#DSSAT
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insilicoplants.bsky.social
💻🌾 Use of an enhanced cultivar calibration framework for #DSSAT to examine effects of ecotype and time-series data
by @luisvargasrojas.bsky.social Matthew Reynolds, and Diane Wang
buff.ly/nYDjbB7 #PlantScience #drought
Use of an enhanced cultivar calibration framework for DSSAT to examine effects of ecotype and time-series data
Abstract. Process-based crop modelling platforms such as DSSAT are potentially valuable tools for crop breeding programmes, with the capacity to predict ge
buff.ly
June 30, 2026 at 4:29 PM
insilicoplants.bsky.social
#FSPM: https://buff.ly/4izuTI4
#Imaging: https://buff.ly/49xU6i1
#AgML (#MachineLearning for #agricultural modelling): https://www.agml.org/ (from @agmip.bsky.social)
#Photosynthesis: https://buff.ly/3BtKo3C
#Crop modelling: https://buff.ly/4fpshKg (from #DSSAT)
#PlantScience 🧪
December 18, 2024 at 5:29 PM
kinarnicholas.bsky.social
Hydrology Paper of the Day @ucdavisplants.bsky.social on agricultural engineering to manage aquifer recharge and nitrogen: biogeochemical cycles; an experiment at Terranova Ranch (California) involving crop management; DSSAT modelling, calibration and validation; and exploring management scenarios.
ucdavisplants.bsky.social UCDavisPlants @ucdavisplants.bsky.social · Jun 27
💻 From Agricultural Water Management: DSSAT modeling shows Ag-MAR improves soil water use and yield efficiency. Timing and method shape nitrate fate and N cycling. (Wenyi Cui, Tiantian Zhou, Cristina Prieto García, Isaya Kisekka, Helen E. Dahlke)
▶️ www.sciencedirect.com/science/arti...
#SoilScience
Fig. 4. Precipitation and temperature data from the closest CIMIS weather station during the simulation period (a), simulated soil inorganic N budget (b) and simulated soil water budget (c) for profile P2 for the T0 scenario (actual experiment). The N budget includes inputs (fertilizer N, irrigation N, mineralized N) and outputs (N immobilized, N leached, plant N uptake, denitrification). The water budget includes irrigation (Ag-MAR flooding and growing season irrigation), precipitation, evapotranspiration, and drainage below soil profile. The numbers on the right side indicate the values for each polygon. The dark blue line indicates the total soil mineral NO3--N. The highlighted areas in blue, gray and orange indicate the flooding period, growing season, and fertilization respectively. The N and water budgets of P1 and P3 are shown in Figs. S5 and S6.
July 9, 2025 at 2:15 AM
insilicoplants.bsky.social
#GlobalSoilPartnership #INSAS webinar - learn how to model crop yield in salt-affected soils with experts from @ufresearch.bsky.social
April 22 | 16:00 - 17:30 CEST
www.fao.org/global-soil-... #SoilHealth #PlantScience #DSSAT
Bluesky
fresearch.bsky.social
April 18, 2025 at 3:10 PM
insilicoplants.bsky.social
DSSAT 2026 European Training Program
Sept 7 - 12, 2026 in Freising, Germany
Learn to use the DSSAT model to simulate crop growth and yield and to analyze soil and plant water, nutrient, and carbon dynamics. More info & registration:
DSSAT 2026 European Training Program
Join us in Europe for the 2026 DSSAT Training Program – hands-on fun with crop modeling!
buff.ly
June 15, 2026 at 3:10 PM
insilicoplants.bsky.social
🌽💻 The Estimation of #Maize Grain Protein Content and #Yield
by Bingxue Zhu, Shengbo Chen, Zhengyuan Xu, Yinghui Ye, Cheng Han, Peng Lu and Kaishan Song
https://buff.ly/3Z5jjN3 via Remote Sensing
#PlantScience 🧪 #DSSAT #RemoteSensing
The Estimation of Maize Grain Protein Content and Yield by Assimilating LAI and LNA, Retrieved from Canopy Remote Sensing Data, into the DSSAT Model
The assimilation of remote sensing data into mechanistic models of crop growth has become an available method for estimating yield. The objective of this study was to explore an effective…
buff.ly
November 19, 2024 at 4:10 PM
insilicoplants.bsky.social
NEW! Use of an enhanced cultivar calibration framework for #DSSAT to examine effects of ecotype and time-series data
from Luis Vargas-Rojas, Matthew Reynolds, and Diane R Wang
doi.org/10.1093/insi... #PlantSci #drought #wheat @purdueagronomy.bsky.social @cimmyt.bsky.social
February 3, 2026 at 4:10 PM
insilicoplants.bsky.social
The #DSSAT Foundation is sponsoring the 27th Open Forum on Crop Modeling and Decision Support System during this year's ASA-CSSA-SSSA Meeting. @ASA_CSSA_SSSA #ACSmtg #PlantScience https://dssat.net/
DSSAT.net - Official Home of the DSSAT Cropping Systems Model
Official Home of the DSSAT Cropping Systems Model
dssat.net
October 24, 2024 at 2:00 PM
volcaniinstitute.bsky.social
🛩️ Integrating #UAV-Based #RemoteSensing Data into the DSSAT-CROPGRO Model via SCOPE for Improved Yield and LAI Predictions in Processing #Tomato

Read Amit Weinman, Nitzan Malachy, Raphael Linker & Offer Rozenstein's full study here 👇

www.sciencedirect.com/science/arti...

Photo: Lior Fine.
May 13, 2025 at 6:08 AM
insilicoplants.bsky.social
2 open scientist positions with Mitti labs in Bengaluru, India :
Crop Modeler - Climate & GHG Emissions
Machine Learning Engineer - Geospatial AI
apply.workable.com/mitti-labs/ #PlantSciJobs #DSSAT #APSIM
November 6, 2025 at 4:10 PM
ucdavisplants.bsky.social
💻 From Agricultural Water Management: DSSAT modeling shows Ag-MAR improves soil water use and yield efficiency. Timing and method shape nitrate fate and N cycling. (Wenyi Cui, Tiantian Zhou, Cristina Prieto García, Isaya Kisekka, Helen E. Dahlke)
▶️ www.sciencedirect.com/science/arti...
#SoilScience
Fig. 4. Precipitation and temperature data from the closest CIMIS weather station during the simulation period (a), simulated soil inorganic N budget (b) and simulated soil water budget (c) for profile P2 for the T0 scenario (actual experiment). The N budget includes inputs (fertilizer N, irrigation N, mineralized N) and outputs (N immobilized, N leached, plant N uptake, denitrification). The water budget includes irrigation (Ag-MAR flooding and growing season irrigation), precipitation, evapotranspiration, and drainage below soil profile. The numbers on the right side indicate the values for each polygon. The dark blue line indicates the total soil mineral NO3--N. The highlighted areas in blue, gray and orange indicate the flooding period, growing season, and fertilization respectively. The N and water budgets of P1 and P3 are shown in Figs. S5 and S6.
June 27, 2025 at 4:29 PM
nihonmatsu.bsky.social
▪️技術的基盤：以下の統合が必要
・気象予測モデル（JMA, ECMWF, GCM）
・作物生理モデル（DSSAT, APSIM）
・機械学習による予測補完（XGBoost, LSTM, AutoML）
・GIS＋衛星リモートセンシング（NDVI, 土壌水分）
・人間中心設計＋農家フィードバックループ
July 14, 2025 at 11:46 PM
insilicoplants.bsky.social
Evaluating a #Cassava Crop Growth #Model by Optimizing Genotypic-Specific Parameters Using Multi-environment Trial Breeding Data

https://buff.ly/3Zdo7QD via @biorxiv-plants.bsky.social #model #PlantScience 🧪 #DSSAT
Evaluating a Cassava Crop Growth Model by Optimizing Genotypic-Specific Parameters Using Multi-environment Trial Breeding Data
Cassava ( Manihot esculenta Crantz) is a critical food security crop for sub-Saharan Africa. Efforts to improve cassava through breeding have expanded over the past decade. At the same time, crop…
doi.org
November 21, 2024 at 8:32 PM
insilicoplants.bsky.social
Enhancing #crop #model parameter estimation across computing environments
from Thiago Berton Ferreira, Vakhtang Shelia, Cheryl Porter, Patricia Cadena, Montserrat Cortasa, Muhammad Khan et al.

https://buff.ly/4eM5CaJ via Computers and Electronics in Agriculture #DSSAT #PlantScience 🧪
November 22, 2024 at 4:10 PM
behavecolpapers.bsky.social
Assessing rice yield responses to climate change scenarios using a crop simulation model @peerj.bsky.social
Assessing rice yield responses to climate change scenarios using a crop simulation model
Climate change is considered one of the most significant global environmental challenges of the future, and it is expected to adversely affect crop production. Rice is one of the most widely consumed staple foods in the world. Crop simulation models are tools that help researchers to simulate crop production stages for the future at the selected regions. The aim of this study was to evaluate the accuracy of the DSSAT (Decision Support System for Agrotechnology Transfer) CERES (Crop Environment Resource Synthesis) Rice (DSSAT-CERES-Rice) crop simulation model during its calibration and validation stages, and to assess the impacts of climate change in the Mediterranean region of Türkiye. In the calibration stage, the results showed that the estimated phenological values were within an acceptable range, with an error percentage below 10%. The simulated and observed leaf area index (LAI) showed good agreement with normalized root mean square error (nRMSE) ranging from 17.40% to 28.44% and Willmott’s d-index values of 0.59–0.79. Similarly, biomass simulations were consistent with observations (nRMSE: 5.60–18.52%) with satisfactory d-index values, except under I1.50 treatment. Climate change scenarios indicated that average yields under irrigated conditions increased by up to 10% in the late-future period, while rainfed conditions showed decreases of 15–25% due to higher temperatures and shortened growth duration. The findings highlight that the crop simulation model offers a robust framework for evaluating the impacts of climate change and guiding the development of effective adaptation strategies.
dlvr.it
March 13, 2026 at 12:34 AM
insilicoplants.bsky.social
PhD Position investigating the impacts of agricultural diversification on crop yield, soil health, and soil biogeochemical cycling, using a systems modeling approach
and AI at Virginia Tech
Application Deadline: September 1, 2026
#PlantSciJobs
Qualifications: § Experience with process-based ecosystem or crop models (e.g., APSIM, DSSAT, DNDC). § Proficiency in at least one programming language (e.g., Python, R, MATLAB, C++). § Experience working with large geospatial datasets. § Master’s degree in a relevant field (e.g., agroecology, soil science, agronomy, hydrology, remote sensing, or a related discipline). § Experience in AI, high-performance computing, or data assimilation is preferred. Application Deadline: September 1, 2026 Application process: Interested candidates are strongly encouraged to contact Dr. Yongfa You (yongfayou@vt.edu) before submitting their application. Please include the following documents in the email: 1) a brief description of research experience, expertise, and interests; 2) curriculum vitae; 3) academic transcripts; 4) contact information of three references.
July 29, 2026 at 4:29 PM
insilicoplants.bsky.social
Register for the DSSAT 2026 European Program
September 7 - 12, 2026 in Freising, Germany
Register here: www.eventbrite.com/e/dssat-2026....
DSSAT 2026 European Training Program
Join us in Europe for the 2026 DSSAT Training Program – hands-on fun with crop modeling!
www.eventbrite.com
August 31, 2026 at 4:29 PM
prepub-neurodegen.bsky.social
Optimizing Sowing Date, Irrigation Scheduling and Nitrogen Management for Wheat (Triticum aestivum L.): Two-Year Pooled Analysis and DSSAT-CERES-Wheat Model Evaluation for the Vindhyan Zone #NeuroDegeneration 🧪🧠
https://www.researchsquare.com/article/rs-10790800/latest
August 26, 2026 at 1:04 AM
cranberriesfeed.bsky.social
CRAN updates: DSSAT TAM #rstats
February 19, 2024 at 7:02 PM
jeffdean-uga.bsky.social
Welcomed a bumper crop of 75 students to campus this morning for the 2025 #DSSAT workshop. #CropModeling
Welcome banner for the 2025 Decision Support System for Agrotechnology Transfer (DSSAT) software training workshop. DSSAT students in the Stuckey Auditorium on the UGA Griffin Campus.
May 19, 2025 at 2:23 PM
joss-openjournals.bsky.social
Just published in JOSS: 'dpest: Streamlining Creation of PEST input files for DSSAT Crop Model Calibration' https://doi.org/10.21105/joss.08188
July 8, 2025 at 6:38 PM
cranupdates.bsky.social
Updates on CRAN: callr (3.7.5), DSSAT (0.0.9), GENEAclassify (1.5.5), GENLIB (1.1.10), latentnet (2.11.0), lmomco (2.4.14), mcgf (1.0.1), r2resize (1.9), samplingin (1.0.5), TAM (4.2-21), TreatmentPatterns (2.6.5), xportr (0.3.2)
February 19, 2024 at 9:16 PM
mellifera0724.bsky.social
結果我搞超久(前後快兩個月)才發現根本不是我有問題是DSSAT有問題
啊！！！ 阿阿阿啊！！！！！！！！

我要中風了
September 5, 2023 at 7:23 PM
insilicoplants.bsky.social
Functional diversity among crop models reveals contrasting resilience of soybean and maize to heatwaves and CO₂ enrichment
by Fedor Egorov, Yaron Michael and David Helman
buff.ly/dETPaUT via Field Crops Research #PlantScience #DSSAT
buff.ly
June 26, 2026 at 4:29 PM
insilicoplants.bsky.social
Using a structured template to improve the “FAIRness” of datasets from agricultural research
buff.ly/ww18OYB via Computers and Electronics in Agriculture #PlantScience #Agronomy #DSSAT
authors.elsevier.com
May 27, 2026 at 3:10 PM