Annual Research Report On The Evaluation Of A Pepper Powdery Mildew Prediction System

ANNUAL RESEARCH REPORT ON THE EVALUATION OF A PEPPER POWDERY MILDEW PREDICTION SYSTEM

Mike Coffey, Professor
Dept. of Plant Pathology
UC Riverside
CA 92521
coffey@ucr.edu

February 2009

Introduction and Background

Powdery mildew of peppers, caused by aggressive strains of the fungus Leveillula taurica, has emerged in recent years as a serious economic threat to processing and fresh market pepper producers in California. Its essentially unpredictable nature, high capacity for sporulation, very long latent period (18-21 days) and explosive epidemic potential under as yet largely undefined conditions can make it very difficult to control. Fungicides are frequently applied too late often resulting in severe sunscald of the pepper fruit, typically to significant and sometimes disastrous economic crop losses. The unpredictable nature of the disease underlines the critical need to invest in research both on more effective control measures: including better timing and appropriate dosage of fungicides such as Rally and Quintec and the assessment of accurate early warning methods.

There is also needs to be a closer examination of the efficacy of fungicides towards the distintly different strains of powdery mildew currently attacking peppers in California. Research by our lab in 2008 determined that there are genetically dinstinct strains of powdery mildew present. There has been no critical work on the sensitivity of these different strains to fungicides such as Rally and Quintec and the outbreaks of mildew in recent years are a warning that current control strategies are probably not very effective when high disease pressure exists.

The onset of powdery mildew occurrence has been impossible to predict in recent seasons in California. A critical factor in these outbreaks is the role of weather conditions. What are the key environmental conditions, especially temperature and relative humidity that trigger the onset of mildew epidemics? Some simple experiments in 2005 using growth chambers set with various temperature/humidity environments provided evidence that the 'Hollister' pepper strain used in our research behaves similarly to a tomato strain used in the development of the Guzman-Plazola Model for mildew prediction. In 2008 we looked at the effect of different temperatures and humidities using a constant environment. While this is an artificial situation it allowed us to determine that relatively high temperature (28 C) could shut down initial mildew development completely over a wide range of relative humidities. This last year we focused on testing the Spectrum WatchDog datalogger technology in conjunction with a disease risk prediction model for Leveillula taurica has been developed by Dr. Remigio Guzman-Plazola, while working at UC Davis with Dr. Mike Davis. For pepper growers, field validation at sufficient locations and through several mildew years might encourage growers to use fungicides in a more effective manner, with economic and environmental benefits. In particular, such disease prediction technologies could be used to determine if and when to apply the first fungicide spray. Such field-based analysis and research would permit modifications and fine-tuning of prediction programs to make them more robust. We used the latest SAS version of this model in a collaboration with Dr. Remigio Guzman-Plazola.

We purchased 4 WatchDog 450 Series Data Loggers featuring four channels with a capacity of 15,000 measurements (3,750 per channel). Data can be downloaded to a PC for analysis.

Select measurement intervals are those 1, 10, 15, 30, 60 and 120 minutes. A 30-minute measurement interval will record for 85 days before the logger's memory is full. EEPROM memory keeps data safe in case of power loss.

WatchDog Datalogger

Leaf Wetness sensor

Work in 2009:

• We used four geographical locations (Ventura, Salinas Valley, Dixon, Woodland) and six different field sites.
• The plan was for collaborators to monitor daily and for the data to be sent on a regular basis to UCR for analysis.
• We collaborated with Remigio Guzman-Plazola who provided the SAS program and analyzed the data both at UCR and in Mexico.
• We issued warnings with regard to potential epidemic conditions in the four areas.

Examples of the databases and analyses:

The SAS System 20:05 Wednesday, October 8, 2008 5

SAS output for Owens-Dixon field from September 3 to October 1, 2008

Obs	DAY	MONTH	YEAR	ICT	ICRH	HTRANGE	HRHRANGE	NCHTEMP	NCLRH	T10
1	1	10	2008	22.6090	46.6042	1.94907	4.47500	1.37319	8.57882	6
2	3	9	2008	22.9855	41.5906	2.35185	6.34167	2.25685	8.47118	4
3	4	9	2008	24.7905	44.0146	2.37269	7.05417	3.37840	8.17431	2
4	5	9	2008	25.4223	46.8104	2.40972	7.15417	3.76053	7.51424	0
5	6	9	2008	25.0814	47.9260	2.57639	9.24583	3.20216	6.44201	0
6	7	9	2008	23.2238	56.4101	2.28241	7.63750	2.77014	5.30208	3
7	8	9	2008	20.5114	62.0153	2.40972	7.66250	1.49321	4.36870	8
8	9	9	2008	18.2934	70.1767	1.84491	5.35833	0.09641	0.10625	8
9	10	9	2008	20.2211	68.4878	2.13657	5.79583	1.36134	1.05556	7
10	11	9	2008	20.8162	66.6972	2.09259	6.09167	1.73210	1.41875	7
11	12	9	2008	18.9066	67.5125	2.25231	6.91250	1.15116	2.35139	10
12	13	9	2008	18.5561	67.2597	2.70370	7.33333	1.31111	3.05451	10
13	14	9	2008	19.2490	65.9639	2.40509	6.90000	1.57006	3.88924	8
14	15	9	2008	20.3490	63.7399	2.22454	7.07083	1.66748	3.55694	7
15	16	9	2008	19.6559	63.8260	2.31250	6.83333	1.04171	2.02187	7
16	17	9	2008	16.9512	62.9146	1.77083	6.70417	0.05077	2.62361	11
17	18	9	2008	16.4863	62.6632	2.50926	7.34167	0.39417	3.92951	10
18	19	9	2008	17.2297	67.0837	2.12963	7.00417	0.15814	0.97951	8
19	20	9	2008	18.4057	72.1965	1.88426	5.82500	0.40536	0.38646	9
20	21	9	2008	18.5071	69.6247	1.85417	5.67083	0.53002	1.32674	10
21	22	9	2008	19.7459	51.9705	1.93056	6.45000	0.73681	6.95417	6
22	23	9	2008	18.8935	51.9535	2.73148	7.31250	1.53295	6.95243	9
23	24	9	2008	19.7186	49.7347	2.41898	6.81667	1.75575	7.09653	8
24	25	9	2008	20.6715	47.3465	2.45833	7.68333	1.66605	7.62361	8
25	26	9	2008	21.9574	49.9417	2.15972	6.64583	2.02215	6.72222	5
26	27	9	2008	22.5502	50.2549	1.98611	5.98333	2.10868	6.68576	3

 

Obs	COND15	COND20	COND25	T30	T35	NLW	MTMA	MRHMA	RANGET	RANGERH
1	2	1	0	2	4	0	37.5000	87.8	26.1667	67.1
2	6	1	0	3	6	0	36.1667	78.9	25.6111	58.2
3	7	2	1	3	8	10	41.1111	80.7	29.0000	60.0
4	8	4	1	3	8	1	41.5556	83.1	27.8889	62.4
5	8	4	2	3	7	0	42.5000	84.8	29.2222	64.1
6	8	2	2	1	8	0	37.9444	93.1	25.8333	72.4
7	3	3	1	4	4	0	34.8889	99.5	26.3333	78.8
8	4	3	5	3	0	7	28.7222	99.5	18.9444	59.5
9	5	3	2	3	4	8	36.1667	97.9	25.6111	62.9
10	5	2	3	2	5	4	36.1667	97.9	25.6111	64.3
11	3	2	2	3	3	4	34.5000	99.5	27.1667	71.2
12	3	2	1	6	2	5	37.0556	100.0	30.5556	73.6
13	4	3	2	3	4	5	37.5000	100.0	31.0000	77.8
14	5	2	3	2	5	0	36.6111	97.9	27.6667	70.6
15	5	3	1	6	1	0	34.5000	97.9	25.5556	69.6
16	3	2	1	2	0	0	28.3333	97.9	19.7778	70.6
17	3	3	1	4	0	0	31.1667	100.0	26.7222	77.8
18	4	4	2	3	0	1	31.1667	99.5	25.0556	64.5
19	4	2	4	4	0	9	31.5556	99.5	22.6111	61.6
20	3	2	3	6	0	8	30.7778	99.5	21.8333	67.5
21	6	1	0	6	0	3	32.0000	96.2	21.4444	75.5
22	4	2	0	4	4	0	37.0556	94.7	30.9444	74.0
23	4	1	0	3	5	0	36.6111	90.6	28.8889	69.9
24	3	2	0	4	4	0	37.0556	85.7	28.5000	65.0
25	5	3	1	3	5	0	37.0556	84.3	25.3333	63.6
26	6	4	1	4	5	0	36.6111	87.3	24.5000	66.6

The SAS System 20:05 Wednesday, October 8, 2008 6

Obs	DAY	MONTH	YEAR	ICT	ICRH	HTRANGE	HRHRANGE	NCHTEMP	NCLRH	T10
27	28	9	2008	23.2789	48.4840	2.21528	6.05417	2.51647	7.22778	0
28	29	9	2008	20.5471	59.5674	1.92593	6.55833	1.24877	3.71493	4
29	30	9	2008	20.7564	57.1417	1.91898	6.35000	1.54819	4.48958	6

 

Obs	COND15	COND20	COND25	T30	T35	NLW	MTMA	MRHMA	RANGET	RANGERH
27	10	3	0	3	6	0	39.7222	78.5	26.4444	57.8
28	8	3	2	3	3	0	34.5000	94.7	23.9444	71.2
29	6	2	1	4	4	0	34.8889	93.9	23.9444	73.2

The SAS System 20:05 Wednesday, October 8, 2008 7

Obs	DAY	MONTH	YEAR	NONCOND	MODERATE	SEVERE	CLASS
1	1	10	2008	2734.97	2730.85	2724.10	N
2	3	9	2008	2306.71	2300.14	2301.00	N
3	4	9	2008	2275.87	2277.26	2271.48	M
4	5	9	2008	2355.55	2353.20	2348.52	N
5	6	9	2008	2435.04	2437.39	2430.31	M
6	7	9	2008	2590.34	2584.89	2581.89	N
7	8	9	2008	2698.32	2693.52	2691.17	N
8	9	9	2008	2668.13	2672.94	2666.56	M
9	10	9	2008	2576.75	2586.02	2573.61	M
10	11	9	2008	2591.74	2596.84	2588.14	M
11	12	9	2008	2570.73	2576.02	2569.59	M
12	13	9	2008	2546.68	2554.66	2542.93	M
13	14	9	2008	2489.78	2496.98	2488.51	M
14	15	9	2008	2572.46	2574.56	2568.64	M
15	16	9	2008	2563.35	2565.53	2560.86	M
16	17	9	2008	2629.74	2630.61	2627.70	M
17	18	9	2008	2493.10	2496.15	2491.04	M
18	19	9	2008	2433.80	2442.99	2438.02	M
19	20	9	2008	2610.52	2619.21	2612.35	M
20	21	9	2008	2604.42	2606.19	2604.27	M
21	22	9	2008	2731.89	2723.73	2721.36	N
22	23	9	2008	2451.56	2453.63	2442.64	M
23	24	9	2008	2382.24	2382.15	2375.17	N
24	25	9	2008	2387.74	2388.74	2383.16	M
25	26	9	2008	2403.43	2402.88	2398.67	N
26	27	9	2008	2414.82	2409.85	2409.44	N
27	28	9	2008	2229.03	2230.85	2226.23	M
28	29	9	2008	2514.82	2514.36	2513.06	N
29	30	9	2008	2522.35	2517.92	2517.60	N

Sistema SAS 22:47 Friday, September 26, 2008 1

SAS output for September 18 to 24. 2008 David Holden field in Ventura.

Obs	DAY	MONTH	YEAR	ICT	ICRH	HTRANGE	HRHRANGE	NCHTEMP	NCLRH	T10
1	18	9	2008	19.1522	54.1510	1.65046	6.32917	0.15409	2.05000	5
2	19	9	2008	17.3061	70.5514	1.73380	9.25000	0.00513	0.23229	10
3	20	9	2008	15.5309	78.4715	1.66667	4.15417	0.00000	0.00000	10
4	21	9	2008	16.0160	63.8014	1.54167	5.42500	0.00000	0.00000	10
5	22	9	2008	16.3926	65.8976	1.52315	7.35417	0.00000	0.89479	11
6	23	9	2008	16.5613	63.0135	1.62269	4.30000	0.00000	0.68819	11
7	24	9	2008	18.5775	80.0292	1.79167	4.26250	0.13368	0.00000	5

 

Obs	COND15	COND20	COND25	T30	T35	NLW	MTMA	MRHMA	RANGET	RANGERH
1	7	3	4	3	0	14	29.9444	97.1	17.8333	74.9
2	3	2	7	1	0	15	27.9444	100.0	19.3889	61.5
3	4	2	8	0	0	16	26.0000	99.5	20.2778	46.0
4	4	3	7	0	0	17	26.0000	90.6	19.0556	36.1
5	3	1	7	0	0	16	26.3889	86.9	17.8333	57.7
6	3	2	5	0	0	17	27.5556	98.7	19.8333	67.6
7	8	3	4	4	0	14	28.7222	98.7	17.7778	49.3

Sistema SAS 22:47 Friday, September 26, 2008 2

Obs	DAY	MONTH	YEAR	NONCOND	MODERATE	SEVERE	CLASS
1	18	9	2008	2652.83	2657.38	2648.29	M
2	19	9	2008	2611.48	2623.36	2617.68	M
3	20	9	2008	2371.91	2387.13	2378.85	M
4	21	9	2008	2124.01	2144.10	2134.65	M
5	22	9	2008	2239.49	2253.94	2252.66	M
6	23	9	2008	2522.38	2534.86	2523.08	M
7	24	9	2008	2635.92	2642.94	2635.69	M

 

SAS output for the new field at Dixon from September 3 to 17, 2008

From September 3 to 8, the canopy conditions kept mostly nonconducive (N) for powdery mildew. From day 9 to 17 all days resulted moderately conducive (M).

Notes:

If the microclimate were to keep like this in a tomato crop situation, some disease could occurr but no control action would be required. Under this conduciveness pattern the grower should download the weather data after three days in order to make sure that no three consecutive conducive (C) days ocurred. If this were the case we would have: MMMCCC, and a fungicide spray would be required in order to arrest any potentially intense fungal development and protect the crop during a Fungicide Protection Period (we use 10 days for tomato) from a potential situation of high conduciveness (mainly C days and no two consecutive N days) during these subsequent days.

Sistema SAS 22:53 Thursday, September 18, 2008

SAS output for the Holden site. 13 to 27 August 2008

Notes:

Leaf wetness data form August 14, time 17:54 to 21:44 were missing. I filled this gap with zeroes.

The SAS output indicates prevalence of conducive microclimate. According to the observed pattern, a fungicide spray should have been done on August 21.

1

Obs	DAY	MONTH	YEAR	ICT	ICRH	HTRANGE	HRHRANGE	NCHTEMP	NCLRH	T10
1	3	9	2008	22.9855	41.5906	2.35185	6.34167	2.25685	8.47118	4
2	4	9	2008	24.7905	44.0146	2.37269	7.05417	3.37840	8.17431	2
3	5	9	2008	25.4223	46.8104	2.40972	7.15417	3.76053	7.51424	0
4	6	9	2008	25.0814	47.9260	2.57639	9.24583	3.20216	6.44201	0
5	7	9	2008	23.2238	56.4101	2.28241	7.63750	2.77014	5.30208	3
6	8	9	2008	20.5114	62.0153	2.40972	7.66250	1.49321	4.36870	8
7	9	9	2008	18.2934	70.1767	1.84491	5.35833	0.09641	0.10625	8
8	10	9	2008	20.2211	68.4878	2.13657	5.79583	1.36134	1.05556	7
9	11	9	2008	20.8162	66.6972	2.09259	6.09167	1.73210	1.41875	7
10	12	9	2008	18.9066	67.5125	2.25231	6.91250	1.15116	2.35139	10
11	13	9	2008	18.5561	67.2597	2.70370	7.33333	1.31111	3.05451	10
12	14	9	2008	19.2490	65.9639	2.40509	6.90000	1.57006	3.88924	8
13	15	9	2008	20.3490	63.7399	2.22454	7.07083	1.66748	3.55694	7
14	16	9	2008	19.6559	63.8260	2.31250	6.83333	1.04171	2.02187	7
15	17	9	2008	16.9512	62.9146	1.77083	6.70417	0.05077	2.62361	11

 

Obs	COND15	COND20	COND25	T30	T35	NLW	MTMA	MRHMA	RANGET	RANGERH
1	6	1	0	3	6	0	36.1667	78.9	25.6111	58.2
2	7	2	1	3	8	10	41.1111	80.7	29.0000	60.0
3	8	4	1	3	8	1	41.5556	83.1	27.8889	62.4
4	8	4	2	3	7	0	42.5000	84.8	29.2222	64.1
5	8	2	2	1	8	0	37.9444	93.1	25.8333	72.4
6	3	3	1	4	4	0	34.8889	99.5	26.3333	78.8
7	4	3	5	3	0	7	28.7222	99.5	18.9444	59.5
8	5	3	2	3	4	8	36.1667	97.9	25.6111	62.9
9	5	2	3	2	5	4	36.1667	97.9	25.6111	64.3
10	3	2	2	3	3	4	34.5000	99.5	27.1667	71.2
11	3	2	1	6	2	5	37.0556	100.0	30.5556	73.6
12	4	3	2	3	4	5	37.5000	100.0	31.0000	77.8
13	5	2	3	2	5	0	36.6111	97.9	27.6667	70.6
14	5	3	1	6	1	0	34.5000	97.9	25.5556	69.6
15	3	2	1	2	0	0	28.3333	97.9	19.7778	70.6

Sistema SAS 22:53 Thursday, September 18, 2008 2

Obs	DAY	MONTH	YEAR	NONCOND	MODERATE	SEVERE	CLASS
1	3	9	2008	2306.71	2300.14	2301.00	N
2	4	9	2008	2275.87	2277.26	2271.48	M
3	5	9	2008	2355.55	2353.20	2348.52	N
4	6	9	2008	2435.04	2437.39	2430.31	M
5	7	9	2008	2590.34	2584.89	2581.89	N
6	8	9	2008	2698.32	2693.52	2691.17	N
7	9	9	2008	2668.13	2672.94	2666.56	M
8	10	9	2008	2576.75	2586.02	2573.61	M
9	11	9	2008	2591.74	2596.84	2588.14	M
10	12	9	2008	2570.73	2576.02	2569.59	M
11	13	9	2008	2546.68	2554.66	2542.93	M
12	14	9	2008	2489.78	2496.98	2488.51	M
13	15	9	2008	2572.46	2574.56	2568.64	M
14	16	9	2008	2563.35	2565.53	2560.86	M
15	17	9	2008	2629.74	2630.61	2627.70	M

Sistema SAS 17:10 Monday, September 1, 2008 81

Obs	DAY	MONTH	YEAR	ICT	ICRH	HTRANGE	HRHRANGE	NCHTEMP	NCLRH	T10
1	13	8	2008	21.9664	57.0021	1.23843	9.1458	0.00000	1.95278	0
2	14	8	2008	23.2984	60.4545	2.94676	10.5625	0.42296	4.90278	0
3	15	8	2008	22.6150	48.5833	1.28704	4.8792	0.25050	1.54792	0
4	16	8	2008	21.3796	66.1035	1.25000	6.1542	0.09074	0.00000	0
5	17	8	2008	21.8046	74.2708	1.25694	5.0958	0.19726	0.00000	0
6	18	8	2008	20.2649	82.7010	0.99537	3.1667	0.00000	0.00000	0
7	19	8	2008	19.7836	82.7403	1.12500	3.0583	0.00000	0.00000	0
8	20	8	2008	19.3949	80.6611	1.57870	4.3958	0.06049	0.00000	6
9	21	8	2008	19.8079	78.9476	1.43519	5.8417	0.19958	0.00000	6
10	22	8	2008	21.2587	76.3573	1.09259	6.1083	0.01404	0.00000	0
11	23	8	2008	19.5889	85.3708	1.21065	4.0292	0.00891	0.00000	0
12	24	8	2008	20.2562	84.2747	1.40278	3.3125	0.21057	0.00000	2
13	25	8	2008	20.5654	83.0986	1.44907	3.3917	0.18202	0.00000	2
14	26	8	2008	19.4699	85.5774	1.59954	3.4083	0.11890	0.00000	3
15	27	8	2008	19.9614	86.7698	1.27083	3.2208	0.11073	0.00000	0

 

Obs	COND15	COND20	COND25	T30	T35	NLW	MTMA	MRHMA	RANGET	RANGERH
1	4	4	10	0	0	0	27.5556	99.5	10.7778	74.5
2	7	2	4	6	0	0	36.1667	99.5	19.3889	78.8
3	3	8	4	6	0	0	29.1667	74.9	13.5556	54.2
4	8	5	7	4	0	5	28.3333	82.6	13.8889	23.9
5	5	8	5	6	0	2	29.1667	96.2	12.7778	35.0
6	11	4	9	0	0	0	27.5556	97.9	14.2778	34.5
7	13	2	9	0	0	0	27.5556	97.9	13.8889	35.6
8	6	2	4	6	0	0	28.3333	100.0	17.7778	41.7
9	6	2	4	6	0	0	28.7222	97.1	17.0000	38.4
10	9	5	7	3	0	0	27.9444	97.9	12.7222	35.9
11	12	3	7	2	0	0	27.5556	98.7	14.6667	33.3
12	10	3	3	6	0	3	29.1667	99.5	17.0556	38.6
13	9	2	5	6	0	0	28.3333	99.5	15.4444	37.8
14	9	2	6	4	0	0	29.1667	100.0	17.0556	37.4
15	13	2	4	5	0	0	28.3333	100.0	15.0556	37.2

Sistema SAS 17:10 Monday, September 1, 2008 82

Obs	DAY	MONTH	YEAR	NONCOND	MODERATE	SEVERE	CLASS
1	13	8	2008	3083.28	3074.67	3077.12	N
2	14	8	2008	3468.61	3461.16	3444.89	N
3	15	8	2008	2167.53	2164.32	2177.37	C
4	16	8	2008	2284.16	2290.33	2295.96	C
5	17	8	2008	2720.34	2718.98	2719.00	N
6	18	8	2008	2707.87	2710.15	2712.31	C
7	19	8	2008	2743.71	2745.54	2744.95	M
8	20	8	2008	2680.68	2676.71	2681.27	C
9	21	8	2008	2628.15	2625.75	2632.03	C
10	22	8	2008	2771.52	2769.88	2773.61	C
11	23	8	2008	2661.81	2662.60	2665.24	C
12	24	8	2008	2652.34	2649.87	2654.22	C
13	25	8	2008	2750.35	2743.72	2748.93	N
14	26	8	2008	2759.58	2759.62	2757.70	M
15	27	8	2008	2688.19	2683.77	2688.90	C

Summary and Conclusions

The results neither proved or disproved the validity of the model. The main problem was getting continuous data sets on a regular basis. In the instances where we did manage to obtain good data sets the SAS program accurately reflected the subsequent disease development. However, there were insufficient sets of data and results obtained to evaluate the reliability of the model. If there is sufficient interest a future project might envisage remote sensing of field sites using radio telemetry to relay the data to the home base for analysis.

Acknowledgements:

I thank the California Pepper Commission for their generous financial support for this research. I acknowledge also the capable assistance of Dave Holden. Valuable discourses were had with Remigio Guzman-Plazola, through the course of a year.

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