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Frontiers of Agricultural Science and Engineering

ISSN 2095-7505

ISSN 2095-977X(Online)

CN 10-1204/S

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Front. Agr. Sci. Eng.    2018, Vol. 5 Issue (4) : 462-468    https://doi.org/10.15302/J-FASE-2018239
RESEARCH ARTICLE
Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application
Alexey FILIPPOV, Maria KUZNETSOVA, Alexander ROGOZHIN, Olga IAKUSHEVA, Valentina DEMIDOVA, Natalia STATSYUK()
Laboratory of Potato & Vegetable Diseases, All-Russian Research Institute of Phytopathology, Bolshie Vyazemy 143050, Russia
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Abstract

Late blight is one of the most important potato diseases. To minimize yield losses, various protective measures are used including fungicide application. Active use of fungicides results in a contamination of the environment. Therefore, crop protection strategies optimizing the number of treatments are of great interest. Using information about late blight development in an experimental potato field recorded over 30 seasons, a simulator to forecast yield losses caused by the disease was developed based on the number of 5-d periods favorable for reinfection of plants during a vegetation season. The simulator was successfully verified using independent data on the disease development from nine unprotected potato fields in the Netherlands and Germany. The average difference between the calculated and real yield losses did not exceed 5%. Using the simulator and weather data for a period of 2007–2017, yield losses were calculated for several areas of the Bryansk, Tambov, and Orenburg Regions of Russia. The results revealed differences in disease development between these regions and may be used to develop recommendations for a frequency of fungicide applications according to the regional risk of epidemics, leading to a significant reduction in fungicide use.
Keywords potato      late blight      Phytophthora infestans      yield losses      retrospective analysis      mathematical model     
Corresponding Author(s): Natalia STATSYUK   
Just Accepted Date: 06 September 2018   Online First Date: 09 October 2018    Issue Date: 19 November 2018
 Cite this article:   
Alexey FILIPPOV,Maria KUZNETSOVA,Alexander ROGOZHIN, et al. Development and testing of a weather-based model to determine potential yield losses caused by potato late blight and optimize fungicide application[J]. Front. Agr. Sci. Eng. , 2018, 5(4): 462-468.
 URL:  
https://academic.hep.com.cn/fase/EN/10.15302/J-FASE-2018239
https://academic.hep.com.cn/fase/EN/Y2018/V5/I4/462
Fig.1  Working window of a simulator program calculating potato yield losses caused by late blight development
Fig.2  Working window of a simulator program determining weather conditions favorable or unfavorable for late blight development
Fig.3  Variation in late blight severity within the observed period (1972–2017, Moscow Region)
Vegetative phase Correlation coefficient
I (Jun. 15 – Jul. 4) -0.04
II (Jul. 5 – Jul. 24) 0.78
III (Jul. 25 – Aug 15) -0.20
Tab.1  Coefficients of correlation between the frequency of reinfection periods and potato yield losses caused by late blight calculated for different vegetative phases
Geographic location of data collection points Year Yield loss/% Deviation of actual from calculated data/%
Actual[11] Calculateda
Munich (Germany) 48°93′ N, E11°55′ E 2011
2012
2013
2014
2016		 41
32
14
40
20		 40
42
8
35
24		 -1
10
-6
-5
4
Lelystad (Netherlands) 52°45′ N, 5°53 E′ 2011
2012
2014
2015		 49
35
26
42		 50
41
33
41		 1
6
7
-1
Tab.2  Comparison of actual and calculated yield losses for nine potato fields in Germany and Netherlands
Region Area Average tuber yield loss/% Frequency of seasons with the corresponding yield losses
<10% 10–30% >30%
Bryansk Bryansk 21.2 18.2 54.5 27.3
Krasnogorsk 20.5 36.4 45.5 18.2
Zhukovsk 19.4 36.4 36.4 27.3
Navlinsk 21.8 36.4 45.5 18.2
Trubchevsk 9.8 63.6 27.3 9.1
Mean 18.5 38.2 41.8 20.0
Tambov Zherdevka 6.4 90.9 0.0 9.1
Kirsanov 10.5 72.7 18.2 9.1
Michurinsk 10.7 72.7 18.2 9.1
Morshansk 11.7 72.7 9.1 9.1
Tambov 9.8 81.8 – 18.2
Mean 9.8 78.2 11.4 10.9
Orenburg Orenburg 1.5 100.0 – –
Buguruslan 2.7 100.0 – –
Sorochinsk 2.8 100.0 – –
Akbulaksk 1.4 100.0 – –
Svetlinsk 1.3 100.0 – –
Mean 1.9 100.0 – –
Tab.3  Late blight severity calculated for three regions of Russia (2007–2017)
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