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A Functional Analysis of Pedotransfer Functions Developed for Sri Lankan soils: Applicability for Process-Based Crop Models

M.H.J.P. Gunarathna, Kazuhito Sakai, M.K.N. Kumari, Manjula Ranagalage
2020 Agronomy  
Initially, we confirmed the importance of PWP (LL15) and FC (DUL) by assessing the sensitivity of the soil input parameters on the growth and yield of rice under rainfed conditions.  ...  We simulated the growth and yield of rice and the four selected outputs related to the APSIM soil module using the measured and estimated values of FC and PWP.  ...  Hence, this study aims to evaluate the sensitivity of soil parameters to the growth and yield of rice using the APSIM-Oryza model in APSIM 7.10. Gunarathna et al.  ... 
doi:10.3390/agronomy10020285 fatcat:jsiusvxegffc5mdqirrh5bez3m

Global Sensitivity Analysis for CERES-Rice Model under Different Cultivars and Specific-Stage Variations of Climate Parameters

Haixiao Ge, Fei Ma, Zhenwang Li, Changwen Du
2021 Agronomy  
In this study, 30 indica hybrid rice cultivars were simulated in the CERES-Rice model; then the Sobol' method was used to perform a global SA on 16 investigated parameters for three model outputs (anthesis  ...  Global sensitivity analysis (SA) has become an efficient way to identify the most influential parameters on model results.  ...  A sensitivity analysis (SA) is a prerequisite process in model parameter estimation.  ... 
doi:10.3390/agronomy11122446 fatcat:fdu5xwvhmzg7hoeozbvyi26uym

A taxonomy-based approach to shed light on the babel of mathematical models for rice simulation

Roberto Confalonieri, Simone Bregaglio, Myriam Adam, Françoise Ruget, Tao Li, Toshihiro Hasegawa, Xinyou Yin, Yan Zhu, Kenneth Boote, Samuel Buis, Tamon Fumoto, Donald Gaydon (+18 others)
2016 Environmental Modelling & Software  
Principal component analysis was performed on model outputs at four sites.  ...  Results indicated that (i) differences in structure often resulted in similar predictions and (ii) similar structures can lead to large differences in model outputs.  ...  TH's participation was supported by MAFF and the Global Environment Research (S-10-2) of MOE, Japan.  ... 
doi:10.1016/j.envsoft.2016.09.007 fatcat:2qi4lbyfbnepvbe4vtb6nvdv2m

Rice Blast (Magnaporthe oryzae) Occurrence Prediction and the Key Factor Sensitivity Analysis by Machine Learning

Li-Wei Liu, Sheng-Hsin Hsieh, Su-Ju Lin, Yu-Min Wang, Wen-Shin Lin
2021 Agronomy  
The temperature phase lag in air and soil may cause a lower dew point and suitable for rice blast pathogens growth.  ...  The SA was conducted in the PNN model resulting in the main effect period is 10 days before the rice blast happened.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/agronomy11040771 fatcat:ipposhrjrzhulazfawf4g3jjym

Cost-Benefit Analysis for Single and Double Rice Cropping Systems under the Background of Global Warming

Qing Ye, Xiaoguang Yang, Yong Li, Wanghua Huang, Wenjuan Xie, Tianying Wang, Yan Wang
2020 Atmosphere  
Global warming might expand crop growth areas for the prevailing single and double rice cropping systems in Southern China.  ...  In addition, output per unit nitrogen usage was $0.25 per kg N higher for DRCS than for SRCS.  ...  Model Description, Calibration, Validation, and Simulations ORYZA is a process-based crop model; the initial version ORYZA 2000 simulates crop growth and development dynamics for rice (Oryza sativa L.  ... 
doi:10.3390/atmos11101048 fatcat:4wvxdhqnifgjjcgcer5rzf3pra

Homology Modeling and Microarray Analysis of Silicon Transporter Protein in Rice, Barley and Maize

2013 Canadian Chemical Transactions  
The 3D models those showed over 90% residues in favorable regions were considered in this study. Microarray analysis indicated root and shoot with highest silicon accumulation in the analyzed plants.  ...  Higher plants like rice, barley and maize have unique silicon accumulation characteristic. Silicon is taken up in the form of silicic acid by silicon transporter protein in root.  ...  A simplified presentation of InterProScan output is enlisted in Table 2 .  ... 
doi:10.13179/canchemtrans.2013.01.04.0044 fatcat:wgqkvpyfajhwnd7llwdyinmhoe

Global sensitivity analysis of yield output from the water productivity model

Eline Vanuytrecht, Dirk Raes, Patrick Willems
2014 Environmental Modelling & Software  
This study includes a global sensitivity analysis of the water productivity model AquaCrop.  ...  The global analysis comprehended a Morris screening followed by a variance-based Extended Fourier Amplitude Sensitivity Test (EFAST) under diverse environmental conditions for maize, winter wheat and rice  ...  A sensitivity analysis (SA) quantifies the influence of each uncertain factor (parameter or driving variable) on the model's output variability and is a key step in understanding the model behaviour in  ... 
doi:10.1016/j.envsoft.2013.10.017 fatcat:af37vhbewvgltdx4j2475rfzpi

Review on Plant Physiology and Crop Modeling for the Response of Rice Crop to Climate Change

2022 Journal of Natural Sciences Research  
ORYZA and CERES-Rice models are the most familiar physiological based rice models currently used for rice crop modeling studies.  ...  Process-based dynamic crop models are able to estimate a range of crop response to the environment and to assess the biophysical effects of future climate scenarios on growth and yield.  ...  of CERES-Rice and ORYZA crop models predict rice yield.  ... 
doi:10.7176/jnsr/13-4-01 fatcat:c7636opuhjcmjmexzmu3vlxhse

Spatial Rice Yield Estimation Based on MODIS and Sentinel-1 SAR Data and ORYZA Crop Growth Model

Tri Setiyono, Emma Quicho, Luca Gatti, Manuel Campos-Taberner, Lorenzo Busetto, Francesco Collivignarelli, Francisco García-Haro, Mirco Boschetti, Nasreen Khan, Francesco Holecz
2018 Remote Sensing  
crop growth model facilitated by the Rice Yield Estimation System (Rice-YES).  ...  SAR data were used to generate rice area maps using MAPScape-RICE to mask LAI map products for further processing, including smoothing with logistic function and running yield simulation using the ORYZA  ...  The boundaries, colors, denominations, and other information shown on any map in this work do not imply any judgment on the part of the authors or their institutes concerning the legal status of any territory  ... 
doi:10.3390/rs10020293 fatcat:ctwq67r2m5eqjiay3aqnnxnyze

Varietal improvement options for higher rice productivity in salt affected areas using crop modelling

Ando M. Radanielson, Donald S. Gaydon, Md. Mahbubur Rahman Khan, Apurbo K. Chaki, Md. Atikur Rahman, Olivyn Angeles, Tao Li, A. Ismail
2018 Field crops research (Print)  
The rice model ORYZA v3 has been recently improved to account for salt stress effect on rice crop growth and yield.  ...  during the later stages of crop growth in the Satkhira situation; (ii) combining short duration growth with salt tolerance (bTR and bPN) above 12 dS m-1 and a resilience trait (aSalt) of 0.11 in a variety  ...  Acknowledgements This work was supported in part, by the Global Rice Science Partnership (GRiSP), Stress Tolerant Rice Varieties for Africa and South Asia (STRASA) funded by the Bill and Melinda Gates  ... 
doi:10.1016/j.fcr.2018.08.020 pmid:31007364 pmcid:PMC6472128 fatcat:d6bnikpm7zealoq3vsyt6s3wtm

The Impacts of Climate Variability on Crop Yields and Irrigation Water Demand in South Asia

Qurat-ul-Ain Ahmad, Hester Biemans, Eddy Moors, Nuzba Shaheen, Ilyas Masih
2020 Water  
Our grid cell (aggregated over study sites) scale analysis shows that 27–72% variations in wheat and 17–55% in rice crop yields are linked with temperature variations at a significance level of p < 0.001  ...  This study examines wheat (Triticum aestivum) and rice (Oryza sativa) crop yields' sensitivity to primary climate variables (i.e., temperature and precipitation) and related changes in irrigation water  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/w13010050 fatcat:z4o54ohhyndevhh2zubm3kaoum

Food system consequences of a fungal disease epidemic in a major crop

H. Charles J. Godfray, Daniel Mason-D'Croz, Sherman Robinson
2016 Philosophical Transactions of the Royal Society of London. Biological Sciences  
Changes in global and East Asian rice production over the different scenarios are summarized in figure 4 .  ...  Despite the rapid growth in world population, there has been a secular decline in the prices of these commodities over the last century, though punctuated by episodes of volatility associated with major  ... 
doi:10.1098/rstb.2015.0467 pmid:28080990 pmcid:PMC5095543 fatcat:6zgiegtm5racthqg7hllxht7cq

Combining Limited Multiple Environment Trials Data with Crop Modeling to Identify Widely Adaptable Rice Varieties

Tao Li, Jauhar Ali, Manuel Marcaida, Olivyn Angeles, Neil Johann Franje, Jastin Edrian Revilleza, Emmali Manalo, Edilberto Redoña, Jianlong Xu, Zhikang Li, Frank Alexander Feltus
2016 PLoS ONE  
A modeling approach was innovated to evaluate varietal performance in a large number of environments using the rice model ORYZA (v3).  ...  ORYZA-based evaluation demonstrated the advantage of GSR varieties in diverse environments.  ...  Acknowledgments This study was a collaboration between the Green Super Rice (GSR) and the Stress-Tolerant Rice for Africa and South Asia (STRASA) projects.  ... 
doi:10.1371/journal.pone.0164456 pmid:27723774 pmcid:PMC5056740 fatcat:grhz4hsqnzdb5cnrihzwizvtpa

Suitability analysis of rice varieties using learning vector quantization and remote sensing images

Annisa Apriliani, Retno Kusumaningrum, Sukmawati Nur Endah, Yudo Prasetyo
2019 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
Rice (Oryza Sativa) is the main food for Indonesian people, thus maintaining the stability of rice production in Indonesia becomes an important issue for further study.  ...  The initial stage of PA is suitability analysis of rice varieties, including INPARA, INPARI, and INPAGO.  ...  The best model, that is the model that results the highest value of accuracy, is used as classification model in second process (suitability analysis of rice varieties).  ... 
doi:10.12928/telkomnika.v17i3.12234 fatcat:dr5ox6btyragrpotmrvzgijtle

Understanding Host-Pathogen Interactions with Expression Profiling of NILs Carrying Rice-Blast Resistance Pi9 Gene

Priyanka Jain, Pankaj K. Singh, Ritu Kapoor, Apurva Khanna, Amolkumar U. Solanke, S. Gopala Krishnan, Ashok K. Singh, Vinay Sharma, Tilak R. Sharma
2017 Frontiers in Plant Science  
Magnaporthe oryzae infection causes rice blast, a destructive disease that is responsible for considerable decrease in rice yield.  ...  The co-expression network showed proteins of genes in response to biotic stimulus interacted in a manner unique to resistant NIL upon M. oryzae infection.  ...  Over 600 million tons of rice is produced annually from 150 million hectares of rice paddies.  ... 
doi:10.3389/fpls.2017.00093 pmid:28280498 pmcid:PMC5322464 fatcat:cd6n7buuabdyjpruhjt6juvd6q
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