Optimizing Crop Management Practices with DSSAT. Our Goal With increasing population and climate change, the ability to maximize crop production is essential.

Slides:

Advertisements

Similar presentations

Dr. Adriana-Cornelia Marica & Alexandru Daniel

Advertisements

Rationalization of water consumption

Soils Need Nutrients Too. KEEPING SOILS FIT Most soils have a large supply of nutrients. But when soils are continually used for growing food, nutrients.

Simulating Cropping Systems in the Guinea Savanna Zone of Northern Ghana with DSSAT-CENTURY J. B. Naab 1, Jawoo Koo 2, J.W. Jones 2, and K. J. Boote 2,

Climate Data and Crop Modeling Joel Paz, Gerrit Hoogenboom, Axel Garcia y Garcia, Larry Guerra, Clyde Fraisse and James W. Jones The University of Georgia.

Module V: Chili Pepper Plant Nutrition Unit 2: Phosphorus Nutrition Lesson 2: Importance of Primary Nutrients After completing this Unit, you will be able.

New development of Hybrid-Maize model Haishun Yang Associate Professor / Crop Simulation Modeler, Dept. Agronomy & Horticulture University of Nebraska.

 Land class of our proposed site: Class Two  There may not be enough sunlight during some parts of the day to support plant growth because there are.

Priorities of Soil Management for Extreme Events and Drought Charles W. Rice University Distinguished Professor Soil Microbiology Department of Agronomy.

Irrigation techniques in tomato Previous NextEnd.

Crop Modeling, The 2012 “Flash Drought” & Irrigation Demand Cameron Handyside University of Alabama in Huntsville Earth Systems Science Center September,

Soil Erosion. What do trees do to soil? Tree roots are in the soil. The roots help to keep soil in place. When the trees are in the soil, the soil does.

ISI-MIP agriculture simulations. 7 Global Gridded Crop Models: EPIC, GEPIC, IMAGE, LPJ-GUESS, LPJmL, pDSSAT, PEGASUS 4 first priority crops: wheat, maize,

Norwegian Institute for Agricultural and Environmental Research Long-term monitoring of nutrient losses from Norwegian micro-catchments.

A Case Study of Crop Model Applications in an Increasing Diversity of Genetically Modified Traits Girish Badgujar 1, V.R. Reddy 1, K. Raja. Reddy 2, David.

INFLUENCES OF IRRIGATION AND N FERTILIZATION ON MAIZE (Zea mays L.) PROPERTIES - Hrvoje PLAVSIC1 - Marko JOSIPOVIC1 - Luka ANDRIC1 - Antun JAMBROVIC1 -

Irrigation and Nitrogen Management Systems for Enhancing Hard Spring Wheat Protein J. Stark, E. Souza, B. Brown, and J. Windes University of Idaho.

Scheduling irrigations for apple trees using climate data Ted Sammis Go to Home.

Scheduling irrigations for lettuce using climate data Ted Sammis.

CGMS/WOFOST model principles

Concepts and Principles of Integrated Nutrient Management (INM)

Application of seasonal climate forecasts to predict regional scale crop yields in South Africa Trevor Lumsden and Roland Schulze School of Bioresources.

Impacts of Climate Change on Corn and Soybean Yields in China Jintao Xu With Xiaoguang Chen and Shuai Chen June 2014.

Vulnerability and Adaptation Assessments Hands-On Training Workshop Impact, Vulnerability and Adaptation Assessment for the Agriculture Sector – Part 2.

Scaling up Crop Model Simulations to Districts for Use in Integrated Assessments: Case Study of Anantapur District in India K. J. Boote, Univ. of Florida.

Water management Soil and Nutrients Pests and diseases.

Trends in World Food Supply

FOOD A G R I C U L T U R E E N V I R O N N M E N T BIOKENAF – QLK5-CT final meeting ATHENS, February 2007.

A process-based, terrestrial biosphere model of ecosystem dynamics (Hybrid v. 3.0) A. D. Friend, A.K. Stevens, R.G. Knox, M.G.R. Cannell. Ecological Modelling.

 Soil Fertility  Ability of a soil to provide nutrients for plant growth  Involves storage and availability of nutrients  Vital to a productive soil.

You Eat Dirt! Soil, Food, and Health. That’s why we need to eat a diversity of foods. Healthy bodies need lots of nutrients.

13-Oct-04 Flint River Basin TAC Impact of Weather Derivatives on Water Use and Risk Management in Georgia Shanshan Lin (presenting), Jeffrey D. Mullen.

MODELING THE IMPACT OF IRRIGATION ON NUTRIENT EXPORT FROM AGRICULTURAL FIELDS IN THE SOUTHEASTERN UNITED STATES W. Lee Ellenburg Graduate Research Assistant.

Small Grain Water Use Montana Small Grain Guide. Water - Nitrogen Relationship u Studies show that without adequate Nitrogen, wheat & barley yields increase.

Fertilization in Vegetables Crops IDEA-NEW. Soils Eastern Region, soil types include: 1. Sandy clay loam soils 2. Coarse-sandy soils Sandy soils, Advantages.

Nitrogen fertilizer use efficiency in rice. Contents  Introduction  Nitrogen dynamic in lowland rice soil  Methods of Nitrogen losses from rice fields.

Resource or Product?. Forage Management Unit for Adults Lesson 2: Establishing Forages.

The Tropical Rainforest IB SL. Location Introduction... They are the world's most productive ecosystems in terms of NPP and biomass. They are complex.

Integrated Pest Management. Learning Objectives 1.Define IPM (Integrated or Insect Pest Management). 2.Describe why IPM is important. 3.Describe what.

Presentation Title Capacity Building Programme on the Economics of Adaptation Supporting National/Sub-National Adaptation Planning and Action Adaptation.

Modelling the optimal phosphate fertiliser and soil management strategy for crops James Heppell August 2014.

Global Change Impacts on Rice- Wheat Provision and the Environmental Consequences Peter Grace SKM - Australia Cooperative Research Centre for Greenhouse.

NITROGEN FERTIGATION OF SUBSURFACE DRIP IRRIGATED BERMUDAGRASS M.A. Maurer* 1, J.A. Moken 2 and J.L. Young 1 1 Department of Agriculture, Stephen F. Austin.

Figure 3. Concentration of NO3 N in soil water at 1.5 m depth. Evaluation of Best Management Practices on N Dynamics for a North China Plain C. Hu 1, J.A.

Fertilizer Management

Effect of Compaction of Soil Surface to Increase Herbicide Effect in Upland Rice Cultivation By THAN TOE DEPUTY SUPERVISOR MYANMAR AGRICULTURE SERVICE.

After successful completion of 3 Units in this Lesson, you will be able to answer: 1.What is the role of nitrogen, phosphorus, and potassium in plant nutrition.

INSTITUTO NACIONAL DE INVESTIGACIÓN Y TECNOLOGÍA AGRARIA Y ALIMENTARIA (INIA) DPTO. MEDIO AMBIENTE ALCALA DE HENARES, MADRID, SPAIN Madrid, September 2006.

AgClimate View Conference/Meeting Name Location Date Presenter University

Syed Aftab Wajid Associate Professor, Department of Agronomy,

Dr. Joe T. Ritchie Symposium ： Evaluation of Rice Model in Taiwan Authors ： Tien-Yin Chou Hui-Yen Chen Institution ： GIS Research Center, Feng Chia University,

Adapting to Increasing Variability.  Longer season cultivars  Supply irrigation water  Drain soil to reduce water logging  Larger planting equipment.

THE EARTH’S RESOURCES AND POLLUTION. Soil Degradation Scientist’ studies and the experiences of farmers have shown that the most productive soil, or the.

Current approaches to assess land use and surface atmosphere interactions: Irrigation, salinity and drought Joop Kroes.

What you think of when you hear “natural resources.”

Reasons for decline in soil fertility

T6M4 PLANT FUEL Designed to match any crops need Low Salt index Nutrients are in plant available forms Compatible with popular pesticides Easy to.

An Agriculture Perspective

Root Foraging Research:

Potassium Polyacrylate Manufacturer in India

E.V. Lukina, K.W. Freeman,K.J. Wynn, W.E. Thomason, G.V. Johnson,

Managing the Soil Section 4.2.

Impacts of cattle on cotton in a bahiagrass/peanut/cotton rotation

Plants need certain things to be able to grow.

María I. Travasso (INTA)

Environmental friendly farming in Moldova - fertilising in – spring 2018 – example corn Struck, Ph.D. & Mr. Covali; Competitiveness Advisors; ENPARD TA.

Crop Growth Model Simulation of G2F Common Hybrids

Overview Exercise 1: Types of information Exercise 2: Seasonality

Reasons for decline in soil fertility

Limiting Factors Chapter 10.2.

Presentation transcript:

Optimizing Crop Management Practices with DSSAT

Our Goal With increasing population and climate change, the ability to maximize crop production is essential. We want to be able to predict optimal management practices for a variety of situations, including under environmental stresses such as during a drought, while minimizing pollution from unused fertilizer. We will use DSSAT to simulate crop growth under a range of management practices and determine the combination that produces the largest yield with the smallest nitrogen pollution. Find areas of DSSAT that can be improved.

Sensitivity Analysis Variables examined: o Days between irrigations 1 – 14 in increments of 1, 15 to 21 in increments of 3 o Total amount of water applied in irrigations throughout the growing season 200 to 500 mm in increments of 10 o Number of applications of Nitrogen as fertilizer 0 to 3 in increments of 1 o Total amount of nitrogen applied throughout the growing season 50 to 290 kg/ha in increments of 10, 300 to 400 in increments of 50 o Number of applications of Phosphorus as fertilizer 0 to 2 in increments of 1 o Total amount of phosphorus applied throughout the growing season 5 to 20 kg/ha in increments of 5, 40 to 100 in increments of 20

Sensitivity Analysis Maize simulated in Ghana without precipitation Planting date: June 17, 2004 Harvest date: September 6, 2004

Sensitivity Analysis

Harvest: 7860 kg/ha Water amount: 320 mm Days between irrigations: 5 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Optimal conditions:

Harvest: 4160 kg/ha Water amount: 200 mm Days between irrigations: 5 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Under-watered conditions:

Harvest: 6375 kg/ha Water amount: 500 mm Days between irrigations: 5 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Overwatered conditions:

Harvest: 6198 kg/ha Water amount: 320 mm Days between irrigations: 15 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Infrequently watered conditions:

Harvest: 5918 kg/ha Water amount: 320 mm Days between irrigations: 5 N applied: 100 kg N applications: 3 P applied: 40 kg P applications: 2 Sensitivity Analysis Fertilizer deprived conditions:

Harvest: 4160 kg/ha Water amount: 200 mm Days between irrigations: 5 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Under-watered conditions:

Effects of Water Deficiency Optimal Conditions Under-watered Conditions

Effects of Water Deficiency Optimal Conditions Under-watered Conditions

Harvest: 6375 kg/ha Water amount: 500 mm Days between irrigations: 5 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Overwatered conditions:

Effects of Over-watering Optimal Conditions Over-watered Conditions

Effects of Water Deficiency Optimal Conditions Over-watered Conditions

Harvest: 6198 kg/ha Water amount: 320 mm Days between irrigations: 15 N applied: 200 kg N applications: 3 P applied: 80 kg P applications: 2 Sensitivity Analysis Infrequently watered conditions:

Effects of Watering Too Infrequently Optimal Conditions Infrequently watered Conditions

Optimal Conditions Infrequently watered Conditions Effects of Watering Too Infrequently

Harvest: 5918 kg/ha Water amount: 320 mm Days between irrigations: 5 N applied: 100 kg N applications: 3 P applied: 40 kg P applications: 2 Sensitivity Analysis Fertilizer deprived conditions:

Effects of Fertilizer Deficiency Optimal Conditions Fertilizer Deprived Conditions

Effects of Fertilizer Deficiency Optimal Conditions Fertilizer Deprived Conditions

LAI vs harvest Days between irrigations Linear fit: LAI = *harvest R squared value: 0.729

Unused nitrogen vs harvest Unused nitrogen = nitrogen applied in fertilizer – cumulative nitrogen uptake

Conclusion Performed exhaustive sensitivity analysis across six degrees of freedom. This can be used to help identify optimal management practice strategies. These simulations and optimizations can be reproduced with different crop types, weather information, and soil properties. Can help identify weaknesses in DSSAT – for example, LAI values seem to be off.

Mysteries of DSSAT Why does overwatering reduce yield? o Water pushes nutrients deeper into the soil faster than roots can grow down? Why is there a spike in minimum harvest weight when nitrogen is added in two applications? Why is there a plateau in cumulative nitrogen uptake? o Crop doesn’t need more nitrogen in that growth stage? Why does nitrogen spontaneously appear in the top soil layer when water deprived? o Nitrogen from second layer is brought up along with water? Why does an LAI of three seem to be the maximum attainable value?

LAI vs harvest Days between irrigations

Unused nitrogen vs harvest Days between irrigations Unused nitrogen = nitrogen applied in fertilizer – cumulative nitrogen uptake

1,5

Sensitivity Analysis