthermore, the current progress in remediation strategies, including agricultural interventions, passivation, phytoremediation and microbial remediation is explored, and their potential and limitations are analyzed to address the gaps. This review offers comprehensive perspectives on the complicated behaviors of arsenic and influence factors in paddy soil-rice system, and provides a scientific basis for developing effective arsenic pollution control strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Grasslands globally deliver many ecosystem services, including water management to alleviate flood risk reduction. Two replicated field experiments were conducted to study how agricultural forage species with diverse rooting systems, sown as single species, affected rooting, soil structure and earthworm populations, and consequently water infiltration to understand how they each might influence flood risk from grasslands. Experiment One showed soils under red clover (Trifolium pratense), white clover (Trifolium repens) and chicory (Cichorium intybus) had higher infiltration rates three years after establishment, compared to perennial ryegrass (Lolium perenne). Higher red clover and chicory root biomass or increased earthworm abundance under white clover may have caused these effects. Experiment Two monitored infiltration at intervals over several years post establishment to understand the timeframe for changes in rates; plantain (Plantago lanceolata) was sown as an additional forage. Infiltration declined post establishment, the timing and extent of decline varying with forages; forage effects were significant after 27 months (P < 0.05). Infiltration rates were higher under red and white clover compared to ryegrass, with chicory and plantain intermediate (P < 0.05). Forages again differed in likely mechanisms delivering higher water infiltration, notably between the two clover species. White clover had higher earthworm biomass (P < 0.05), whereas red clover had a higher average root diameter compared to the other forages (P < 0.05). Drivers of intermediate benefits of chicory and plantain also differed: chicory had higher earthworm abundance (month 38) compared to plantain, which had higher average root diameter compared to ryegrass (month 41); 30 months post-establishment soil bulk density was lower under both forages compared to ryegrass and red clover, with white clover intermediate (P < 0.05); bulk density and penetration resistance did not relate to infiltration. Findings demonstrate that a shift from perennial ryegrass-dominated pastures to swards with more contrasting forages provides an ecohydrological approach to mitigating flood risk and climate adaptation., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Christina Marley reports The PROSOILplus project received funding through the Welsh Government Rural Communities - Rural Development Programme 2014–2020, which is funded by the European Agricultural Fund for Rural Development and the Welsh Government. Christina Marley reports IBERS receives strategic funding from BBSRC, UKRI. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Feeding a growing population with healthy food while preserving the natural ecosystem's resources is a critical challenge of our century. In Egypt, the increasing demand for food commodities and the intensive consumption of freshwater resources by the agricultural sector is hindering the food system capability to achieve sustainable food and nutrition security. The Egyptian government has recently prioritized the improvement of dietary supply through the efficient use of the locally available natural resources. However, strategies to transform the Egyptian agri-food system towards the sustainable satisfaction of healthy dietary needs have not been yet studied. Here, a novel approach has been introduced, able to combine the environmental advantages of an optimized crop allocation with the benefits of providing a healthy diet. First, a physically based agro-hydrological model is used to assess the crop water needs associated with the current cropland and diet (baseline). Subsequently, a linear optimization crop allocation algorithm is designed to replace crops in order to maximize green water productivity, while meeting the dietary requirements of the EAT-Lancet diet. Our results show that through an optimized crop allocation entailing the production of healthy and varied food, it is possible to reach an average 95 % satisfaction of the demand for healthy food items by local agricultural products, with an 8 % reduction in local freshwater consumption and a 90 % increase in crop profitability. Our study suggests the prioritization of the promotion of the dietary guidelines by the EAT-Lancet Commission at the national level in Egypt, to support human health against malnutrition and the development of a more sustainable and efficient food system., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The expanding global population and the use of conventional agrochemical pesticides have led to the loss of crop yield and food shortages. Excessive pesticide used in agriculture risks life forms by contaminating soil and water resources, necessitating the use of nano agrochemicals. This article focuses on synthesis moiety and use of nanopesticides for enhanced stability, controlled release mechanisms, improved efficacy, and reduced pesticide residue levels. The current literature survey offered regulatory frameworks for commercial deployment of nanopesticides and evaluated societal and environmental impacts. Various physicochemical and biological processes, especially microorganisms and advanced oxidation techniques are important in treating pesticide residues through degradation mechanisms. Agricultural waste could be converted into nanofibers for sustainable composites production, new nanocatalysts, such as N-doped TiO 2 and bimetallic nanoparticles for advancing pesticide degradation. Microbial and enzyme methods have been listed as emerging nanobiotechnology tools in achieving a significant reduction of chlorpyrifos and dimethomorph for the management of pesticide residues in agriculture. Moreover, cutting-edge biotechnological alternatives to conventional pesticides are advocated for promoting a transition towards more sustainable pest control methodologies. Application of nanopesticides could be critical in addressing environmental concern due to its increased mobility, prolonged persistence and ecosystem toxicity. Green synthesis of nanopesticides offers solutions to environmental risks associated and using genetic engineering techniques may induce pest and disease resistance for agricultural sustainability. Production of nanopesticides from biological sources is necessary to develop and implement comprehensive strategies to uphold agricultural productivity while safeguarding environmental integrity., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

As rice has no physiological capacity of fixing nitrogen in the soil, its production had always been reliant on the external application of nitrogen (N) to ensure enhanced productivity. In the light of improving nitrogen use efficiency (NUE) in rice, several advanced agronomic strategies have been proposed. However, the soared increase of the prices of N fertilizers and subsequent environmental downfalls caused by the excessive use of N fertilizers, reinforces the prerequisite adaptation of other sustainable, affordable, and globally acceptable strategies. An appropriate alternative approach would be to develop rice cultivars with better NUE. Conventional breeding techniques, however, have had only sporadic success in improving NUE, and hence, this paper proposes a new schema that employs the wholesome benefits of the recent advancements in omics technologies. The suggested approach promotes multidisciplinary research, since such cooperation enables the synthesis of many viewpoints, approaches, and data that result in a comprehensive understanding of NUE in rice. Such collaboration also encourages innovation that leads to developing rice varieties that use nitrogen more effectively, facilitate smart technology transfer, and promotes the adoption of NUE practices by farmers and stakeholders to minimize ecological impact and contribute to a sustainable agricultural future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Accurate crop yield predictions are crucial for farmers and policymakers. Despite the widespread use of ensemble machine learning (ML) models in computer science, their application in crop yield prediction remains relatively underexplored. This study, conducted in Canada, aims to assess the potential of five distinct ensemble ML models-Adaptive Boosting (AdaBoost), Gradient Boosting Machine (GBM), XGBoost, LightGBM, and Random Forest (RF)-in predicting crop yields chosen for their ability to manage complex datasets and their strong performance potential. The study integrated various factors, including climate variables, satellite-derived vegetation indices, soil characteristics, and honeybee census data. Data preparation comprised two main steps: first, climate variables were interpolated and averaged for croplands in ArcGIS Pro, along with averaging vegetation indices and soil characteristics. Honeybee census data was also incorporated. Second, the data was organized in Python to create a structured format for models' input. The models' accuracy was assessed using Root Mean Squared Error (RMSE), R-squared, and Mean Absolute Error (MAE). XGBoost emerged as the most accurate model, with the lowest MAE (68.70 for canola and 39.47 for soybeans), lowest RMSE (119.48 for canola and 102.39 for soybeans), and highest R-squared values (0.95 for canola and 0.96 for soybeans) on the test dataset. The study also assessed crop yields under various climate change scenarios, finding minimal variations across the scenarios, but significant negative impacts on canola and soybean yields across Canada. Honeybee colonies were identified as the most influential factor on crop yields, contributing 52.34 % to canola and 57.18 % to soybean yields. This research provides detailed crop yield maps of canola and soybeans at the Census Consolidated Subdivisions (CCS) level across Canada's agricultural landscape, offering valuable forecasts for localized decision-making. Additionally, it offers a proactive strategy for climate change preparedness, assisting farmers and stakeholders optimise resource allocation and manage risks effectively., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Biochar application is an effective strategy to address Agro-climatic challenges. However, the agro-environmental impacts of different biochar technology models are lacking of systematic summaries and reviews. Therefore, this paper comprehensively reviews recent developments derived from published literature, delving into the economic implications and environmental benefits of three distinct process namely technologies-pyrolysis, gasification, and hydrothermal carbonization. This paper specifically focuses on the agricultural life cycle assessment (LCA) methodology, and the influence of biochar preparation technologies and products on energy consumption and agricultural carbon emissions. LCA analysis shows that process and feedstock pose a predominant role on the properties and production rate of biochar, while gasification technology exhibits excellent economic attributes compared to the other two technologies. Biochar applications in agricultural has the beneficial effect of sequestering carbon and reducing emissions, especially in the area of mitigating the carbon footprint of farmland. However, the complexity of the composition of the prepared feedstock and the mismatch between the biochar properties and the application scenarios are considered as potential sources of risks. Notably, mechanism of carbon sequestration and emission reduction by soil microorganisms and agro-environmental sequestration by biochar application remains unclear, calling for in-depth studies. We review novel aspects that have not been covered by previous reviews by comparing the technical, economic, and environmental benefits of pyrolysis, gasification, and hydrothermal carbonization systematically. Overall, this study will provide a valuable framework to environmental implications of biochar preparation, application, and life cycle assessments., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Phytoremediation coupled with agroproduction (PCA) model contributes to sustainable agriculture and environmental management. This study investigated the impact of continuous cropping early/late season rice (RR) and Sedum alfredii-rice rotation (SR) on soil physical and chemical properties, as well as their relationships with soil microbial community. In 2022, SR treatment significantly increased pH value and organic matter content by 7 % and 17 %, respectively, compared to the levels in 2020, while RR treatment showed no change. RR treatment resulted in a significant decrease in soil concentrations of Ca, Mg, and K by 18.42 %, 29.01 %, and 7.77 %, respectively. Furthermore, SR treatment saw reductions of 29.62 % in total Cd and 38.30 % in DTPA extractable Cd in the soil. Over the two years, both treatments notably influenced the diversity, structure, and network of the rhizosphere bacterial and fungal communities, which are crucial for nutrient cycling and plant health. Notably, SR treatment exhibited a more complex network compared to RR, suggesting a greater impact on the interconnected systems. Therefore, these findings highlight the potential of Sedum rotation system to rehabilitate contaminated soils while supporting agricultural practices, which is essential for food security and environmental sustainability. This research direction holds promise for future exploration and application in the fields of phytoremediation and agroecology., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

The differential responses of methanogenesis and methanotrophy to elevated carbon dioxide concentrations ([CO 2 ]) (e[CO 2 ]) and elevated temperature ([T]) (e[T]) may lead to dramatic changes in the response of CH 4 emissions from rice paddies to global warming. In this study, we systematically investigated the responses and mechanisms of CH 4 flux from rice paddies to e[CO 2 ] and e[T] based on the production and oxidation of CH 4 . The CH 4 flux, soil properties, and soil methanogenesis and methanotrophy were observed under CK (ambient [CO 2 ] + ambient [T]), EC (e[CO 2 ] by 200 μmol mol -1  + ambient [T]), ET (ambient [CO 2 ] + e[T] by 2 °C), and ECT (e[CO 2 ] by 200 μmol mol -1  + e[T] by 2 °C) treatments. The results revealed that EC, ET, and ECT significantly increased the cumulative amount of CH 4 (CAC) in the rice paddies by 10.63, 15.20, and 11.77 kg ha -1 , respectively, compared with CK. ECT increased the CAC in the rice paddies by 1.14 kg ha -1 compared with EC. Moreover, EC, ET, and ECT significantly enhanced the methane production potential (MPP) and methane oxidation potential (MOP) and tended to increase the mcrA gene abundance of the methanogens. EC tended to prompt the pmoA gene abundance of the methanotrophs, but the effect of ET on the pmoA gene abundance was less consistent across the growth stages. ECT significantly decreased the relative abundances of Methanosarcina and Methylocystis (Type II) by 4.9 % and 14.2 %, respectively, while it increased the relative abundance of Methylosarcina (Type I) by 24.0 % compared with CK. Overall, the increased MPP/MOP, mcrA/pmoA, and microbial biomass carbon under climate change increased the CH 4 flux from the rice paddies. The contribution of e[CO 2 ] to the CH 4 flux was significantly enhanced by e[T], which could further exacerbate the risk of global climate change induced by e[CO 2 ]., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Phosphorus (P) is essential for plants but often limited in soils, with microbes playing a key role in its cycling. P deficiency in crops can be mitigated by applying by-products like sludge and struvite to enhance yield and sustainability. Here, we evaluated the contribution of four different types of fertilizers: i) conventional NPK; ii) sludge; iii) struvite; and iv) struvite+sludge in a semiarid maize plantation to the availability of P and the responses of the soil microbiome. We investigated the effects of these treatments on the relative abundance of bacterial and archaeal genes and proteins related to organic P mineralization, inorganic P solubilization, and the P starvation response regulation through a multi-omic approach. Moreover, we explored the impact of maize phenology by collecting samples at germination and flowering stages. Our findings suggest that the phenological stage has a notable impact on the abundance of P cycle genes within bacterial and archaeal communities, particularly regarding the solubilization of inorganic P. Furthermore, significant variations were observed in the relative abundance of genes associated with different P cycles in response to various fertilizer treatments. Sludge and struvite application improved P availability, which was related to an increase in the relative abundance of Sphingomonas (Proteobacteria) and Luteitalea (Acidobacteria) respectively, and genes related to inorganic P solubilization. Furthermore, we observed a substantial taxonomic clustering of functional processes associated with the P cycle. Among the dominant bacterial populations containing P-related genes, those microbes possessing genes linked to the solubilization of inorganic P typically did not harbor genes associated with the mineralization of organic P. This phenomenon was particularly evident among members of Actinobacteria. Overall, we reveal important shifts in bacterial and archaeal communities and associated molecular processes, stressing the intricate interplay between fertilization, phenology, and P cycling in agroecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Excessive utilization of chemical fertilizers in mango orchards not only hampers the attainment of sustainable harvests but also poses significant ecological detriments. This investigation proposes a promising solution by advocating the judicious replacement of chemical fertilizers with organic fertilizer (OF) and slow-release fertilizer (SRF), with potential to bolster soil health and augment crop productivity. In light of the promise held by these alternatives, it is imperative to establish detailed fertilization protocols for enhanced sustainable practices in mango farming. This two-year field study employed a comprehensive suite of seven fertilization strategies, unveiling that a 25 % chemical fertilizers substitution with OF and SRF improved mango yields by 12.5 % and 11.3 %, respectively, over standard practices. Additionally, these approaches substantially augmented the nutritional quality of mangoes, evident from Vitamin C enhancements of 53.9 % to 56.9 %, and improvements in sugar-to-acid ratio (19.2 %-30.3 %) and solid-to-acid ratio (12.1 %-25.3 %). Notably, the application of OF and SRF led to increased leaf nitrogen and phosphorus concentrations, while simultaneously reducing soil phosphorus and potassium levels. Furthermore, these fertilizers fostered the growth of beneficial soil microorganisms, namely Actinobacteria and Proteobacteria, and strengthened the synergy within the soil bacterial community, hence optimizing bacterial competition and nutrient cycling. The study proposes that the adoption of OF or SRF can effectively regulate soil nutrient balance, promote resilient and functional soil bacterial ecosystems, and ultimately improve mango yield and fruit quality. It recommends a fertilization scheme incorporating 25 % organic or slow-release nitrogen to align with ecological sustainability goals, promoting a more vigorous and resilient soil and crop system., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Hydrothermal cracking involves the conversion of organic waste into efficient fertilizer through hydrolysis at temperatures ranging from 180 to 220 °C and pressures of 1.5 to 2.45 MPa, which offers significant advantages in shortening the production cycle, enhancing efficiency, and decomposing antibiotics. As a result, it holds immense practical value for promoting organic fertilizer manufacturing processes globally. The products derived from hydrothermal cracking can be categorized into solid and liquid components. Extensive research has focused on the composition and use of solids, while studies on liquids have mainly examined basic characteristics. The study aimed to comprehensively analyze the components in liquid products prepared through hydrothermal cracking and evaluate their suitability as liquid fertilizers. Specifically, we employed rigorous analytical techniques to accurately identify and quantify medium and trace elements, organic acids, amino acids, and plant growth regulators. Furthermore, we carried out a planting experiment to assess the yield and soil changes following the application of liquid products in maize cultivation. The experimental data revealed that the liquid product contained abundant medium and trace elements, along with 6.22 g/L free amino acids and 9.22 g/L organic acids. It is noteworthy that this liquid product contained 1.22 × 10 5  pg/mL ABA, 6.26 × 10 3  pg/mL IAA, 1.07 × 10 2  pg/mL IBA, and 3.60 × 10 -2  pg/mL GA3. The utilization of this liquid product has the potential to enhance the disease resistance of maize crops and promote the accumulation of nitrate nitrogen in the soil. By understanding the composition of liquid products via hydrothermal cracking, valuable insights can be gained into their potential benefits for agricultural and ecological applications., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

In plant environments, there exist heterogeneous microbial communities, referred to as the plant microbiota, which are recruited by plants and play crucial roles in promoting plant growth, aiding in resistance against pathogens and environmental stresses, thereby maintaining plant health. These microorganisms, along with their genomes, collectively form the plant microbiome. Research on the plant microbiome can help unravel the intricate interactions between plants and microbes, providing a theoretical foundation to reduce pesticide use, enhance agricultural productivity, and promote environmental sustainability. Despite significant progress in the field of research, unresolved challenges persist due to ongoing technological limitations and the complexities inherent in studying microorganisms at small scales. Recently, synthetic community (SynCom) has emerged as a novel technique for microbiome research, showing promising prospects for applications in the plant microbiome field. This article systematically introduces the origin and distribution of plant microbiota, the processes of their recruitment and colonization, and the mechanisms underlying their beneficial functions for plants, from the aspects of composition, assembly, and function. Furthermore, we discuss the principles, applications, challenges, and prospects of SynCom for promoting plant health., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Terracing is widely recognized as an effective strategy for mitigating soil erosion and preserving soil quality. This study aimed to evaluate the variations in soil aggregate C, N, and P composition, as well as the soil quality index (SQI), in subtropical citrus orchards of different plantation ages (PA) and across various terrace positions (TP). Surface soil samples (0-20 cm) were collected from four TP categories: terrace wall (TW), slub ditch (SD), under grove (UG), and between grove (BG), across varying PA (5, 15, 25, 35, and 45 years). The results showed the C, N, and P concentrations in most soil aggregates, along with the SQI of the slub ditch and under grove, increased significantly with plantation age. Compared to the 5-year-old plantations, the SQI of the slub ditch and under grove increased by 84 % and 66 % at 45 years, respectively. The aggregate stability and SQI of BG generally trended upwards but declined at 25 and 35 years. By 45 years, the SQI of the terrace wall was significantly lower than that of other positions, being 58 %, 61 %, and 39 % lower compared to the slub ditch, under grove, and between grove, respectively. Additionally, the C/P and N/P ratios of the terrace wall were higher than those of other positions, indicating phosphorus limitation in TW. Path analysis revealed plantation ages had greater effects on SQI. Aggregate stability and soil properties showed significant positive impacts on SQI. Overall, as plantation age increased, the differences in SQI among the slub ditch, under grove, and between grove decreased, while the terrace wall exhibited the weakest erosion resistance. Therefore, efforts should be made to restore the ecological function of the terrace wall, such as by colonizing it with moss. Additionally, reasonable tillage plans, including appropriate fertilization, should be formulated to enhance orchard soil quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Soil organic matter has been well acknowledged as a natural solution to mitigate climate change and to maintain agricultural productivity. Microbial necromass is an important contributor to soil organic carbon (SOC) storage, and serves as a resource pool for microbial utilization. The trade-off between microbial births/deaths and resource acquisition might influence the fate of microbial necromass in the SOC pool, which remains poorly understood. We coupled soil microbial assembly with microbial necromass contribution to SOC on a long-term, no-till (NT) farm that received maize (Zea mays L.) stover mulching in amounts of 0 %, 33 %, 67 %, and 100 % for 8 y. We characterized soil microbial assembly using the Infer Community Assembly Mechanisms by Phylogenetic-bin-based null model (iCAMP), and microbial necromass using its biomarker amino sugars. We found that 100 % maize stover mulching (NT100) was associated with significantly lower amino sugars (66.4 mg g -1 SOC) than the other treatments (>70 mg g -1 SOC). Bacterial and fungal communities responded divergently to maize stover mulching: bacterial communities were positive for phylogenetic diversity, while fungal communities were positive for taxonomic richness. Soil bacterial communities influenced microbial necromass contribution to SOC through determinism on certain phylogenetic groups and bacterial bin composition, while fungal communities impacted SOC accumulation through taxonomic richness, which is enhanced by the positive contribution of dispersal limitation-dominated saprotrophic guilds. The prevalence of homogeneous selection and dispersal limitation on microbial cell wall-degrading bacteria, specifically Chitinophagaceae, along with increased soil fungal richness and interactions, might induce the decreased microbial necromass contribution to SOC under NT100. Our findings shed new light on the role of microbial assembly in shaping the dynamics of microbial necromass and SOC storage. This advances our understanding of the biological mechanisms that underpin microbial necromass associated with SOC storage, with implications for sustainable agriculture and mitigation of climate change., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Anthropogenic nitrogen (N) inputs substantially influence the N cycle in agricultural ecosystems. However, the potential links among various environmental factors, nitrogen functional genes, and transformation rates under N fertilization remain poorly understood. Here, we conducted a five-year field experiment and collected 54 soil samples from three 0-4 m boreholes across different treatments: control, N-addition (nitrogen fertilizer) and NPK-addition (combined application of nitrogen, phosphorus and potassium fertilizers) treatments. Our results revealed pronounced variations in soil physiochemical parameters, metal concentrations and antibiotic levels under both N and NPK treatments. These alternations induced significant shifts in bacterial and fungal communities, altered NFG abundance and composition, and greatly enhanced rates of nitrate reduction processes. Notably, nutrients, antibiotics and bacteria exerted a more pronounced influence on NFGs and nitrate reduction under N treatment, whereas nutrients, metals, bacteria and fungi had a significant impact under NPK treatment. Furthermore, we established multidimensional correlations between nitrate reduction gene profiles and the activity rates under N and NPK treatments, contrasting with the absence of significant relationships in the control treatment. These findings shed light on the intricate relationships between microbial genetics and ecosystem functions in agricultural ecosystem, which is of significance for predicting and managing metabolic processes effectively., Competing Interests: Declaration of competing interest We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Farm dams, also known as 'agricultural ponds', are ubiquitous features of agricultural landscapes globally. Those accessed by livestock have high methane (CH 4 ) emissions per unit area relative to other freshwater systems. Fencing dams and installing water troughs to prevent livestock from entering the dams are promising strategies to improve water quality and substantially reduce their carbon footprints. However, previous studies only measured the effects of fencing on methane diffusive emissions without considering ebullitive fluxes (i.e., methane bubbles), which is often the dominant emission pathway in smaller water bodies. Also, data is lacking on how the benefits of fencing farm dams vary across seasons. Using Australia as a test case, this study investigates the benefit of fencing off farm dams by monitoring total CH 4 (diffusion + ebullition) and carbon dioxide (CO 2 ) in summer and winter. Fenced dams had 72 % lower CH 4 emissions in summer and 92 % lower in winter than unfenced dams. Similarly, CO 2 -equivalent (CO 2  + CH 4 ) fluxes were lower in fenced dams by 59 % in summer and 73 % in winter. Fenced dams had higher water quality, with 51 % less total dissolved nitrogen, 57 % less phosphorous, and 23-49 % more dissolved oxygen. Average daily air temperature was a key predictor of CH 4 emissions from farm dams, underscoring the importance of considering temporal dynamics for estimating yearly farm dam emissions. We confirmed that excluding livestock from entering farm dams using fences significantly mitigates CH 4 emissions and enhances water quality, and these benefits are maintained seasonally., Competing Interests: Declaration of competing interest The authors declare no conflict of interest., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Climate warming has become a global issue of close concern, and China, as a significant agricultural country, has an increasing demand for food, which requires China to increase carbon reduction in this industry. This paper accounts for carbon emissions from the food production industry (CEFI) using the input-output method, then screens the influencing factors of CEFI based on Random Forest (RF), analyzes the heterogeneous effects of the influencing factors on CEFI in different clusters through K-means-SHAP, and finally explores the potential of carbon emissions from this industry for the period 2024-2040. The study's findings are as follows: First, there are apparent inequalities in CEFI, especially between provinces, which are gradually increasing. Second, addressing people's consumption awareness and behaviors is not the fundamental solution to alleviate CEFI; instead, it should focus on sustainable agricultural production transformation and "food miles" in the transportation phase. In addition, attention needs to be paid to the impacts of fertilizer application, transport modes, and livestock management on the CEFI of each cluster. Finally, the study suggests that around 2028, 70% of China's provinces will be at the "carbon peak" and that less developed and more developed regions have more significant potential to reduce emissions. In this regard, this paper encourages a series of policies that are key to promoting the sustainable development of CEFI, such as reducing the volume and efficiency of traditional fertilizers, vigorously developing organic fertilizer inputs, strengthening technological innovation and R&D inputs in the transportation sector, and steadily supporting germplasm innovation in the livestock sector., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

This study evaluated the potential for combining dehydrated human urine with one other form of organic waste to create circular fertilisers tailored to meet the macronutrient demand of 15 major crops cultivated globally. Through a reverse blending modelling approach, data on 359 different organic wastes were used to identify 38 fertiliser blends. Materials found to be particularly suitable as blending materials were various biochars and ashes, due to their low nitrogen and high phosphorus and/or potassium content, and byproduct concentrates, due to their high phosphorus content, since the nitrogen content of human urine is disproportionately higher than its phosphorus content. Several organic wastes were suitable for fertilising more than one crop. The macronutrient content of the simulated fertiliser blends was comparable to that of blended inorganic fertilisers, but only a few blends precisely matched the macronutrient demand of crops. Fertilising crops with some simulated fertilisers would potentially result in excess application of one or more macronutrients, and thus overfertilisation. For organic wastes with data available on their content of six or more heavy metals, it was found that the simulated fertilisers generally met European Union regulations on use of fertilisers of organic origin in agriculture. Overall, these findings suggest that fertiliser blends combining dehydrated human urine and organic wastes, both of which are widely available globally, could replace inorganic blended fertilisers in agriculture. Such recycling would help the global food system and water sector transition to circularity and promote better management of plant-essential nutrients in society., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Prithvi Simha and Björn Vinnerås are co-owners of Sanitation360 AB, a university spin-off commercialising various technologies for recycling human urine. They declare that the work reported in this study was not influenced by their involvement in this company. Prithvi Simha reports financial support was provided by Research Council of Norway. Bjorn Vinneras reports financial support was provided by Swedish Research Council. Paula Loureiro Paulo reports financial support was provided by Coordination of Higher Education Personnel Improvement. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Space agriculture, pivotal for sustainable extraterrestrial missions, requires plants that can adapt to altered gravitational conditions. This study delves into the adaptive responses to altered gravity of Wolffia globosa, an aquatic plant known for its rapid growth and high nutritional value. The research aimed to analyse the effect of simulated microgravity and hypergravity on relative growth rate (RGR), morphological characteristics, protein content, and the correlation between plant size and growth rate of Wolffia globosa. The study highlighted the responses of the species to altered gravity, uncovering inherent variability among seven different clones of W. globosa. Results show a base variability among clones in terms of RGR, size and protein content. Furthermore, some clones are affected by simulated microgravity, showing a decrease in RGR. Differently, under hypergravity, clones showed RGR higher than in 1 g control, therefore revealing a novel plant response to hypergravity. Morphological adaptations to gravity alterations were also evident. Among the studied clones, significant morphological changes were observed, further underlining the peculiar adaptation to the hypergravity environment. Differently, under simulated microgravity, morphology was generally stable across clones. A key finding of the study was the significant negative correlation between RGR and the physical dimensions of the plants: the fastest growth was associated with the smallest dimensions of the plants. This correlation might have practical implications in selecting clones for space cultivation, that leads to compact yet highly productive clones. The analysis of the protein content of all the clones revealed mostly no significant changes under hypergravity. Otherwise, a general decrease in protein content was observed under simulated microgravity. Overall, the study confirms the suitability of W. globosa for space agriculture and provides new insights into the perspective of using W. globosa as an alternative crop species for protein production for manned Space missions. Furthermore, it underscores the need for focusing on the clones and the selection of the W. globosa plants that are best adapted to the environmental conditions of space; therefore, selecting those with the best combination of biomass production (by means of growth rate, size), and protein content., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Background and Aims Cotton-peanut rotation is a sustainable farming practice that enhances land utilization and promotes the sustainable development of agriculture. Crop rotation can reduce the occurrence of pests and diseases, as different crops have varying levels of resistance to such threats. Additionally, by alternating the types of crops grown, the soil environment is changed, which can lead to the elimination of favorable conditions for pathogens and pests, thereby alleviating the impact of these issues. Furthermore, cotton-peanut rotation can improve soil fertility.To investigate the effects of different crop rotation systems on crop yield, soil nutrients, and soil microbial communities., Methods: Using high-throughput sequencing technology, investigate the soil microbial diversity in the root zone after cotton-peanut rotation.Various planting patterns, including cotton continuous cropping (MC), peanut continuous cropping (HC), peanut-cotton-peanut rotation (HR), and fallow (X), were established to assess variations in crop yield, soil nutrients, and soil microbial diversity., Results: Significant differences were observed in crop yield, soil nutrients, and soil microbial community structure among different planting patterns. The HR system significantly increased the output compared with the HC and MC systems. Additionally, HR exhibited significantly lower total nitrogen (N) and basic nitrogen (BN) contents than HC and MC, whereas MC showed lower total potassium (K) and available potassium (AK) contents. HR led to a decrease in soil bacterial diversity but an increase in fungal diversity, with Ascomycota and Mortierellomycota being dominant. Various bacteria (Chloroflexi, Bacteroidota, and Actinobacteriota) associated with organic matter degradation and nutrient cycling were found across different planting systems, enhancing material cycling efficiency. Furthermore, Planctomycetota bacteria related to crop nutrient synthesis and Glomeromycota bacteria aiding plant nutrient absorption were significantly higher in the MC system than in the HR or HC systems. Redundancy analysis indicated a significant negative correlation between crop rotation and soil fungal community, whereas Ascomycota exhibited a significant negative correlation with organic matter., Conclusion: Peanut-cotton rotation can mitigate soil nutrient loss, enhance beneficial microorganism diversity, suppress harmful bacterial populations, stabilize ecosystems, and boost crop yield., Competing Interests: Declarations Competing interests The authors declare no competing interests., (© 2024. The Author(s).)

Cyanobacteria, often overlooked in traditional agriculture, are gaining recognition for their roles in enhancing plant growth and soil health through diverse mechanisms. This review examines their multifaceted contributions to agricultural systems, highlighting their proficiency in auxin production, which promotes plant growth and development. Additionally, we examined cyanobacteria's ability to produce siderophores that enhance iron absorption and address micronutrient deficiencies, as well as their capacity for nitrogen fixation, which converts atmospheric nitrogen into a form that plants can utilize, all with the goal of reducing reliance on synthetic fertilizers. A meta-analysis of existing studies indicates significant positive effects of cyanobacteria on crop yield, although variability exists. While some research shows considerable yield increases, other studies report non-significant changes, suggesting benefits may depend on specific conditions and crop types. The overall random-effects model estimate indicates a significant aggregate effect, with a few exceptions, emphasizing the need for further research to optimize the use of cyanobacteria as biofertilizers. Although cyanobacteria-based products are limited in comparison to seaweed-derived alternatives, for instance, ongoing challenges include regulatory issues and production costs. Integrating cultivation with wastewater treatment could enhance competitiveness and viability in the agricultural market., Competing Interests: Declarations Conflict of interest The authors declare that the research was conducted in the absence of any commercial or financial relationship that could be construed as a potential conflict of interest., (© 2024. The Author(s), under exclusive licence to Springer Nature B.V.)