IJERD – International Journal of Environmental and Rural Development (2020) 11-1

Research article
erdInfluence of Meteorological Parameters on Population ofWhitefly, Bemisia tabaci on Greenhouse-grown Tomatoes
KANCHANA THINNABUT
Department of Entomology and Plant Pathology, Faculty of Agriculture, Khon Kaen University,
Khon Kaen, Thailand

DUANGRAT THONGPAK
Department of Entomology and Plant Pathology, Faculty of Agriculture, Khon Kaen University,
Khon Kaen, Thailand

CHUTINAN CHOOSAI
Department of Entomology and Plant Pathology, Faculty of Agriculture, Khon Kaen University,
Khon Kaen, Thailand

UBON TANGKAWANIT*
Department of Entomology and Plant Pathology, Faculty of Agriculture, Khon Kaen University,Khon Kaen, Thailand
Email: Ubonta@kku.ac.th
Received 23 January 2020

Accepted 25 March 2020(*Corresponding Author)

Abstract Whiteflies (Bemisia tabaci (Gennadius)) are important vectors of diseases oftomato crop production. Outbreaks of whiteflies can cause decreased productivity andtransmit pathogens. The purposes of this study were to compare the degree of white fly
infestation in two varieties of tomatoes, Shiny Queen and Ninmanee, and to investigate
whitefly population responses to weather-related environmental parameters. The study wasconducted in a green house. Whitefly population was counted every two days on threepositions of the plant; the upper part, middle part and lower part. The results indicated that
the Shiny Queen variety was infected with significantly higher numbers of white fly than was
the Ninmanee variety. Whitefly numbers observed on Shiny Queen variety were significantly
related to temperature, relative humidity, solar radiation and dew point. A mathematicalmodel was developed to predict the relationship of environmental conditions to white fly
population.
Keywords weather parameters, abiotic factors, Aleyrodidae

INTRODUCTION
The whitefly Bemisia tabaci (Gennadius) (Hemiptera: Aleyrodidae) is an important pest on tomato.
It can cause direct damage to the crop by puncturing the leaf tissue and feeding on the phloem
resulting in reduced growth rate and yield. In addition, it can transmit tomato yellow leaf curl virus(TYLCV) (Liu et al., 2013). The common cultivated tomato (Solanum esculentum) is very
susceptible to TYLCV. Infected tomato plants show symptoms of yellowing, curling, and cuppingof leaves. Additionally, this virus causes a severe stunting and abortion of flowers and fruits, leading
to 100% yield loss (Yan et al., 2018). The production of honeydew by the whitefly can causes
stickiness and promotes growth of mold. B. tabaci, eggs nymphs and adults are found on theunderside of leaves where they are protected from applications of insecticides. Production ofvegetables in greenhouses is practiced worldwide and it can protect crops from abiotic factors suchas wind, rain, and temperature that may damage to the crop. It may protect crops from many diseases,and some common field pests. The largest area of greenhouse cultivation occurs in Asia, with China
having 55% of the total world’s plastic greenhouse acreage (including large plastic tunnels) and over
75% of the world’s small plastic tunnels (Peet and Welles, 2005).
Ⓒ ISERD

40

IJERD – International Journal of Environmental and Rural Development (2020) 11-1

Because of seasonal climatic variations in agricultural areas, insect pests show varying trends
in their incidence in nature. There some reports that the population of whitefly depends upon certain
abiotic factors such as temperature, relative humidity, rainfall and sunshine hours (Janu and Dahiya,2017; Jha and Kumar, 2017). Therefore, if the correlation of whitefly abundance and abiotic factors
is understood, that knowledge can applied in designing a pest management program for tomato
production in the green house.
OBJECTIVE
The objectives of this study were to compare the degree of white fly infestation in two varieties oftomatoes, and to investigate how whitefly population changed with meteorological parameters.
METHODOLOGY
The experiment was conducted in a greenhouse at the agricultural experimental area at Khon Kaen
University. Seedlings (20 days old) of the tomato varieties Shiny Queen and Ninmanee weretransplanted from nursery to the field. Meteorological data, temperature (ºC), relative humidity (%)
wind speed (km/h), rainfall (mm), solar radiation (wat/m 2) and dew point (ºC) were recorded dailyusing a 2000 series Watch Dog weather station.
The population of whitefly was first observed when plants were 25 days old. The number ofwhiteflies was directly counted every other day between 16:00 and 17:00 from 23 tomato plants ofeach variety. Whiteflies were observed on three leaves (on upper, middle and lower parts of plant)
using hand len of 10x magnification. Analysis of variance was conducted for testing the significanceif one of the weather variables was linearly related to the whitefly population. The null hypothesis
states that 1=2=……i = 0. If alternative hypothesis is accepted ( 0), then, a mathematicalmodel of biting black flies can be analysed by logistic regression.
RESULTS AND DISCUSSION
Population dynamics of whiteflies from the two tomato varieties were similar during the vegetativeand flowering stages. In the vegetative stage, the number of whitefly from both tomato varieties waslowest. Then, whitefly population gradually increased in the late flowering stage. Abundance
increased by up to 18.3 and 2.39 insects/plant in Shiny Queen and Ninmanee, respectively. During
fruiting and harvesting stage, the number of whitefly gradually increased in Shiny Queen variety, but
it decreased in Ninmanee (Fig. 1). There were significant differences between the mean number ofnymphs and adults of whitefly on the two tomato varieties. Shiny Queen was more infected withwhitefly than was the Ninmanee variety (Table 1). The results of this study corresponded with thereports of Arnal et al (1998) and Patra et al. (2016) who found that whitefly were present throughout
the growing period in tomato.
Abiotic parameters were separately analysed by logistic regression for each tomato variety(Table 3). The results revealed that the whitefly abundance on the Ninmanee variety was not related
to abiotic parameters whereas it was on the Shiny Queen variety. This result may related to the small
number of whitefly infections in the Ninmanee variety. When each abiotic parameter was separatelyanalysed by logistic regression for the Shiny Queen variety, four of six parameters; temperature,relative humidity, solar radiation and dew point, were significantly related to the whitefly population
with r2 0.31-0.47 (Table 3). The results indicated that solar radiation and temperature were negativelyrelated to the abundance of whitefly populations. These results were corroborated with the previous
studies of Jha and Kumar (2017) who reported that sunshine hours was negatively correlated whitefly
population on tomato. There was a positive relationship between whitefly abundance and dew point,and dew formation is a meteorological and hydrologic phenomenon which can provide an importantwater input. There is a report indicating that nutrients in dew can be assimilated by certain insectⒸ ISERD41

IJERD – International Journal of Environmental and Rural Development (2020) 11-1pests (Xu et al., 2015). The results differ from some previous studies where maximum temperature
was found to be positively correlated with whitefly abundance (Bala et al., 2019).
Umar et al. (2003) have reported that the correlation of whitefly population abundance andtemperature, relative humidity and precipitation was negative for whitefly populations on somevarieties of cotton. However for certain other varieties, a positive correlation of abundance withtemperature and relative humidity was observed. Janu and Dahiya (2017) found that weather
parameters from different years show different levels of correlation. Therefore, the difference of hostplant varieties or the duration of the experiment gave different results in respect to weather
correlation. During this experiment, there was no rain and no wind speed because the experiment
was done in a controlled greenhouse.
The regression equation of whitefly population with all weather parameters; temperature,relative humidity, wind speed, rainfall, solar radiation and dew point was analysed. Statisticalanalyses indicate that no weather variable was related to the number of whiteflies in the Ninmaneevariety. However, there was statistically strong evidence that at least one of weather variables wasrelated to the number of whiteflies in Shiny Queen. The regression model revealed a significantly
positive association with only dew point, (p < 0.05), but not with any other of the weather variables(p > 0.05). The following regression model was selected as shown in Table 3 with r2 = 0.66. This
result differed from the previous report of Sharma et al. (2013) that six weather parameters played asignificant role in whitefly abundance on tomato; maximum and minimum temperature, sunshine
hours, maximum and minimum relative humidity, and rainfall. The differential results may dependon environmental conditions such as plant varieties, natural enemies, and cultural management.
Table 1 Mean number of nymphs and adults of whitefly on tomato varieties
Shiny Queen and Ninmanee
Varieties*
Shiny QueenNinmaneeadult2.93 ± 3.01a
0.95 ± 0.6b

Mean ± SD**nymph
4.56 ± 5.6a
0.50 ± 0.80b

nymph + adult7.49 ± 8.03a
1.46 ± 1.24b* n=23 (for each tomato varieties)** Mean within a column followed by different small letters differ significantly (p < 0.05)

NinmaneeFig. 1 Population dynamics of whitefly on tomato leaves during a= vegetative stage,b=flowering stage, c=fruiting stage, and d= havesting stage(arrow indicates insecticide application)Ⓒ ISERD

42

IJERD – International Journal of Environmental and Rural Development (2020) 11-1

Table 2 Meteorological parameters data from tomato greenhouse during the experiment
Checkeddate

Temperature (C)

RH (%)

Solar Rad
(wat/m2)

Dew Point(C)

Rainfall(mm)WindSpeed(km/h)

1

28.87

56.77

67.33

21.53

002

30.75

39.8

141

19

00

34

32.4
31.21

33.6
40.87

144.33124.33

18.67
20.2

0000

56

33.12
32.71

34.3
30.47

113.33158.33

18.83
17.87

0000

78

33.45
34.04

27.77
28.07

138
161.67

17.77
18.53

0
0

0
0

9

33.86

27.93

170.33

18.73

0

0

10
11

30.86
29.21

45.13
49.63

76.33
114.33

20.8
21.63

0
0

0
0

12
13

27.94
32.72

55.93
27.63

78
150

21.9
17.3

0
0

0
0

14

29.73

43.3

138

19.9

0

0

15
16

28.32
30.63

48.67
32.13

128.67158.67

19.5
15.7

0
0

0
0

17
18

31.54
33.71

38.47
32.53

152.67
163

19.17
17.4

0
0

0
0

19
20

30.3
31.54

60.57
45.7

71
108.67

22.67
21.33

0
0

0
0

21

29.2

64.7

66.67

23.37

0

0

2223

31.49
31.83

55.23
40.33

127.33
92.67

22.5
19.2

0
0

0
0

2425

33.15
31.28

48.53
40.7

102.33100.33

20.9
19.07

0
0

00

26

30.22

61.33

95

23.27

0

0

27
28

30.58
27.88

65.27
69.57

60.67
81.33

22.5
23

0
0

0
0

29
30

30.32
28.73

58.43
60.67

69.33
61

22.83
21.93

0
0

0
0

31
32

16.88
28.52

66.7
65.4

27.33
59.33

67.47
74.1

0
0

0
0

33

30.8

52.87

90.33

72.7

0

0

34
35

30.88
30.25

64.33
54

28
106

72.9
71.43

0
0

00

36
37

32.13
30.94

38.9
46.93

117
119.33

66.3
67.97

0
00038

32.44

36.57

129.67

64.8

0039

31.42

46.1

117.6768.27

00Ⓒ ISERD

43

IJERD – International Journal of Environmental and Rural Development (2020) 11-1

Table 3 Regression equations of weather variables related to whitefly population
Shiny Queen

Temperature (ºC)
Relative humidity (%)
Solar radiation (wat/m2)
Dew point (ºC)
Wind speed (km/h)
Rainfall (mm)Pooled weather
parameters

2Regression EquationR𝑦 = 56.54 − 1.59𝑋
𝑦 = −12.2 + 0.42𝑋
𝑦 = 23.30 − 0.15𝑋
𝑦 = 0.06 + 0.24𝑋
-0.31
0.44
0.47
0.38-𝑦 = 15.36 + 0.16𝑑𝑒𝑤 𝑝𝑜𝑖𝑛𝑡

0.66

Ninmanee
Regression
Equation-R2-

CONCLUSION
This experiment provided information on the population of whitefly infesting two varieties of tomato;
Shiny Queen and Ninmanee. The statistical significance of whitefly numbers indicated that the Shiny
Queen was more infested by whitefly than the Ninmanee variety. Some weather variables;
temperature, relative humidity, solar radiation, and dew point, were related to whitefly population in
Shiny Queen. Those parameters were used to create a mathematical model for white fly populationin the greenhouse.
ACKNOWLEDGEMENTS
This research has been supported by Khon Kaen University. We would like to thank Dr. Chanon
Lapjit who provided plants and green house for this research.
REFERENCES
Arnal, E., Debrot, E., Marcano, R.M. and Manlagne, A. 1998. Population fluctuaion of whitefly and its relation
to tomato yellow mosaic in one location in Venezuela. Fitopatologia Venezoloana, 6, 21-26.
Bala, S.Ch., Nihal, R. and Sarkar, A. 2019. Population dynamics of whitefly (Bemisia tabaci, Genn.) and Thrips(Scirtothrips dorsalis, Hood.) in Bt cotton. J. Entomol. Zool. Stud., 7, 1020-1024.
Janu, A. and Dahiya, K.K. 2017. Influence of weather parameters on population of whitefly, Bemisia tabaci in
American cotton (Gossypium hirsutum). J. Entomol. Zool. Stud, 5, 649-654.
Jha, S.K. and Kumar, M. 2017. Effect of weather parameters on incidence of whitefly, Bemisia tabaci(Gennadius) on tomato. J. Entomol. Zool. Stud., 5, 304-306.
Liu, B., Preisser, E.L., Chu, D., Pan, H., Xie, W., Wang, S., Wu, Q., Zhou, X. and Zhang, Y. 2013. Multiple
forms of vector manipulation by a plant-infecting virus: Bemisia tabaci and tomato yellow leaf curl virus.
J. Virol., 87, 4929-4937.
Patra, B., Alam, Sk.F. and Samanta, A. 2016. Influence of weather factors on the incidence of whitefly, Bemisia
tabaci Genn. On tomato in Darjeeling Hills of West Bengal. JANRM., 3, 243-246.
Peet, M. and Welles, G., 2005. Greenhouse tomato production. In: Heuvelink, E.P. (Ed.), Crop Production
Science. Horticulture Series.
Sharma, D., Maqbool, A., Ahmad, H., Srivastava, K., Kumar, M., Vir, V. and Jamwal, S. 2013. Effect ofmeteorological factors on the population dynamics of insect pests of tomato. Veg. Sci., 40, 90-92.
Umar, M.S., Arif, M.J., Murtaza, M.A., Gogi, M.D. and Salman, M. 2003. Effect of abiotic factors on thepopulation fluctuation of Whitefly, Bemisia tabaci (Gen.) in nectaried and nectariless genotypes of cotton.
Int. J. Agri. Biol., 5, 362-363.
Xu, Y., Yan, B. and Tang, J. 2015. The effect of climate change on variations in dew amount in a paddy
ecosystem of the Sanjiang Plain, China. Adv. Meteorol, Article ID 793107, 9.
Yan, Z., Pérez-de-Castro, A., Díez, M.J., Hutton, S.F., Visser, R.G.F., Wolters, A.A., Bai, Y. and Li, J. 2018.
Resistance to tomato yellow leaf curl virus in tomato germplasm. Front, Plant Sci., 9, 1198.

Ⓒ ISERD44