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.

Building an interoperable space for smart agriculture

The digital transformation in agriculture introduces new challenges in terms of data,knowledge and technology adoption due to critical interoperability issues,and also challenges regarding the identification of the most suitable data sources to be exploited and the information models that must be used.DEMETER(Building an Interoperable,Data-Driven,Innovative and Sustainable European Agri-Food Sector)addresses these challenges by providing an overarching solution that integrates various heterogeneous hardware and software resources(e.g.,devices,networks,platforms)and enables the seamless sharing of data and knowledge throughout the agri-food chain.This paper introduces the main concepts of DEMETER and its reference architecture to address the data sharing and interoperability needs of farmers,which is validated via two rounds of 20 large-scale pilots along the DEMETER lifecycle.This paper elaborates on the two pilots carried out in region of Murcia in Spain,which target the arable crops sector and demonstrate the benefits of the deployed DEMETER reference architecture.

Modeling Climate Change Impacts on the US Agricultural Exports

Climate change is expected to have substantial effects on agricultural productivity worldwide. However, these impacts will differ across commodities, locations and time periods. As a result, landowners will see changes in relative returns that are likely to induce modifications in production practices and land allocation. In addition, regional variations in impacts can alter relative competitiveness across countries and lead to adjustments in international trade patterns. Thus in climate change impact studies it is likely useful to account for worldwide productivity effects. In this study, we investigate the implications of considering rest of world climate impacts on projections of the US agricultural exports. We chose to focus on the US because it is one of the largest agricultural exporters. To conduct our analyses, we consider four alternative climate scenarios, both with and without rest of world climate change impacts. Our results show that considering/ignoring rest of world climate impacts causes significant changes in the US production and exports projections. Thus we feel climate change impact studies should account not only for climate impacts in the country of focus but also on productivity in the rest of the world in order to capture effects on commodity markets and trade potential.

Irrigation Water Demand Model as a Comparative Tool for Assessing Effects of Land Use Changes for Agricultural Crops in Fraser Valley, Canada

Available water for human needs and agriculture is a growing global concern. Agriculture uses approximately 70% of global freshwater, mainly for irrigation. The Lower Fraser Valley (LFV), British Columbia, is one of the most productive agricultural regions in Canada, supporting livestock production and a wide variety of crops. Water scarcity is a growing concern that threatens the long-term productivity, sustainability, and economic viability of the LFV’s agriculture. We used the BC Agriculture Water Demand Model as a tool to determine how crop choice, irrigation system, and land-use changes can affect predicted water requirements under these different conditions, which can aid stakeholders to formulate better management decisions. We conducted a comparative assessment of the irrigation water demand of seven major commercial crops, by distinct soil management groups, at nineteen representative sites, that use both sprinkler vs drip irrigation. Drip irrigation was consistently more water-efficient than sprinkler irrigation for all crops. Of the major commercial crops assessed, raspberries were the most efficient in irrigation water demand, while forage and pasture had the highest calculated irrigation water demand. Significant reductions in total irrigation water demand (up to 57%) can be made by switching irrigation systems and/or crops. This assessment can aid LFV growers in their land-use choices and could contribute to the selection of water management decisions and agricultural policies.

Finding Food Security through Changing the Agricultural Model to Sustain Insect Biodiversity

Worldwide biodiversity is being threatened by human activities to a greater level wherein the natural ecosystems are reaching the verge of collapsing. We are faced with four major interrelated challenges namely a changing climate, biodiversity loss, human population growth and food production for this growing population. Agricultural intensification contributes significantly to biodiversity loss. The agricultural model for our current food production systems is mainly based on the Green Revolution, which promoted the cultivation of crops in extensive monoculture fields and intensified external inputs of agrochemicals. This model resulted in biodiversity loss, particularly in insect populations. A model based on ecological intensification as an alternative to agricultural intensification with minimized use of agro-inputs may slow the rate of biodiversity loss resulting in more sustainable agricultural ecosystems.

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.

A Study on the Countermeasures of Modern Agricultural Development from a Perspective of E-commerce——A Case of Suzhou,China

Based on the fact that e-commerce promotes the development of modern agriculture,the paper summarizes the present situation of agri-cultural e-commerce through related materials.Taking Suzhou city as an example,the paper analyzes the features of modern agriculture.And themodern agriculture is characterized with apparent industrialization and scaled requirements,the branded and particular agriculture has more advan-tages,leisure agriculture is the very special one.In order to upgrade the degree of agricultural industrialization of Suzhou,promote the communica-tion of agricultural information and sales of products and lower the risks of agricultural production,the e-commerce countermeasures of modern agri-culture have been put forward.Firstly,strengthen the network construction of agricultural information.Secondly,carry out the agricultural e-com-merce business by B2B model.Thirdly,construct the e-commerce platform of leisure agriculture.Fourthly,construct the e-commerce platform ofmodern agriculture.Fifthly,perfect the logistics distribution network of agricultural products of Suzhou.The last point is to accelerate the e-com-merce training of farmers and the introduction of talents.

Comments on the article of “Agriculture Green Development:a model for China and the world”

The coming century will be one of grand global challenges.We will be facing global warming,a growing world population and growing economies.To meet the needs of all world citizens in a sustainable way will not be easy.One of the challenges will be to feed the growing world population,while limiting global warming.Food and water security are at risk,and we will need to invest in innovative and clean technologies to ensure that also in the future there will be enough food to feed the word.This all is reflected in the UN Sustainable Development Goals.

Historical Transformation of China＇s Agriculture＂ Productivity Changes and Other Key Features

According to an analysis of sampled data from the National Bureau of Statistics for 70,000 peasant households, agricultural labor productivity has been increasing at a faster rate than land productivity since 2003. Labor productivity has, in fact, experienced long-term stagnation, The data also reveals the heterogenization of small farmers, farm machinery replacing manual labor as an agricultural input, the expansion of the scale of land management, the development of the rural land leasing market and the diversification of the agricultural management entities. Review of the historical transformation of agriculture helps to recognize the declining importance of agricultural land, the direction of agricultural technological changes, the path and the disposition of the changes to the agricultural system, and the adjustment of China＇s rural policies.

Agricultural Risk Modeling Challenges in China:Probabilistic Modeling of Rice Losses in Hunan Province

This article summarizes a joint research projec undertaken under the Risk Management Solutions, Inc(RMS) banner to investigate some of the possible approaches for agricultural risk modeling in China. Two modeling approaches were investigated—the simulated weather crop index and the burn yield analysis approach. The study was limited to Hunan Province and a single crop—rice. Both modeling approaches were dealt with probabilistically and were able to produce probabilistic risk metrics. Illustrative model outputs are also presented. The article discusses the robustness of the modeling approaches and their dependence on the availability, access to, and quality of weather and yield data. We offer our perspective on the requirements for models and platforms for agricultural risk quantification in China in order to respond to the needs of all stakeholders in agricultural risk transfer.

Agricultural Load Modeling Based on Crop Evapotranspiration and Light Integration for Economic Operation of Greenhouse Power Systems

The threat of environmental degradation attracts great attention to clean energy production and transportation.However,the limited scope of energy consumption causes the large-scale of clean energy sources to be abandoned in Sichuan province.In the meantime,the development of modern greenhouse cultivation has transformed the agriculture industry to develop a brand-new type of electrical load in the grid.Consequently,the agricultural load can be used to consume the clean energy while facilitating plant growth.In this paper,an innovative agricultural load model is proposed based on crop evapotranspiration and daily light integration.Furthermore,the proposed agricultural load model is also applied to investigate the electricity consumption of five types of crop planting.The results illustrate that the power consumption is primarily driven by an artificial lighting compensation system.

Operating pesticide use reduction within the boundary of food security in peri-urban settings

Pesticide use in peri-urban areas afects the urban enviroment and public health,and reducing the use may present food security isues for urban dwellers.In this study,we explore how a muiallyadopted goal of a 20%reduetion in pesticide use could be achieved,along with local food security and environmental implica-tions,for Shanghai located in the densely populated East China.A regional Shanghai Agricultural Sector Model inorporating district-and technology-varying crop budgets,was developed to simulate the efects of pesticide reduction policy.Here we find that achieving the reduction goal had the largest implications in districts with high pesticide use totals and intensities,potentially reducing pesticide non point source pollution in the Yangtze River Estuary and Dianshan Lake;the production levels of rice and leafy vegetables would be most afected;and adopting machinery that allows more precise pesticide application modulates these results.Moreover,imposing the requlrements at the district-level caused more severe local food security concerns,and less environmental benefits.Furthermore,a closed Shanghai's agricultural economy would subtantally enlarge the regional het-erogeneity in the above-mentioaned outcomes.Exploring the ffects of a quantity control policy on current-use pesticides at diferent aggregation levels has important implications for regulating the use of agrochemicals.