Read by QxMD icon Read

" crop model*"

Chuang Zhao, Shilong Piao, Xuhui Wang, Yao Huang, Philippe Ciais, Joshua Elliott, Mengtian Huang, Ivan A Janssens, Tao Li, Xu Lian, Yongwen Liu, Christoph Müller, Shushi Peng, Tao Wang, Zhenzhong Zeng, Josep Peñuelas
Rice is the staple food for more than 50% of the world's population(1-3). Reliable prediction of changes in rice yield is thus central for maintaining global food security. This is an extraordinary challenge. Here, we compare the sensitivity of rice yield to temperature increase derived from field warming experiments and three modelling approaches: statistical models, local crop models and global gridded crop models. Field warming experiments produce a substantial rice yield loss under warming, with an average temperature sensitivity of -5...
December 19, 2016: Nature Plants
Laila A Puntel, John E Sawyer, Daniel W Barker, Ranae Dietzel, Hanna Poffenbarger, Michael J Castellano, Kenneth J Moore, Peter Thorburn, Sotirios V Archontoulis
Improved prediction of optimal N fertilizer rates for corn (Zea mays L.) can reduce N losses and increase profits. We tested the ability of the Agricultural Production Systems sIMulator (APSIM) to simulate corn and soybean (Glycine max L.) yields, the economic optimum N rate (EONR) using a 16-year field-experiment dataset from central Iowa, USA that included two crop sequences (continuous corn and soybean-corn) and five N fertilizer rates (0, 67, 134, 201, and 268 kg N ha(-1)) applied to corn. Our objectives were to: (a) quantify model prediction accuracy before and after calibration, and report calibration steps; (b) compare crop model-based techniques in estimating optimal N rate for corn; and (c) utilize the calibrated model to explain factors causing year to year variability in yield and optimal N...
2016: Frontiers in Plant Science
Nathan Czyzewicz, Elisabeth Stes, Ive De Smet
The first signaling peptide discovered and purified was insulin in 1921. However, it was not until 1991 that the first peptide signal, systemin, was discovered in plants. Since the discovery of systemin, peptides have emerged as a potent and diverse class of signaling molecules in plant systems. Peptides consist of small amino acid sequences, which often act as ligands of receptor kinases. However, not all peptides are created equal, and signaling peptides are grouped into several subgroups dependent on the type of post-translational processing they undergo...
2017: Methods in Molecular Biology
Chuang Zhao, Shilong Piao, Yao Huang, Xuhui Wang, Philippe Ciais, Mengtian Huang, Zhenzhong Zeng, Shushi Peng
Wheat growth is sensitive to temperature, but the effect of future warming on yield is uncertain. Here, focusing on China, we compiled 46 observations of the sensitivity of wheat yield to temperature change (SY,T, yield change per °C) from field warming experiments and 102 SY,T estimates from local process-based and statistical models. The average SY,T from field warming experiments, local process-based models and statistical models is -0.7±7.8(±s.d.)% per °C, -5.7±6.5% per °C and 0.4±4.4% per °C, respectively...
November 17, 2016: Nature Communications
Tilele Stevens, Kaveh Madani
Agriculture is the mainstay of Malawi's economy and maize is the most important crop for food security. As a Least Developed Country (LDC), adverse effects of climate change (CC) on agriculture in Malawi are expected to be significant. We examined the impacts of CC on maize production and food security in Malawi's dominant cereal producing region, Lilongwe District. We used five Global Circulation Models (GCMs) to make future (2011 to 2100) rainfall and temperature projections and simulated maize yields under these projections...
November 8, 2016: Scientific Reports
Alex Wu, Youhong Song, Erik J van Oosterom, Graeme L Hammer
The next advance in field crop productivity will likely need to come from improving crop use efficiency of resources (e.g., light, water, and nitrogen), aspects of which are closely linked with overall crop photosynthetic efficiency. Progress in genetic manipulation of photosynthesis is confounded by uncertainties of consequences at crop level because of difficulties connecting across scales. Crop growth and development simulation models that integrate across biological levels of organization and use a gene-to-phenotype modeling approach may present a way forward...
2016: Frontiers in Plant Science
Tao Li, Jauhar Ali, Manuel Marcaida, Olivyn Angeles, Neil Johann Franje, Jastin Edrian Revilleza, Emmali Manalo, Edilberto Redoña, Jianlong Xu, Zhikang Li
Multi-Environment Trials (MET) are conventionally used to evaluate varietal performance prior to national yield trials, but the accuracy of MET is constrained by the number of test environments. A modeling approach was innovated to evaluate varietal performance in a large number of environments using the rice model ORYZA (v3). Modeled yields representing genotype by environment interactions were used to classify the target population of environments (TPE) and analyze varietal yield and yield stability. Eight Green Super Rice (GSR) and three check varieties were evaluated across 3796 environments and 14 seasons in Southern Asia...
2016: PloS One
Xiuwei Liu, Hongyong Sun, Til Feike, Xiying Zhang, Liwei Shao, Suying Chen
The major wheat production region of China the North China Plain (NCP) is seriously affected by air pollution. In this study, yield of winter wheat (Triticum aestivum L.) was analyzed with respect to the potential impact of air pollution index under conditions of optimal crop management in the NCP from 2001 to 2012. Results showed that air pollution was especially serious at the early phase of winter wheat growth significantly influencing various weather factors. However, no significant correlations were found between final grain yield and the weather factors during the early growth phase...
2016: PloS One
Pierre-Yves Bernard, Marc Benoît, Jean Roger-Estrade, Sylvain Plantureux
The objectives of this comparison of two biophysical models of nitrogen losses were to evaluate first whether results were similar and second whether both were equally practical for use by non-scientist users. Results were obtained with the crop model STICS and the environmental model AGRIFLUX based on nitrogen loss simulations across a small groundwater catchment area (<1 km(2)) located in the Lorraine region in France. Both models simulate the influences of leaching and cropping systems on nitrogen losses in a relevant manner...
December 1, 2016: Journal of Environmental Management
Brett Ford, Weiwei Deng, Jenni Clausen, Sandra Oliver, Scott Boden, Megan Hemming, Ben Trevaskis
An increase in global temperatures will impact future crop yields. In the cereal crops wheat and barley, high temperatures accelerate reproductive development, reducing the number of grains per plant and final grain yield. Despite this relationship between temperature and cereal yield, it is not clear what genes and molecular pathways mediate the developmental response to increased temperatures. The plant circadian clock can respond to changes in temperature and is important for photoperiod-dependent flowering, and so is a potential mechanism controlling temperature responses in cereal crops...
October 2016: Journal of Experimental Botany
Tony Carr, Haishun Yang, Chittaranjan Ray
Water Productivity (WP) of a crop defines the relationship between the economic or physical yield of the crop and its water use. With this concept it is possible to identify disproportionate water use or water-limited yield gaps and thereby support improvements in agricultural water management. However, too often important qualitative and quantitative environmental factors are not part of a WP analysis and therefore neglect the aspect of maintaining a sustainable agricultural system. In this study, we examine both the physical and economic WP in perspective with temporally changing environmental conditions...
2016: PloS One
Fay Newbery, Aiming Qi, Bruce Dl Fitt
Combining climate change, crop growth and crop disease models to predict impacts of climate change on crop diseases can guide planning of climate change adaptation strategies to ensure future food security. This review summarises recent developments in modelling climate change impacts on crop diseases, emphasises some major challenges and highlights recent trends. The use of multi-model ensembles in climate change modelling and crop modelling is contributing towards measures of uncertainty in climate change impact projections but other aspects of uncertainty remain largely unexplored...
August 2016: Current Opinion in Plant Biology
S V Krishna Jagadish, Rajeev N Bahuguna, Maduraimuthu Djanaguiraman, Rico Gamuyao, P V Vara Prasad, Peter Q Craufurd
Flowering is a crucial determinant for plant reproductive success and seed-set. Increasing temperature and elevated carbon-dioxide (e[CO2]) are key climate change factors that could affect plant fitness and flowering related events. Addressing the effect of these environmental factors on flowering events such as time of day of anthesis (TOA) and flowering time (duration from germination till flowering) is critical to understand the adaptation of plants/crops to changing climate and is the major aim of this review...
2016: Frontiers in Plant Science
Emilie J Millet, Claude Welcker, Willem Kruijer, Sandra Negro, Aude Coupel-Ledru, Stéphane D Nicolas, Jacques Laborde, Cyril Bauland, Sebastien Praud, Nicolas Ranc, Thomas Presterl, Roberto Tuberosa, Zoltan Bedo, Xavier Draye, Björn Usadel, Alain Charcosset, Fred Van Eeuwijk, François Tardieu
Assessing the genetic variability of plant performance under heat and drought scenarios can contribute to reduce the negative effects of climate change. We propose here an approach that consisted of (1) clustering time courses of environmental variables simulated by a crop model in current (35 years × 55 sites) and future conditions into six scenarios of temperature and water deficit as experienced by maize (Zea mays L.) plants; (2) performing 29 field experiments in contrasting conditions across Europe with 244 maize hybrids; (3) assigning individual experiments to scenarios based on environmental conditions as measured in each field experiment; frequencies of temperature scenarios in our experiments corresponded to future heat scenarios (+5°C); (4) analyzing the genetic variation of plant performance for each environmental scenario...
October 2016: Plant Physiology
Christian Folberth, Rastislav Skalský, Elena Moltchanova, Juraj Balkovič, Ligia B Azevedo, Michael Obersteiner, Marijn van der Velde
Global gridded crop models (GGCMs) are increasingly used for agro-environmental assessments and estimates of climate change impacts on food production. Recently, the influence of climate data and weather variability on GGCM outcomes has come under detailed scrutiny, unlike the influence of soil data. Here we compare yield variability caused by the soil type selected for GGCM simulations to weather-induced yield variability. Without fertilizer application, soil-type-related yield variability generally outweighs the simulated inter-annual variability in yield due to weather...
June 21, 2016: Nature Communications
Tianyi Zhang, Tao Li, Xiaoguang Yang, Elisabeth Simelton
Climate-induced crop yields model projections are constrained by the accuracy of the phenology simulation in crop models. Here, we use phenology observations from 775 trials with 19 rice cultivars in 5 Asian countries to compare the performance of four rice phenology models (growing-degree-day (GDD), exponential, beta and bilinear models) when applied to warmer climates. For a given cultivar, the difference in growing season temperature (GST) varied between 2.2 and 8.2 °C in different trials, which allowed us to calibrate the models for lower GST and validate under higher GST, with three calibration experiments...
2016: Scientific Reports
H Fraga, I García de Cortázar Atauri, A C Malheiro, J A Santos
Viticulture is a key socioeconomic sector in Europe. Owing to the strong sensitivity of grapevines to atmospheric factors, climate change may represent an important challenge for this sector. The present study analyses viticultural suitability, yield, phenology, and water and nitrogen stress indices in Europe, for present climates (1980-2005) and future (2041-2070) climate change scenarios (RCP4.5 and RCP8.5). The STICS crop model is coupled with climate, soil and terrain databases, also taking into account CO2 physiological effects, and simulations are validated against observational datasets...
June 2, 2016: Global Change Biology
Rose A Graves, Scott M Pearson, Monica G Turner
Rural landscapes face changing climate, shifting development pressure, and loss of agricultural land. Perennial bioenergy crops grown on existing agricultural land may provide an opportunity to conserve rural landscapes while addressing increased demand for biofuels. However, increased bioenergy production and changing land use raise concerns for tradeoffs within the food-energy-environment trilemma. Heterogeneity of climate, soils, and land use complicate assessment of bioenergy potential in complex landscapes, creating challenges to evaluating future tradeoffs...
March 2016: Ecological Applications: a Publication of the Ecological Society of America
Sabine-Karen Lammoglia, Julien Moeys, Enrique Barriuso, Mats Larsbo, Jesús-María Marín-Benito, Eric Justes, Lionel Alletto, Marjorie Ubertosi, Bernard Nicolardot, Nicolas Munier-Jolain, Laure Mamy
The current challenge in sustainable agriculture is to introduce new cropping systems to reduce pesticides use in order to reduce ground and surface water contamination. However, it is difficult to carry out in situ experiments to assess the environmental impacts of pesticide use for all possible combinations of climate, crop, and soils; therefore, in silico tools are necessary. The objective of this work was to assess pesticides leaching in cropping systems coupling the performances of a crop model (STICS) and of a pesticide fate model (MACRO)...
May 18, 2016: Environmental Science and Pollution Research International
Weilong Ding, Lifeng Xu, Yang Wei, Fuli Wu, Defeng Zhu, Yuping Zhang, Nelson Max
How to select and combine good traits of rice to get high-production individuals is one of the key points in developing crop ideotype cultivation technologies. Existing cultivation methods for producing ideal plants, such as field trials and crop modeling, have some limits. In this paper, we propose a method based on a genetic algorithm (GA) and a functional-structural plant model (FSPM) to optimize plant types of virtual rice by dynamically adjusting phenotypical traits. In this algorithm, phenotypical traits such as leaf angles, plant heights, the maximum number of tiller, and the angle of tiller are considered as input parameters of our virtual rice model...
August 21, 2016: Journal of Theoretical Biology
Fetch more papers »
Fetching more papers... Fetching...
Read by QxMD. Sign in or create an account to discover new knowledge that matter to you.
Remove bar
Read by QxMD icon Read

Search Tips

Use Boolean operators: AND/OR

diabetic AND foot
diabetes OR diabetic

Exclude a word using the 'minus' sign

Virchow -triad

Use Parentheses

water AND (cup OR glass)

Add an asterisk (*) at end of a word to include word stems

Neuro* will search for Neurology, Neuroscientist, Neurological, and so on

Use quotes to search for an exact phrase

"primary prevention of cancer"
(heart or cardiac or cardio*) AND arrest -"American Heart Association"