How Could Agricultural Land Systems Contribute to Raise Food Production Under Global Change?

To feed the increasing world population, more food needs to be produced from agricultural land systems. Solutions to produce more food with fewer resources while minimizing adverse environmental and ecological consequences require sustainable agricultural land use practices as supplementary to advanced biotechnology and agronomy. This review paper, from a land system perspective, systematically proposed and analyzed three interactive strategies that could possibly raise future food production under global change. By reviewing the current literatures, we suggest that cropland expansion is less possible amid iferce land competition, and it is likely to do less in increasing food production. Moreover, properly allocating crops in space and time is a practical way to ensure food production. Climate change, dietary shifts, and other socio-economic drivers, which would shape the demand and supply side of food systems, should be taken into consideration during the decision-making on rational land management in respect of sustainable crop choice and allocation. And ifnally, crop-speciifc agricultural intensiifcation would play a bigger role in raising future food production either by increasing the yield per unit area of individual crops or by increasing the number of crops sown on a particular area of land. Yet, only when it is done sustainably is this a much more effective strategy to maximize food production by closing yield and harvest gaps.

Impact of systems modelling on agronomic research and adoption of new practices in smallholder agriculture

An analysis of the impact of simulation modelling in three diverse crop-livestock improvement projects in Agricultural Research for Development（AR4D） reveals benefits across a range of aspects including identification of objectives, design and implementation of experimental programs, effectiveness of participatory research with smallholder farmers, implementation of system change and scaling-out of results.In planning change, farmers must consider complex interactions within both biophysical and socioeconomic aspects of their crop and animal production activities.For this, whole-farm models that include household models of food, workload and financial requirements have the most utility and impact.The analysis also proposes improvements in design and implementation of AR4 D projects to improve the utility of simulation modelling for securing positive agronomic and livestock outcomes and lasting legacies.

Impact of rainfed and irrigated agriculture systems on soil carbon stock under different climate scenarios in the semi-arid region of Brazil

Understanding the dynamics of soil organic carbon(SOC) is of fundamental importance in land use and management, whether in the current researches or in future scenarios of agriculture systems considering climate change. In order to evaluate SOC stock of the three districts(Delmiro Gouveia, Pariconha, and Inhapi districts) in the semi-arid region of Brazil in rainfed and irrigated agriculture systems under different climate scenarios using the Century model, we obtained RCP4.5 and RCP8.5 climate scenarios derived from the Eta Regional Climate Model(Eta-Had GEM2-ES and Eta-MIROC5) from the National Institute for Space Research, and then input the data of bulk density, p H, soil texture, maximum temperature, minimum temperature, and rainfall into the soil and climate files of the Century model. The results of this study showed that the Eta-Had GEM2-ES model was effective in estimating air temperature in the future period. In rainfed agriculture system, SOC stock under the baseline scenario was lower than that under RCP4.5 and RCP8.5 climate scenarios, while in irrigated agriculture system, SOC stock in the almost all climate scenarios(RCP4.5 and RCP8.5) and models(Eta-Had GEM2-ES and Eta-MIROC5) will increase by 2100. The results of this study will help producers in the semi-arid region of Brazil adopt specific agriculture systems aimed at mitigating greenhouse gas emissions.

The Bioprospecting of Microbial-Derived Antimicrobial Peptides for Sustainable Agriculture

Strategies aimed at defining,discovering,and developing alternatives to traditional antibiotics will underlie the development of sustainable agricultural systems.Among such strategies,antimicrobial peptides(AMPs)with broad-spectrum antimicrobial activity and multifaceted mechanisms of action are recognized as ideal alternatives in the post-antibiotic era.In particular,AMPs derived from microbes with active metabolisms that can adapt to a variety of extreme environments have long been sought after.Consequently,this review summarizes information on naturally occurring AMPs,including their biological activity,antimicrobial mechanisms,and the preparation of microbial-derived AMPs;it also outlines their applications and the challenges presented by their use in the agroindustry.By dissecting the research results on microbial-derived AMPs of previous generations,this study contributes valuable knowledge on the exploration and realization of the applications of AMPs in sustainable agriculture.

Quantifying major sources of uncertainty in projecting the impact of climate change on wheat grain yield in dryland environments

Modelling the impact of climate change on cropping systems is crucial to support policy-making for farmers and stakeholders.Nevertheless,there exists inherent uncertainty in such cases.General Circulation Models(GCMs)and future climate change scenarios(different Representative Concentration Pathways(RCPs)in different future time periods)are among the major sources of uncertainty in projecting the impact of climate change on crop grain yield.This study quantified the different sources of uncertainty associated with future climate change impact on wheat grain yield in dryland environments(Shiraz,Hamedan,Sanandaj,Kermanshah and Khorramabad)in eastern and southern Iran.These five representative locations can be categorized into three climate classes:arid cold(Shiraz),semi-arid cold(Hamedan and Sanandaj)and semi-arid cool(Kermanshah and Khorramabad).Accordingly,the downscaled daily outputs of 29 GCMs under two RCPs(RCP4.5 and RCP8.5)in the near future(2030s),middle future(2050s)and far future(2080s)were used as inputs for the Agricultural Production Systems sIMulator(APSIM)-wheat model.Analysis of variance(ANOVA)was employed to quantify the sources of uncertainty in projecting the impact of climate change on wheat grain yield.Years from 1980 to 2009 were regarded as the baseline period.The projection results indicated that wheat grain yield was expected to increase by 12.30%,17.10%,and 17.70%in the near future(2030s),middle future(2050s)and far future(2080s),respectively.The increases differed under different RCPs in different future time periods,ranging from 11.70%(under RCP4.5 in the 2030s)to 20.20%(under RCP8.5 in the 2080s)by averaging all GCMs and locations,implying that future wheat grain yield depended largely upon the rising CO2 concentrations.ANOVA results revealed that more than 97.22% of the variance in future wheat grain yield was explained by locations,followed by scenarios,GCMs,and their interactions.Specifically,at the semi-arid climate locations(Hamedan,Sanandaj,Kermanshah and Khorramabad),most of the variations arose from the scenarios(77.25%),while at the arid climate location(Shiraz),GCMs(54.00%)accounted for the greatest variation.Overall,the ensemble use of a wide range of GCMs should be given priority to narrow the uncertainty when projecting wheat grain yield under changing climate conditions,particularly in dryland environments characterized by large fluctuations in rainfall and temperature.Moreover,the current research suggested some GCMs(e.g.,the IPSL-CM5B-LR,CCSM4,and BNU-ESM)that made moderate effects in projecting the impact of climate change on wheat grain yield to be used to project future climate conditions in similar environments worldwide.

Traditional agroecological knowledge and practices:The drivers and opportunities for adaptation actions in the northern region of Ghana

Agroecological practices are promoted as a more proactive approach than conventional agriculture to achieving a collective global response to climate change and variability while building robust and resilient agricultural systems to meet food needs and protect the integrity of ecosystems.There is relatively limited evidence on the key traditional agroecological knowledge and practices adopted by smallholder farmers,the factors that influence smallholder farmers’decision to adopt these practices,and the opportunities it presents for building resilient agricultural systems.Using a multi-scale mixed method approach,we conducted key informant interviews(n=12),focus group discussions(n=5),and questionnaire surveys(N=220)to explore the traditional agroecological knowledge and practices,the influencing factors,and the opportunities smallholder farmers presented for achieving resilient agricultural systems.Our findings suggest that smallholder farmers employ a suite of traditional agroecological knowledge and practices to enhance food security,combat climate change,and build resilient agricultural systems.The most important traditional agroecological knowledge and practices in the study area comprise cultivating leguminous crops,mixed crop-livestock systems,and crop rotation,with Relative Importance Index(RII)values of 0.710,0.708,and 0.695,respectively.It is reported that the choice of these practices by smallholder farmers is influenced by their own farming experience,access to market,access to local resources,information,and expertise,and the perceived risk of climate change.Moreover,the results further show that improving household food security and nutrition,improving soil quality,control of pest and disease infestation,and support from NonGovernmental Organizations(NGOs)and local authorities are opportunities for smallholder farmers in adopting traditional agroecological knowledge and practices for achieving resilient agricultural systems.The findings call into question the need for stakeholders and policy-makers at all levels to develop capacity and increase the awareness of traditional agroecological knowledge and practices as mechanisms to ensure resilient agricultural systems for sustainable food security.

Trends of Extreme Temperature and Rainfall Indices for Arid and Semi-Arid Lands of South Eastern Kenya

Extreme climate events have profound impacts on economies and livelihoods of many regions of the world. In Kenya, the extreme climate events often have strong impacts on agriculture production systems in the Arid and Semi-Arid Lands (ASALs). A small change in the mean climate condition can cause large changes in these production systems. There is a paucity of information on trends in climate and climate extremes in the country. However, a joint World Meteorological Commission for Climatology/World Climate Research Programme (WCPRP) project on climate Variability and Predictability (WMO CCl/CLIVAR) Expert Team (ET) on Climate Change Detection, Monitoring and Indices has defined 27 core climate indices mainly focusing on extreme events which can be derived through the use of RClimDex Software. In this study, therefore, the RClimDex software has been used to derive climate extreme indices for five stations in the ASALs of South-Eastern Kenya based on climate data for the period 1961 to 2009. The objective was to examine trends in these extremes to aid agricultural planning and practice. These indices have shown decreasing trends in annual rainfall, rainfall intensity and consecutive wet days but increasing trends in consecutive dry days. Steady warming patterns were evident in both the maximum and minimum temperature indices. This paper concludes that indeed significant changes in climate extremes are apparent in the ASALs of the country and recommends a re-thinking of planning and practice of rain-fed agriculture in the ASALs of South-Eastern Kenya.

The Risk of <i>Fusarium</i>and Their Mycotoxins in the Food Chain

Fusarium sp. and mycotoxins of these species pose a major risk to consumer health, agriculture and the food industry. This paper is a worldwide bibliographic study on impact of Fusarium and mycotoxins on the food chain. The factors influencing the development of fungi Fusarium sp., the formation of mycotoxins and their microbiological risk on the food chain must be considered as a whole. For cereals and oilseeds before and after harvest, fungal infections and mycotoxin contamination present serious problems worldwide. This paper is an overview of the factors that include the microbiological risk and impact of Fusarium in the food chain mentioned in national and international studies. The methods and results obtained in this direction internationally are mentioned, such as: infrared spectroscopy, Raman spectrometry and hyperspectral imaging. Also, in review are presented solutions to reduce this impact on the food chain.

中国重要农业文化遗产的空间分布特征及其差异性管理策略

Climate change and rapid urbanization pose significant challenges to the conservation and management of agricultural heritage systems,including decline in agricultural land,loss of labor,and ecosystem degradation.Although existing studies have proposed general strategies with theoretical guidance and specific strategies for particular systems to promote the conservation of agricultural heritage systems,there remains a large knowledge gap in effective and differentiated management strategies at the regional level.This is especially so in China because of the clear regional differences in the natural and socioeconomic conditions of the widely distributed China Nationally Important Agricultural Heritage Systems(China-NIAHS).In this study,we integrated multi-source data and spatial analysis to reveal the distribution characteristics of existing China-NIAHS and proposed differentiated management strategies.Results show that there are four clustering distribution zones of China-NIAHS,i.e.,the northwest clustering zone west of the Heihe-Tengchong Line(ZoneⅠ),the clustering belt with‘Northeast-Hebei-Shandong'as core(ZoneⅡ),the Yangtze River Delta clustering zone(ZoneⅢ),and the Hunan-Chongqing-Yunnan-Guizhou clustering zone(ZoneⅣ).Different management strategies are proposed for the China-NIAHS in each clustering zone.Specifically,ZoneⅠshould focus on maintaining their ecological functions and services,while ZoneⅡshould aim for livelihood supply,sustainable resource use,and ecological protection.For ZoneⅢ,rapid urbanization could become a positive driving force for China-NIAHS conservation through sustainable tourism and reasonable urban zoning.ZoneⅣshould emphasize the mutual support between characteristic product development and the brand effect of the China-NIAHS.These findings will help establish regional and targeted management strategies for China-NIAHS and provide a reference for the conservation of agricultural heritage systems in other countries.

Foundations of Programmable Process Structures for the unified modeling and simulation of agricultural and aquacultural systems

This research paper defines the theoretical foundations and computational implementation of a non-conventional modeling and simulation methodology,inspired by the needs of problem solving for biological,agricultural,aquacultural and environmental systems.The challenging practical problem is to develop a framework for automatic generation of causally right and balance-based,unified models that can also be applied for the effective coupling amongst the various(sophisticated field-specific,sensor data processing-based,upper level optimization-driven,etc.)models.The scientific problem addressed in this innovation is to develop Programmable Process Structures(PPS)by combining functional basis of systems theory,structural approach of net theory and computational principles of agent based modeling.PPS offers a novel framework for the automatic generation of easily extensible and connectible,unified models for the underlying complex systems.PPS models can be generated from one state and one transition meta-prototypes and from the transition oriented description of process structure.The models consist of unified state and transition elements.The local program containing prototype elements,derived also from the meta-prototypes,are responsible for the case-specific calculations.The integrity and consistency of PPS architecture are based on the meta-prototypes,prepared to distinguish between the conservation-laws-based measures and the signals.The simulation is based on data flows amongst the state and transition elements,as well as on the unification based data transfer between these elements and their calculating prototypes.This architecture and its AI language-based(Prolog)implementation support the integration of various field-and task-specific models,conveniently.The better understanding is helped by a simple example.The capabilities of the recently consolidated general methodology are discussed on the basis of some preliminary applications,focusing on the recently studied agricultural and aquacultural cases.

Study on the adaptability of traditional architecture in agricultural heritage sites after tourism intervention—a case study of Huzhou Digang Food Street in China

Traditional architecture in agricultural heritage sites(AHSs)embodies the livelihood of local communities and residents,which is an important part of the AHS.However,with the intervention of tourism,some of the traditional architecture in AHSs has gradually transformed into simple use for tourism,without refecting the cultural connotations of agricultural heritage systems,as well as the farming wisdom of the AHS.This paper takes Digang Food Street in Huzhou,China as an example,which is in the core protection area of the Huzhou mulberry-dyke and fsh-pond system,combining comparative analysis and geographical system analysis to explore the adaptive transformation in decoration,structure,spatial layout and functional form of buildings after the development of the tourism industry.The dynamic relationship among traditional architecture,sustainable development of tourism and conservation of agriculture heritage is also analysed,expecting to provide some experience and reference for the conservation of other AHSs.

An improved method that incorporates the estimated runoff for peak discharge prediction on the Chinese Loess Plateau

An accurate prediction of peak discharge in watersheds is critical not only for water resource manage-ment,but also for understanding the complex relationships of hydrological processes.In this study,a modified peak discharge formula based on the Chemicals,Runoff,and Erosion from Agricultural Man-agement Systems(CREAMS)model was developed by introducing rainfall intensity and soil moisture factors.The reliability of the proposed method was tested with data from 1464 storm events in 41 watersheds and was applied to 256 storm events in five remaining typical watersheds using the opti-mized parameters.The results indicate that the proposed method is highly accurate in terms of model efficiency,as determined by Nash-Sutcliffe efficiencies(NSEs)of 88.60%,74.04%,and 90.12%during the calibration,validation,and application cases,respectively.Furthermore,it performed better than the original and modified CREAMS methods.Subsequently,using the parameters derived from the initial 41 watersheds and the runoff estimated using the modified Soil Conservation Service curve number(SCS-CN)method,the proposed method was used to predict the peak discharge from the last five typical watersheds.Large NSE(63.88-80.83%)and low root mean square error(RMSE)values(0.31-35.93 m^(3)s^(-1))were obtained for the five watersheds.Overall,the proposed peak discharge model,combined with the modified SCS-CN method,may accurately predict event-based peak discharge and runoff for general applications under various hydrological and geomorphic conditions in the Loess Plateau region.

Magnitude,direction,and drivers of rhizosphere effect on soil nitrogen and phosphorus in global agroecosystem

The rhizosphere is the most active soil area for material transformation and energy flow of soil,root,and microorganism,which plays an important role in soil biochemical cycling.Although the rhizospheric nitrogen(N)and phosphorous(P)were easily disturbed in the agroecosystem,the effects of rhizosphere on the dynamics of soil N and P cycling have not yet been systematically quantified globally.We summarized the magnitude,direction,and driving forces of rhizosphere effects on agroecosystem's N and P dynamics by 1063 observations and 15 variables from 122 literature.Rhizosphere effects increased available N(AN,9%),available P(AP,11%),and total P(TP,5%),and decreased nitrate N(NO_(3)-N,18%)and ammonia N(NH_(4)-N,16%).The effect of rhizosphere on total N(TN)was not significant.These effects improved AN in tropical(12%)and subtropical(14%)regions.The effect of rhizosphere on TP was greater under subtropical conditions than in other climates.The most substantial effects of the rhizosphere on TP and AP were observed under humid conditions.Rhizosphere effects increased AN and AP in vegetables more than in other crop systems.Application of N>30o kg ha^(-1) had the most significant and positive rhizosphere effects on TN and AN.P application of 100-150 kg ha^(-1) had the greatest rhizosphere effects on TP and AP.These effects also improved the microbial(biomass N and P)and enzymatic aspects(urease,acid phosphatase,and alkaline phosphatase)of soil P and N cycling.Structural equation modeling suggested that aridity indices,fertilizer application rate,soil pH,microbial biomass,and soil enzymes strongly influence the magnitude and direction of the rhizosphere's effect on the P and N cycles.Overall,these findings are critical for improving soil nutrient utilization efficiency and modeling nutrient cycling in the rhizosphereforagricultural systems.

Extracts from cotton over the whole growing season induce Orobanche cumana(sunflower broomrape) germination with significant cultivar interactions

Five cotton cultivars and their parents were tested for induction of germination of Orobanche cumana Wallr.(sunflower broomrape) seeds in pot and field experiments. Germination rates induced by cotton root extracts were the highest followed by stem extracts then leaf extracts. Cotton seedlings at the six-leaf stage induced higher germination than seedling at the two-and four-leaf stage, in all five cotton cultivars and their parents. In the field, the highest concentration of cotton root extracts gave the highest germination rate of O. cumana, and the lowest concentration of cotton root extracts gave the lowest germination rate. Methanol extracts of cotton rhizosphere soil gave the highest germination of O. cumana. In general,the root, stem and leaf extracts were more active at the sixleaf stage than other seedling stages. In conclusion,extracts of cotton rhizosphere soil and tissues have high activity in the seedling stage. Extracts of cotton across the whole growing season were able to induce O. cumana germination but displayed significant cultivar interactions.

Greenhouse gas emissions during the COVID-19 pandemic from agriculture in China

To study the impact of the COVID-19 pandemic on agricultural carbon emissions in China,the greenhouse gas emissions generated by crop and livestock production,and agricultural material and energy inputs in China from 2019 to 2021 were systematically calculated.It was found that from 2019 to 2021,Net greenhouse gas emissions(NGHGE)from agriculture in China had an increasing trend.Methane emissions ranked first in NGHGE,with an annual proportion exceeding 65%and an increasing annual trend.CH_(4)emissions were primarily influenced by enteric fermentation and rice production.Nitrous oxide emissions accounted for around 22%of annual NGHGE and decreased from 2019 to 2021.The main sources of N_(2)O emissions were the use of nitrogen fertilizers and manure management.Carbon dioxide emissions accounted for about 18%annually,with diesel and agricultural electricity use contributing to over 60%of CO_(2)emissions.Soil carbon sequestration represented about a 6.1%lowering of NGHGE.The combined proportion of CH4 emissions from enteric fermentation and rice production accounted for over 50%of total GHG emissions.The changes in NGHGE were mainly caused by disturbance of the livestock industry during the pandemic.