30 results match your criteria Agricultural Systems[Journal]

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Identification of production challenges and benefits using value chain mapping of egg food systems in Nairobi, Kenya.

Agric Syst 2018 Jan;159:1-8

Leverhulme Centre for Integrative Research in Agriculture and Health, London, United Kingdom.

Commercial layer and indigenous chicken farming in Nairobi and associated activities in the egg value chains are a source of livelihood for urban families. A value chain mapping framework was used to describe types of inputs and outputs from chicken farms, challenges faced by producers and their disease control strategies. Commercial layer farms were defined as farms keeping exotic breeds of chicken, whereas indigenous chicken farms kept different cross breeds of indigenous chicken. Read More

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http://dx.doi.org/10.1016/j.agsy.2017.10.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6472295PMC
January 2018

Emergy evaluation for decision-making in complex multifunctional farming systems.

Agric Syst 2019 ;171:1-12

USEPA - United States Environmental Protection Agency, 27 Tarzwell Drive, Narragansett, RI 02882, United States of America.

In a farm, commonly found in the South Portugal, human activities benefit from important fluxes of renewable resources. In this study, traditional economic and emergy evaluations are compared to determine their potential contributions to understanding this complex system and applied to a case study of a farm. This allows us to determine how each method values local natural resources and purchased factors of production and services in an empirical context. Read More

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http://dx.doi.org/10.1016/j.agsy.2018.12.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6452492PMC
January 2019

ASAP: A new global early warning system to detect anomaly hot spots of agricultural production for food security analysis.

Agric Syst 2019 Jan;168:247-257

European Commission, Joint Research Centre, Directorate D - Sustainable Resources, Via E. Fermi 2749, I-21027 Ispra, VA, Italy.

Monitoring crop and rangeland conditions is highly relevant for early warning and response planning in food insecure areas of the world. Satellite remote sensing can obtain relevant and timely information in such areas where ground data are scattered, non-homogenous, or frequently unavailable. Rainfall estimates provide an outlook of the drivers of vegetation growth, whereas time series of satellite-based biophysical indicators at high temporal resolution provide key information about vegetation status in near real-time and over large areas. Read More

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http://dx.doi.org/10.1016/j.agsy.2018.07.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360855PMC
January 2019
1 Read

From extreme weather to impacts: The role of the areas of concern maps in the JRC MARS bulletin.

Agric Syst 2019 Jan;168:213-223

European Commission, Joint Research Centre, Italy.

Each month the JRC issues the MARS Bulletin detailing the agro-meteorological and expert analysis underpinning the assessment of European crops' status and yield forecasts. In this context a resume is provided to give an overview on the geographical distribution of eventual crop damages. The MARS Bulletin provides such information in a set of synthetic maps (Areas of Concern), produced in each Bulletin, depicting extreme weather events and their impact on crops that have occurred in Europe during the analysis period. Read More

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http://dx.doi.org/10.1016/j.agsy.2018.07.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360853PMC
January 2019

Performance of the MARS-crop yield forecasting system for the European Union: Assessing accuracy, in-season, and year-to-year improvements from 1993 to 2015.

Agric Syst 2019 Jan;168:203-212

European Commission, Joint Research Centre (JRC), Ispra 21027, Italy.

19,980 crop yield forecasts have been published for the European Union (EU) Member States (MS) during 1993-2015 using the MARS-Crop Yield Forecasting System (MCYFS). We assess the performance of these forecasts for soft wheat, durum wheat, grain maize, rapeseed, sunflower, potato and sugar beet, and sought to answer three questions. First, how good has the system performed? This was investigated by calculating several accuracy indicators (e. Read More

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http://dx.doi.org/10.1016/j.agsy.2018.06.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360854PMC
January 2019

Using reanalysis in crop monitoring and forecasting systems.

Agric Syst 2019 Jan;168:144-153

European Commission, Joint Research Centre, Italy.

Weather observations are essential for crop monitoring and forecasting but they are not always available and in some cases they have limited spatial representativeness. Thus, reanalyses represent an alternative source of information to be explored. In this study, we assess the feasibility of reanalysis-based crop monitoring and forecasting by using the system developed and maintained by the European Commission- Joint Research Centre, its gridded daily meteorological observations, the biased-corrected reanalysis AgMERRA and the ERA-Interim reanalysis. Read More

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http://dx.doi.org/10.1016/j.agsy.2018.07.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6360535PMC
January 2019

Mapping Nairobi's dairy food system: An essential analysis for policy, industry and research.

Agric Syst 2018 Nov;167:47-60

International Livestock Research Institute, Nairobi, Kenya.

Demand for dairy products in sub-Saharan Africa, is expected to triple by 2050, while limited increase in supply is predicted. This poses significant food security risk to low income households. Understanding how the dairy food system operates is essential to identify mitigation measures to food insecurity impact. Read More

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http://dx.doi.org/10.1016/j.agsy.2018.08.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6358146PMC
November 2018
12 Reads

Can Bangladesh produce enough cereals to meet future demand?

Agric Syst 2018 Jun;163:36-44

Plant Production Systems, Wageningen University, P.O. Box 430, 6700 AK Wageningen, Netherlands.

Bangladesh faces huge challenges in achieving food security due to its high population, diet changes, and limited room for expanding cropland and cropping intensity. The objective of this study is to assess the degree to which Bangladesh can be self-sufficient in terms of domestic maize, rice and wheat production by the years 2030 and 2050 by closing the existing gap (Yg) between yield potential (Yp) and actual farm yield (Ya), accounting for possible changes in cropland area. Yield potential and yield gaps were calculated for the three crops using well-validated crop models and site-specific weather, management and soil data, and upscaled to the whole country. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.11.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5903259PMC

Improving the use of crop models for risk assessment and climate change adaptation.

Agric Syst 2018 Jan;159:296-306

Institute for Climate and Atmospheric Science, School of Earth and Environment, University of Leeds, Leeds LS2 9JT, UK.

Crop models are used for an increasingly broad range of applications, with a commensurate proliferation of methods. Careful framing of research questions and development of targeted and appropriate methods are therefore increasingly important. In conjunction with the other authors in this special issue, we have developed a set of criteria for use of crop models in assessments of impacts, adaptation and risk. Read More

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http://dx.doi.org/10.1016/j.agsy.2017.07.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5738966PMC
January 2018
8 Reads

Climate smart agriculture, farm household typologies and food security: An assessment from Eastern India.

Agric Syst 2018 Jan;159:57-68

International Maize and Wheat Improvement Center (CIMMYT), Sustainable Intensification Program and CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS), NASC Complex, DPS Marg, New Delhi 110012. India.

One of the great challenges in agricultural development and sustainable intensification is the assurance of social equity in food security oriented interventions. Development practitioners, researchers, and policy makers alike could benefit from prior insight into what interventions or environmental shocks might differentially affect farmers' food security status, in order to move towards more informed and equitable development. We examined the food security status and livelihood activities of 269 smallholder farm households (HHs) in Bihar, India. Read More

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http://dx.doi.org/10.1016/j.agsy.2017.09.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5738964PMC
January 2018

Mapping regional risks from climate change for rainfed rice cultivation in India.

Agric Syst 2017 Sep;156:76-84

Department of Biology, University of York, York YO10 5DD, UK.

Global warming is predicted to increase in the future, with detrimental consequences for rainfed crops that are dependent on natural rainfall (i.e. non-irrigated). Read More

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http://dx.doi.org/10.1016/j.agsy.2017.05.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5555444PMC
September 2017
2 Reads

Toward a new generation of agricultural system data, models, and knowledge products: State of agricultural systems science.

Agric Syst 2017 Jul;155:269-288

University of Reading, UK.

We review the current state of agricultural systems science, focusing in particular on the capabilities and limitations of agricultural systems models. We discuss the state of models relative to five different Use Cases spanning field, farm, landscape, regional, and global spatial scales and engaging questions in past, current, and future time periods. Contributions from multiple disciplines have made major advances relevant to a wide range of agricultural system model applications at various spatial and temporal scales. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.09.021DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485672PMC
July 2017
9 Reads

Towards a new generation of agricultural system data, models and knowledge products: Design and improvement.

Agric Syst 2017 Jul;155:255-268

University of Reading, United Kingdom.

This paper presents ideas for a new generation of agricultural system models that could meet the needs of a growing community of end-users exemplified by a set of Use Cases. We envision new data, models and knowledge products that could accelerate the innovation process that is needed to achieve the goal of achieving sustainable local, regional and global food security. We identify desirable features for models, and describe some of the potential advances that we envisage for model components and their integration. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.10.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485644PMC
July 2017
4 Reads

Brief history of agricultural systems modeling.

Agric Syst 2017 Jul;155:240-254

University of Reading, UK.

Agricultural systems science generates knowledge that allows researchers to consider complex problems or take informed agricultural decisions. The rich history of this science exemplifies the diversity of systems and scales over which they operate and have been studied. Modeling, an essential tool in agricultural systems science, has been accomplished by scientists from a wide range of disciplines, who have contributed concepts and tools over more than six decades. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.05.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485640PMC
July 2017
15 Reads

Next generation crop models: A modular approach to model early vegetative and reproductive development of the common bean ().

Agric Syst 2017 Jul;155:225-239

Agricultural & Biological Engineering Dept., University of Florida, FL, USA.

The next generation of gene-based crop models offers the potential of predicting crop vegetative and reproductive development based on genotype and weather data as inputs. Here, we illustrate an approach for developing a dynamic modular gene-based model to simulate changes in main stem node numbers, time to first anthesis, and final node number on the main stem of common bean (). In the modules, these crop characteristics are functions of relevant genes (quantitative trait loci (QTL)), the environment (E), and QTL × E interactions. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.10.010DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485674PMC
July 2017
5 Reads

Modelling the impacts of pests and diseases on agricultural systems.

Agric Syst 2017 Jul;155:213-224

AGIR, Université de Toulouse, INRA, INPT, INP- EI PURPAN, Castanet-Tolosan, France.

The improvement and application of pest and disease models to analyse and predict yield losses including those due to climate change is still a challenge for the scientific community. Applied modelling of crop diseases and pests has mostly targeted the development of support capabilities to schedule scouting or pesticide applications. There is a need for research to both broaden the scope and evaluate the capabilities of pest and disease models. Read More

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http://dx.doi.org/10.1016/j.agsy.2017.01.019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485649PMC
July 2017
1 Read

Towards a new generation of agricultural system data, models and knowledge products: Information and communication technology.

Agric Syst 2017 Jul;155:200-212

Oregon State University, Corvallis, OR, USA.

Agricultural modeling has long suffered from fragmentation in model implementation. Many models are developed, there is much redundancy, models are often poorly coupled, model component re-use is rare, and it is frequently difficult to apply models to generate real solutions for the agricultural sector. To improve this situation, we argue that an open, self-sustained, and committed community is required to co-develop agricultural models and associated data and tools as a common resource. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.09.017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485661PMC
July 2017
17 Reads

Next generation data systems and knowledge products to support agricultural producers and science-based policy decision making.

Agric Syst 2017 Jul;155:191-199

Department of Applied Economics, Oregon State University, United States.

Research on next generation agricultural systems models shows that the most important current limitation is data, both for on-farm decision support and for research investment and policy decision making. One of the greatest data challenges is to obtain reliable data on farm management decision making, both for current conditions and under scenarios of changed bio-physical and socio-economic conditions. This paper presents a framework for the use of farm-level and landscape-scale models and data to provide analysis that could be used in NextGen knowledge products, such as mobile applications or personal computer data analysis and visualization software. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.10.009DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485645PMC
July 2017
4 Reads

Next generation agricultural system data, models and knowledge products: Introduction.

Agric Syst 2017 Jul;155:186-190

NASA/Columbia University, USA.

Agricultural system models have become important tools to provide predictive and assessment capability to a growing array of decision-makers in the private and public sectors. Despite ongoing research and model improvements, many of the agricultural models today are direct descendants of research investments initially made 30-40 years ago, and many of the major advances in data, information and communication technology (ICT) of the past decade have not been fully exploited. The purpose of this Special Issue of Agricultural Systems is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.09.003DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485643PMC
July 2017
4 Reads

Next generation agricultural system models and knowledge products: Synthesis and strategy.

Agric Syst 2017 Jul;155:179-185

NASA/Columbia University, United States.

The purpose of this Special Issue of is to lay the foundation for the next generation of agricultural systems data, models and knowledge products. In the Introduction to this Special Issue, we described a vision for accelerating the rate of agricultural innovation and meeting the growing global need for food and fiber. In this concluding article of the NextGen Special Issue we synthesize insights and formulate a strategy to advance data, models, and knowledge products that are consistent with this vision. Read More

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http://dx.doi.org/10.1016/j.agsy.2017.05.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485654PMC
July 2017
2 Reads

Yield gap analyses to estimate attainable bovine milk yields and evaluate options to increase production in Ethiopia and India.

Agric Syst 2017 Jul;155:43-51

CSIRO Agriculture and Food, 306 Carmody Rd, St Lucia, Qld 4067, Australia.

Livestock provides an important source of income and nourishment for around one billion rural households worldwide. Demand for livestock food products is increasing, especially in developing countries, and there are opportunities to increase production to meet local demand and increase farm incomes. Estimating the scale of livestock yield gaps and better understanding factors limiting current production will help to define the technological and investment needs in each livestock sector. Read More

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http://dx.doi.org/10.1016/j.agsy.2017.04.007DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5485639PMC
July 2017
2 Reads

Losses, inefficiencies and waste in the global food system.

Agric Syst 2017 May;153:190-200

School of Geosciences, University of Edinburgh, Drummond Street, Edinburgh EH8 9XP, UK.

Losses at every stage in the food system influence the extent to which nutritional requirements of a growing global population can be sustainably met. Inefficiencies and losses in agricultural production and consumer behaviour all play a role. This paper aims to understand better the magnitude of different losses and to provide insights into how these influence overall food system efficiency. Read More

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http://dx.doi.org/10.1016/j.agsy.2017.01.014DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5437836PMC
May 2017
21 Reads

Mapping of beef, sheep and goat food systems in Nairobi - A framework for policy making and the identification of structural vulnerabilities and deficiencies.

Agric Syst 2017 Mar;152:1-17

Royal Veterinary College, London, United Kingdom; Leverhulme Centre for Integrated Research in Agriculture and Health, London, United Kingdom.

Nairobi is a large rapidly-growing city whose demand for beef, mutton and goat products is expected to double by 2030. The study aimed to map the Nairobi beef, sheep and goat systems structure and flows to identify deficiencies and vulnerabilities to shocks. Cross-sectional data were collected through focus group discussions and interviews with people operating in Nairobi ruminant livestock and meat markets and in the large processing companies. Read More

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https://linkinghub.elsevier.com/retrieve/pii/S0308521X163014
Publisher Site
http://dx.doi.org/10.1016/j.agsy.2016.12.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5312657PMC
March 2017
4 Reads

Targeting, out-scaling and prioritising climate-smart interventions in agricultural systems: Lessons from applying a generic framework to the livestock sector in sub-Saharan Africa.

Agric Syst 2017 Feb;151:153-162

CSIRO (Commonwealth Scientific and Industrial Research Organisation), Brisbane, Australia.

As a result of population growth, urbanization and climate change, agricultural systems around the world face enormous pressure on the use of resources. There is a pressing need for wide-scale innovation leading to development that improves the livelihoods and food security of the world's population while at the same time addressing climate change adaptation and mitigation. A variety of promising climate-smart interventions have been identified. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.05.017DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5268338PMC
February 2017
6 Reads

Can we be certain about future land use change in Europe? A multi-scenario, integrated-assessment analysis.

Agric Syst 2017 Feb;151:126-135

School of Water, Energy and Environment, Cranfield University, Cranfield, Bedford MK43 0AL, UK.

The global land system is facing unprecedented pressures from growing human populations and climatic change. Understanding the effects these pressures may have is necessary to designing land management strategies that ensure food security, ecosystem service provision and successful climate mitigation and adaptation. However, the number of complex, interacting effects involved makes any complete understanding very difficult to achieve. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.12.001DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5268336PMC
February 2017
1 Read

Towards better metrics and policymaking for seed system development: Insights from Asia's seed industry.

Agric Syst 2016 Sep;147:111-122

International Food Policy Research Institute, 2033 K St NW, Washington, DC 20006, USA.

Since the 1980s, many developing countries have introduced policies to promote seed industry growth and improve the delivery of modern science to farmers, often with a long-term goal of increasing agricultural productivity in smallholder farming systems. Public, private, and civil society actors involved in shaping policy designs have, in turn, developed competing narratives around how best to build an innovative and sustainable seed system, each with varying goals, values, and levels of influence. Efforts to strike a balance between these narratives have often played out in passionate discourses surrounding seed rules and regulations. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.05.015DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4952526PMC
September 2016

Analysing reduced tillage practices within a bio-economic modelling framework.

Agric Syst 2016 Jul;146:91-102

Division of Agricultural and Environmental Sciences, University of Nottingham, Sutton Bonington Campus, College Road, Sutton Bonington, Loughborough LE12 5RD, United Kingdom.

Sustainable intensification of agricultural production systems will require changes in farm practice. Within arable cropping systems, reducing the intensity of tillage practices (e.g. Read More

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http://dx.doi.org/10.1016/j.agsy.2016.04.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4913617PMC
July 2016
4 Reads

Closing system-wide yield gaps to increase food production and mitigate GHGs among mixed crop-livestock smallholders in Sub-Saharan Africa.

Agric Syst 2016 Mar;143:106-113

Commonwealth Scientific and Industrial Research Organization, Queensland Bioscience Precinct, 306 Carmody Road, St Lucia, QLD 4067, Australia.

In this study we estimate yield gaps for mixed crop-livestock smallholder farmers in seven Sub-Saharan African sites covering six countries (Kenya, Tanzania, Uganda, Ethiopia, Senegal and Burkina Faso). We also assess their potential to increase food production and reduce the GHG emission intensity of their products, as a result of closing these yield gaps. We use stochastic frontier analysis to construct separate production frontiers for each site, based on 2012 survey data prepared by the International Livestock Research Institute for the Climate Change, Agriculture and Food Security program. Read More

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http://dx.doi.org/10.1016/j.agsy.2015.12.006DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4767044PMC

Farm systems assessment of bioenergy feedstock production: Integrating bio-economic models and life cycle analysis approaches.

Agric Syst 2012 Jun;109:53-64

Division of Agricultural and Environmental Sciences, School of Biosciences, University of Nottingham, Sutton Bonington Campus, LE12 5RD, United Kingdom.

Climate change and energy security concerns have driven the development of policies that encourage bioenergy production. Meeting EU targets for the consumption of transport fuels from bioenergy by 2020 will require a large increase in the production of bioenergy feedstock. Initially an increase in 'first generation' biofuels was observed, however 'food competition' concerns have generated interest in second generation biofuels (SGBs). Read More

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https://linkinghub.elsevier.com/retrieve/pii/S0308521X120003
Publisher Site
http://dx.doi.org/10.1016/j.agsy.2012.02.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4268688PMC
June 2012
8 Reads

Interactions of CO2, temperature and management practices: simulations with a modified version of CERES-Wheat.

Agric Syst 1995 ;49:135-52

A new growth subroutine was developed for CERES-Wheat, a computer model of wheat (Triticum aestivum) growth and development. The new subroutine simulates canopy photosynthetic response to CO2 concentrations and light levels, and includes the effects of temperature on canopy light-use efficiency. Its performance was compared to the original CERES-Wheat V-2 10 in 30 different cases. Read More

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February 1998
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