Effect of Rainfall and Maximum Temperature on Corn Aflatoxin in the Southeastern U. S Coastal Plain Arnold Salvacion, Brenda Ortiz, Brian Scully, David M. Wilson, Gerrit Hoogenboom, Dewey Lee 1
What is Aflatoxin? Carcinogenic toxin produced by the mold fungi Aspergillus Flavus and Aspergillus parasiticus Contaminated corn is especially toxic to especially young animals and poultry Sudden death in poultry and livestock (High ) / Cause liver and esophageal cancer (Low) http://aes.missouri.edu/delta/croppest/afltox1b.jpg Corn grain with Aflatoxin > 20 ppb can not marketed. Corn can not enter inter-state commerce and only can be used for livestock feed. Yellow-green powdery growth of Aspergillus flavus on a corn rootworm-damaged ear. (Source: Alison Robertson Iowa State) 2
Factors driving contamination Drought and heat stress during kernel filling High ambient temperatures 3
to reduce Aflatoxin risks associated with climate and weather conditions Objective Drought conditions are prone during the summer months in the Southeast May, 17, 2011 Identify the effect of rainfall and temperature on Corn Aflatoxin Contamination in the Southeastern U. S. Coastal Plain 4
Specific Objectives 1. Determine probability of aflatoxin contamination greater than 20 ppb for a given amount of rainfall and maximum temperature. 2. Determine which temporal resolution (Monthly, Decadal, and Weekly) of rainfall and maximum temperature can better predict probability of contamination 5
31 N 32 N 33 N 34 N 35 N Materials and Methods Corn Aflatoxin Data - 1977 to 2004 (53 Counties in Georgia) 19 years Legend Georgia Counties Sampling Sites Weather Stations Historic weather data from 21 weather stations Logistic regression to test the relationship between aflatoxin level > 20 ppb and climatic variables 85 W 84 W 83 W 82 W 81 W 6
31 N 32 N 33 N 34 N 35 N 31 N 32 N 33 N 34 N 35 N Dry May-July Wet May-July 1978 Aflatoxin Contamination in Georgia 1997 Aflatoxin Contamination in Georgia Legend under 20 20-200 over 200 Legend under 20 20-200 over 200 85 W 84 W 83 W 82 W 81 W 85 W 84 W 83 W 82 W 81 W 7
Results from previous studies Modeling the probability of aflatoxin contamination using the Agricultural Reference Index for Drought (ARID). Month(s) in which ARID could predict aflatoxin risk Model Months Coefficient Pr (> z ) March 0.69 0.7262 April 0.32 0.1673 May 2.98 0.0497* June 46.35 1.41e -9 *** July 5.78 0.0148* August 0.19 0.0193* Aflatoxin risk can be predicted using ARID (70% confidence). June ARID values can be used to predict aflatoxin risk. 9
Stepwise logistic regression to evaluate the relation between aflatoxin contamination and climatic variables/time Coefficient p-value March-Rain event 0.00304 March - Rainfall 0.00012 March- Tmax 2.39E-06 March - Tmin 0.00271 April - Tmin 0.0212 May - Rainfall 0.06368 May - Tmin 0.13571 June - Rainfall 0.08543 June - Tmax 0.01197 June - Tmin 0.56361 July - Rain event 0.01435 July - Rainfall 0.18093 July - Tmax 0.34893 March Rain * March Tmax 9.81E-05 March Rain * March Tmin 0.0267 May Rain * May Tmin 0.0619 June Rain * June Tmin 0.07078 July Rain * Jul Tmax 0.18212 10
Predicted Probability Predicted Probability 0.2 0.4 0.6 0.8 Predicted Probability Predicted Probability 0.2 0.4 0.6 0.8 Monthly level (June) Results Variable Estimate Std. Error p-value Intercept - 9.518 1.819 <0.0001 Rainfall (mm) - 0.012 0.004 0.0019 Maximum Temperature ( C) 0.298 0.053 <0.0001 AIC = 769.84 Cross-Validation = 0.66 20 40 60 80 100 120 28 30 32 34 36 38 Rainfall Rainfall (mm) Maximum Maximum Temperature Tempreature ( C) ( o C) 11
Predicted Probability Above Threshold 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Predicted Probability Above Threshold 0.2 0.3 0.4 0.5 0.6 0.7 0.8 Predicted probability of aflatoxin contamination above threshold (20 ppb) based on monthly deviations of Rainfall and Maximum Temperature for the month of June -40-20 0 20 40 60 80 Rainfall Deviations (mm) -4-2 0 2 4 Maximum Temperature Deviations ( C) 12
Decadal level -10 days (June) Variable Estimate Std. Error p-value Intercept - 13.796 2.029 <0.0001 Rainfall (mm) 2 rd Decade - 0.010 0.003 0.0004 3 th Decade - 0.004 0.001 0.0070 Maximum Temperature ( C) 2 nd Decade 0.378 0.060 <0.0001 3 rd Decade 0.057 0.026 0.0316 AIC = 596.41 Cross-Validation = 0.722 13
Predicted Probability 0.2 0.4 0.6 0.8 Predicted Probability 0.2 0.4 0.6 0.8 Decadal level Rainfall 23rd nd Decade DECAD 3 rd 4th Decade DECAD 0 50 100 150 200 Rainfall (mm) 0 200 400 600 800 Rainfall (mm) 14
Predicted Probability 0.2 0.4 0.6 0.8 Predicted Probability 0.2 0.4 0.6 0.8 Decadal level Maximum Temperature 2nd DECAD 3rd DECAD 30 32 34 36 Maximum Tempreature ( C) 30 32 34 36 38 40 Maximum Tempreature ( C) 15
Weekly level (June) Variable Estimate Std. Error p-value Intercept - 1.036 1.912 <0.0001 Rainfall (mm) 2 nd Week - 0.0005 0.0003 0.048 4 th Week - 0.0001 0.0003 0.001 5 th Week (last two days) - 0.0025 0.0007 0.0003 Maximum Temperature ( C) 2 nd Week 0.378 0.060 0.0001 3 rd Week 0.057 0.026 0.004 AIC = 813.87 Cross-Validation = 0.70 16
Predicted Probability 0.0 0.2 0.4 0.6 0.8 Predicted Probability 0.0 0.2 0.4 0.6 0.8 Predicted Probability 0.0 0.2 0.4 0.6 0.8 Weekly level (June) Rainfall 2nd Week 3rd Week 4th Week 0 500 1000 1500 2000 Rainfall (mm) 0 500 1000 1500 2000 Rainfall (mm) 0 500 1000 1500 2000 Rainfall (mm) 17
Predicted Probability 0.0 0.2 0.4 0.6 0.8 Predicted Probability 0.0 0.2 0.4 0.6 0.8 Weekly level (June) Maximum Temperature 2nd Week 3rd Week 26 28 30 32 34 36 Maximum Temperature ( C) 28 30 32 34 36 38 Maximum Temperature ( C) 18
Mean Aflatoxin Content (ppb) Adjusting Management Strategies Planting Date 1 Date 2 70 60 50 1st Planting Date 2nd Planting Date 40 30 20 10 0 18000 22000 26000 Planting Density Preliminary Data Collected in 2010 Aflatoxin risk due to climatic conditions during the growing season could be minimized by adjusting management practices 19
Conclusions Rainfall but most important Maximum Temperature are related to aflatoxin contamination. Rainfall and Max. Temperature conditions during the Second decade of June and/or second week of June can be used to predict aflatoxin contamination. 20
Thanks Brenda Ortiz 334-644-5534 bortiz@auburn.edu 21