scispace - formally typeset
Search or ask a question
Journal ArticleDOI

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

TL;DR: It is concluded that multiple platforms and multiple models are needed for model applications for different purposes, and the Use Cases provide a useful framework for considering capabilities and limitations of existing models and data.
About: This article is published in Agricultural Systems.The article was published on 2017-07-01 and is currently open access. It has received 251 citations till now. The article focuses on the topics: Systems science & Information system.
Citations
More filters
Journal ArticleDOI
TL;DR: The history of agricultural systems modeling is summarized and lessons learned are identified that can help guide the design and development of next generation of agricultural system tools and methods.

421 citations


Cites background from "Toward a new generation of agricult..."

  • ...…crop, livestock, and economic models have been combined to study farming systems aswell as to analyze national and global impacts of climate change, policies, or alternative technologies, as shown in the companion paper on the state of agricultural system science (Jones et al., 2017–in this issue)....

    [...]

Book ChapterDOI
01 Jan 2000
TL;DR: The feedback mechanism involved in all principles for artificial learning refers back to the notion of the control-circuit, which serves as a basis for the analysis and the design of feedback-control systems.
Abstract: The feedback mechanism involved in all principles for artificial learning refers back to the notion of the control-circuit. This very common concept serves as a basis for the analysis and the design of feedback-control systems.

329 citations

Journal ArticleDOI
TL;DR: This paper provides an overview of the eight main global and regional scale agricultural monitoring systems currently in operation and compares them based on the input data and models used, the outputs produced and other characteristics such as the role of the analyst, their interaction with other systems and the geographical scale at which they operate.

180 citations

Journal ArticleDOI
TL;DR: The extent of digital twin adoption in agriculture is examined, light is shed on the concept and the benefits it brings, and an application-based roadmap for a more extended adoption is proposed.

153 citations

References
More filters
Book
Luc Anselin1
31 Aug 1988
TL;DR: In this article, a typology of Spatial Econometric Models is presented, and the maximum likelihood approach to estimate and test Spatial Process Models is proposed, as well as alternative approaches to Inference in Spatial process models.
Abstract: 1: Introduction.- 2: The Scope of Spatial Econometrics.- 3: The Formal Expression of Spatial Effects.- 4: A Typology of Spatial Econometric Models.- 5: Spatial Stochastic Processes: Terminology and General Properties.- 6: The Maximum Likelihood Approach to Spatial Process Models.- 7: Alternative Approaches to Inference in Spatial Process Models.- 8: Spatial Dependence in Regression Error Terms.- 9: Spatial Heterogeneity.- 10: Models in Space and Time.- 11: Problem Areas in Estimation and Testing for Spatial Process Models.- 12: Operational Issues and Empirical Applications.- 13: Model Validation and Specification Tests in Spatial Econometric Models.- 14: Model Selection in Spatial Econometric Models.- 15: Conclusions.- References.

8,282 citations


"Toward a new generation of agricult..." refers background in this paper

  • ...Spatial econometrics advanced to include rates of development and specialization of production (Anselin, 1988)....

    [...]

Journal ArticleDOI
TL;DR: Linear regression equations have been obtained to directly calculate the nutrient requirements of dairy cattle (TDN, DE, ME, NEL,CP, Ca, P, Vitamin A and Vitamin D) on different physiological stages: maintenance, pregnancy and milk production based on NRC nutrient requirements tables.
Abstract: Linear regression equations have been obtained to directly calculatenutrient requirements of dairy cattle (TDN, DE, ME, NEL,CP, Ca, P, Vitamin A and Vitamin D) on differentphysiological stages: maintenance, pregnancy and milkproduction based on NRC nutrient requirements tables. TheR-square was calculated for each equation to establish thedegree of adjustment.

6,663 citations

Journal ArticleDOI
TL;DR: A review of the intergovernmental panel on climate change report on global warming and the greenhouse effect can be found in this paper, where the authors present chemistry of greenhouse gases and mathematical modelling of the climate system.
Abstract: Book review of the intergovernmental panel on climate change report on global warming and the greenhouse effect. Covers the scientific basis for knowledge of the future climate. Presents chemistry of greenhouse gases and mathematical modelling of the climate system. The book is primarily for government policy makers.

3,456 citations

Journal ArticleDOI
TL;DR: The benefits of the new, re-designed DSSAT-CSM will provide considerable opportunities to its developers and others in the scientific community for greater cooperation in interdisciplinary research and in the application of knowledge to solve problems at field, farm, and higher levels.

3,339 citations


"Toward a new generation of agricult..." refers background or methods in this paper

  • ...A number of other cropping and grassland systemmodels have similar components and capabilities (e.g., APSIM, Keating et al., 2003a, 2003b and Holzworth et al., 2014; CROPSYST, Stöckle et al., 2003, 2014; EPIC, Williams et al., 1989; STICS, Brisson et al., 2003 and Bergez et al., 2014; SALUS, Basso and Ritchie, 2015 and Dzotsi et al., 2013), although most models do not simulate impacts of pests and diseases unless coupled externally with time-series input data or pest models like in DSSAT CSM (Boote et al., 1983; Batchelor et al., 1993)....

    [...]

  • ...Dzotsi et al. (2013) used a similar approach, showing that reduced maize, peanut, and cotton models parameterized from the DSSAT CSM model accurately reproduced DSSAT results across time and space....

    [...]

  • ...2 shows a schematic of the components in theCropping System Model (CSM) that incorporates the CERES (e.g., see Basso et al., 2016), CROPGRO, and other models in DSSAT (Jones et al., 2003; Boote et al., 2010; Hoogenboom et al., 2015)....

    [...]

  • ..., 2016), CROPGRO, and other models in DSSAT (Jones et al., 2003; Boote et al., 2010; Hoogenboom et al., 2015)....

    [...]

  • ...Examples of these are DSSAT (Jones, 1993), APSIM (Holsworth et al., 2014), Century (Parton et al., 1993), SAVANNA (Coughenhour, 1992), The Hurley Pasture Model (Thornley, 1997), PHYGROW (Stuth et al., 2003)....

    [...]

Journal ArticleDOI
29 Jul 2011-Science
TL;DR: It was found that in the cropping regions and growing seasons of most countries, with the important exception of the United States, temperature trends from 1980 to 2008 exceeded one standard deviation of historic year-to-year variability.
Abstract: Efforts to anticipate how climate change will affect future food availability can benefit from understanding the impacts of changes to date. We found that in the cropping regions and growing seasons of most countries, with the important exception of the United States, temperature trends from 1980 to 2008 exceeded one standard deviation of historic year-to-year variability. Models that link yields of the four largest commodity crops to weather indicate that global maize and wheat production declined by 3.8 and 5.5%, respectively, relative to a counterfactual without climate trends. For soybeans and rice, winners and losers largely balanced out. Climate trends were large enough in some countries to offset a significant portion of the increases in average yields that arose from technology, carbon dioxide fertilization, and other factors.

3,231 citations


"Toward a new generation of agricult..." refers background in this paper

  • ...…yields in response to some combination of weather conditions, nutrient levels, irrigation amounts, etc. (e.g., Schlenker and Lobell, 2010; Lobell et al., 2011), they do not predict responses to nonlinearities and threshold effects outside the range of conditions in data used to develop…...

    [...]

  • ...(e.g., Schlenker and Lobell, 2010; Lobell et al., 2011), they do not predict responses to nonlinearities and threshold effects outside the range of conditions in data used to develop them....

    [...]

Related Papers (5)