North cotton growing zone of India witnessed another whitefly outbreak within a decade

doi:10.21203/rs.3.rs-3113576/v1

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North cotton growing zone of India witnessed another whitefly outbreak within a decade

https://doi.org/10.21203/rs.3.rs-3113576/v1

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Whitefly, Bemisia tabaci (Gennadius), is a polyphagous and important pest of cotton worldwide. Both adults and nymphs of B. tabaci affect the crop by causing direct and indirect damage. A severe outbreak of whitefly was experienced during 2015 in North India on cotton followed by the outbreak during 2022 cotton season. During 2015, whitefly crossed and persisted above ETL (Economic Threshold Level is 18adults/ 3 leaves) between 28^th - 35^th SMW but during 2022 stayed above ETL between 27^th - 36^th SMW and peak incidence noticed during 31^st and 29^th SMW , respectively. So in 2022, early pest buid up in the form of ETL as well as peak activity indicating longer persistence (≥10 weeks ) of whitefly and high severity in terms of average whitefly population during season resulted in more damage to cotton crop. Additionally , farmers’ field survey data during 2022, showed whitefly population crossed ETL at 585 out of 1317 locations (44.42 percent) and during 2015, 620 out of 1089 locations (57 per cent ) were recorded above ETL indicating that unlike 2015; 2022 outbreak was not uniform in the entire zone wherein only few blocks of Punjab, Haryana and Rajasthan recorded severe infestations of whitefly.

Biological sciences/Ecology

Biological sciences/Zoology

Earth and environmental sciences/Ecology

Cotton

Whitefly

Outbreak

Resurgence

Climate change

The whitefly, Bemisia tabaci Gennadius (Hemiptera: Aleyrodidae) was first reported in Greece about 125 years ago(1889) ⁵²² . In India, whitefly was first recorded on cotton at Pusa (Bihar) during 1905 and assumed the status of a serious pest of cotton in Punjab in the 1930s. However, B. tabaci had assumed a status of key pest of cotton only after the introduction of synthetic pyrethroids during early 1980s to control bollworms in cotton ¹⁷³.The ability of whitefly to survive and proliferate rapidly is attributed to its adaptability to a wide range of hosts over 900 plant species ¹⁵¹⁹. Besides cotton, its infestations are observed on other important cultivated crops likegreen gram, black gram, pigeon pea, cluster bean, cucurbits ,okra, brinjal, chilli, etc. during the season and at the end of cotton season, the adults migrate to other crops such as Brassicas, potato, tomato and several weed hosts like peelibuti (Abutilon sp.), kangi buti (Sida sp.), puthkanda (Achyranthes splendens), etc. Although suitable weather conditions for growth of B. tabaci are 27^oC temperature and 71% relative humidity, but for rapid population build up of this insect hot and humid conditions are always favourable. Whitefly cause damage by sucking phloem sap that results in early wilting, premature defoliation, stunted growth,that eventually lead to yield loss. Indirect damage to crop plants is caused by the whitefly-excreted honeydew, which promotes fungal growth on leaves and cotton in opened bolls and thereby reduces the quality and market value of produce. Cotton losses due to whitefly have been estimated to be in the range of 15–20% and sometimes up to 30% ⁹.The economic threshold level (ETL) of 18 adults per 3 leaves has been established for triggering the insecticidal management of whitefly ².

Over the years, whitefly has created a niche in the cotton agroecosystems and has almost become a pest of a regular occurrence in all the cotton-growing areas of North-West India. The period of activity of whitefly remain from 30–150 days after sowing with occurence of more than one peaks of population during the season. Whitefly outbreak affected the cotton production adversely in 2015 as whitefly outbreak resulted in reduction in productivity of the zone ( Table 1). Worldover severe outbreaks of whitefly were reported in Sudan and Iran (1950s), El Salvador (1961), Mexico (1962), Brazil (1968), Turkey (1974), Israel (1976), Thailand (1978), Arizona and California, USA (1981) and Ethiopia (1984). In 1989-90 its epidemic invasion was recorded on cotton in the USA, Mexico, South America and Asia and in 1995 again in USA (Arizona). In 1994, the outbreak of B.tabaci was reported on cotton crop in Australia while its occurrence appeared in the country in 1959 without much economic loss ⁶¹⁴.

During the cotton growing season of 2022, increased whitefly infestation was recroded in many blocks of the North zone. This second outbreak has occurred within less than a decade’s time since 2015. Occurrence of whitefly outbreak on cotton crop may be due to the prevailing ecological conditions, impact of climate change and host plant interactions. The main aim of present study was to have an insight into the severity of whitefly incidence in cotton crop and associated factors responsible for the outbrteak.

To have an insight into infestation level and peak activity of whitefly during the crop season was continuously monitored through population dynamics studies under unprotected conditions atexperimental farm of various research institutes of North zone. Similarly surveys were also conducted at farmers’ fields locations of the North zone to record whitefly incidence and number of locations having incidence above Economic Threshold Levels (ETL).

2.1 Population dynamics under unprotected conditions: Cotton genotypes from Non-Bt and Bt/BG-II backgrounds were sown at 5 experimental farms of North zone in an area of 500 sq meter for each genotype. Following the standard observation protocol, the weekly population of whitefly was recorded on Non-Bt, and Bt-cotton genotypes under unprotectedconditionsinitiated one month after sowing of the crop. Regular observations on the dynamics of whitefly under unsprayed conditions were recorded in cotton crops. Both BG-II and Non-Bt genotypes were selected for study as a representative of the cultivation practices of the growers and suitability to whitefly where Non-Bt genotypes were common throughout the period of study however the Bt cotton genotypes changed as per the pattern of cultivation among growers of the zone. The population of whitefly adults and nymphal counts was recorded from 3 fully formed leaves (upper, middle and lower strata) of 20 tagged plants in these cultivars regularly at weekly intervals. The mean of the weekly population was compared for population dynamics. Based on the 19 weekly observations recroded on BG-II and HS-6 (Non-Bt genotype) during the season, seasonal mean was calculated to compare the severity of the incidence.

2.2 Farmers field locations surveys: The weekly surveys were conducted at farmers’ field locations in North zone ( Fig. 1) to assess the ground situations where number of locations having infestation above the ETL was noted and pointed out. During each survey, a total of five or more locations from five different villages were monitored for sucking pests. Whitefly populations were recorded on randomly selected 3 leaves per plant. The average population of whitefly adults/ 3leaves was calculated and used for comparison and level of incidence.

2.3 Weather Parameters: Prevailing weather parameters like maximum temperature (T max), minimum temperature (Tmin ), average temperature (T mean), morning relative humidity (RH-M), evening relative humidity (RH-E), average relative humidity (RH mean), cumulative rainfall during the crop duration were recorded at ICAR-CICR, Regional Station Sirsa. Here we have also discussed the relationship between seasonal mean (24 SMW-42 SMW) of weather data (taken during 2012 to 2022) and whitefly population/3leaves (mean of two genotypes) at ICAR-CICR ,Regional Station, Sirsa location.

2.4 Statistical Analysis: Analysis of Variance (ANOVA) was conducted using SAS statistical software version. Prior to conducting ANOVA, all the data were checked for the normality by seeing the normal distribution curve. Means of the treatments were separated based on the Tukey's Honestly Significant Difference test with α = 0.05 level of significance.

Regular observations on the dynamics of whitefly on cotton cultivars under unsprayed conditions indicated that the 2015 outbreak was not a sudden phenomena but was a result of steady increasing trend of population built up of whitefly since 2012 in the entire North zone (Haryana, Rajasthan and Punjab). However, the incidence of whitefly recorded during 2022 was compared with whitefly incidence recrorded during 2015 the then outbreak year for whitefly.

3.1 In Haryana, Sirsa district is having the highest area under cotton cultivation which was selected for experimental studies under unprotected conditions as well as for farmers field locations survey to assess the ground situations. The experimental data under unprotected conditions during 2012, 2013 and 2014 recorded an increase in average whitefly adult population per three leaves (Table 3) in BG-II genotype and HS-6 (Non-Bt genotype). Normal peak activity of whitefly was recorded during 30-31st Standard Meteorological Week (SMW) during 2012 and 2013, while it reached its highest in 37th SMW during 2014 leading to a good carry-over of whitefly incidence for the ensuing cotton season of 2015. During 2015, 2016 & 2017 ,whitefly surveillance clearly showed that the situations of the whitefly population during 2015 (epidemic year) and 2017 were almost at the same level (above ETL level). However, in 2017, the damage supposed to be caused by the whitefly and CLCuD on cotton production was curbed due to the use and timely adoption of management strategies. The decreases in seasonal mean /3leaves recorded were 20.32, 10.1 & 16.5 in BG-II and 20.9, 12.5,&16.4 in HS-6 during 2015 to 2017 (Table 2).During 2018, 2019 & 2020 seasonal mean (average population range per three leaves) was 14 (5.8–31.2), 11.1 (3.8–18.4) & 13.47 (0.7–35.8) in BG-II and 16.3 (5.9–36.4), 13.9 (3.9–29.5) & 16.52 (0.5–48.1) in HS-6 (N-Bt), respectively. The peak activity was recorded during 29, 31 & 38th SMW, respectively (Table 2). During 2021 & 22 seasonal mean per three leaves ranged between 7.02 (1.20–13.70) & 33.50 (6.50–74.10) in BG-II, 8.98 (0.30–28.00) & 38.53 (11.10–84.10) in HS-6, respectively (Table 2). Peak activity of whitefly was recorded from 29th SMW onwards in BG-II and HS-6 (Fig. 1). The seasonal mean data from 2012 to 2022 reported maximum whitefly population during 2022 cotton season .

3.2 In Punjab, Bathinda district cultivated cotton in the largest area among cotton growing districts.On farm experiment conducted during 2012, 2013 and 2014 in BG-II genotype average whitefly adult population per three leaves exhibited an increasing trend in population.Peak activity of whitefly was recorded during 41st SMW in the year 2012 and 2013 but in 2014 its paek was in 39th SMW supporting good population innoculum for 2015 cotton season. During 2015, 2016& 2017 population per three leaves ranged between 3.6–34.1 (2017) in BG-II genotype whereas during 2015 and 2016 the crop was not sown. In HS-6, whitefly adult population /3leaves ranged from 0.4–28.6 (2016), 3.2–31.5 (2017) but in 2015 the data was not recorded due to the failure of HS-6 crop (Table 2). During 2015, 2016& 2017 peak activity of whitefly was recorded between 38th & 39th SMW. During 2018, 2019 & 2020 population per three leaves recorded seasonal mean/3leaves as 5.2, 3.9 & 3.8, in BG-II; 3.8 (2019) & 14.1(2020) in HS-6 (Table 2). During 2021,the population per three leaves ranged between 1.8–15.2 in BG-II, 0.8–16.4 in HS-6 whereas during 2022 it ranged between 4.50–94.20 & 4.4–105. Peak activity of whitefly during 2022 was recorded during 30th SMW. The seasonal mean/3leaves recorded was 11.7 & 25.89 in BG-II and 6.5 & 28.10 in HS-6 during 2021 & 2022.The highest seasonal mean of whitefly adults/3leaves was recorded during 2022.

3.3 In Rajasthan, Sriganganagar district is having maximum area under cotton cultivation. On farm experiment on population dynamics under unprotected conditions conducted during 2012, 2013 and 2014. For the year 2012 and 2013, whitefly peak incidence was recorded during the 33rd & 35th SMW while in 2014 it reached its highest in 33rd SMW preceeding to 2015 outbreak. The entire North zone experienced the peak during later part of 2014 season supporting a good start for the next season of 2015. The increasing trend in seasonal mean/3leaves recorded during 2012, 2013, and 2014 was12.1, 12.8 & 53.9 in HS-6 (Table 2). The population per three leaves in BG-II ranged between 2.3–41.7 during 2017,whereas it was not sown in 2015 and 2016. In HS-6, population per three leaves ranged from 0.0-83.9 (2016) & 1.2–46.5 (2017) but in 2015, HS-6 was not available. During 2015, 2016 & 2017 peak activity of whitefly was recorded between 40th & 41st SMW. Stable seasonal mean/3leaves 17.7(2016) and19.1 (2017) was recorded in HS-6 during 2015, 2016 and 2017, respectively (Table 2). During 2018, 2019 & 2020 population per three leaves ranged between 8.9 (0.0-23.5), 10.2(0.0-28.1) & 35.8( 4.6–98.4) in BG-II and 10.1 (0.0-29.5) during 2019 & 32.1 (0.0-80.6) during 2020 in HS-6 whereas HS-6 not sown in 2018 (Table 2). During 2021 and 2022 seasonal mean (average population range) per three leaves was 5.6 (0.5–17.4) & 52.51 (2.67-111.11) in BG-II and 9.2 (0.4–38.6) &47.88 (4.43-146.22) in HS-6 (Table 2). Peak activity of whitefly was recorded during 28th SMW in 2022.

Table : 1 Area, and Productivity of North Zone

Year	Area ( In Lakh ha)				Zonal Productivity ( Lint kg/ha)
Year	Haryana	Punjab	Rajasthan	Total North Zone	Zonal Productivity ( Lint kg/ha)
2011	6.41	5.60	4.70	16.71	651
2012	6.14	4.80	4.50	15.44	705
2013	5.36	4.46	3.93	13.75	729
2014	6.48	4.20	4.87	15.55	579
2015	6.15	3.39	4.48	14.02	433
2016	5.70	2.85	4.71	13.26	590
2017	6.56	3.85	5.03	15.40	624
2018**	7.08	2.68	6.29	16.05	625
2019	7.23	2.48	7.60	17.31	638
2020	7.40	2.52	8.08	18.00	572
2021	6.95	3.04	7.07	17.06	599
2022	6.47	2.41	7.77	16.65	439

Source: Committee on Cotton Production and Consumption (COCPC), Ministry of Textile, Govt. of India and Ministry of Agriculture and Farmers’ Welfare, Govt. of India.

Table 2

**Population range and peak activity period of whitefly population recorded based on experiment conducted under unprotected conditions**.
Year	Sirsa		Sri Ganganagar		Bathinda
	Population range /3 leaves (Peak activity SMW)		Population range /3 leaves (Peak activity SMW)		Population range /3 leaves (Peak activity SMW)
	BG-II Genotype	Non Bt genotype	BG-II Genotype	Non Bt genotype	BG-II Genotype	Non Bt genotype
2012	1.3–8.9(30)	0.9–8.2(40)	0.0-27.1(33)	0.7–25.5(33)	1.0-46.3 (41)	-
2013	2.1–48.0(31)	1.1–55.0(31)	-	0.7–28.4(35)	-	2.9-109.8(41)
2014	0.8–54.9(37)	0.4–38.9(37)	-	10.0-145.4(33)	-	0.0-120.6(39)
2015	0.3–57.7(31)	0.2–55.5(30)	-	-	-	-
2016	1.7–17.3(31)	2.5–26.9(32)	-	0.0-83.9(40)	-	0.4–28.6(38)
2017	0.0-45.7(30)	0.4–41.3(30)	2.3–41.7(41)	1.2–46.5(39)	3.6–34.1(30)	3.2–31.5(39)
2018	5.8–31.2(29)	5.9–36.4(30)	0.0-23.5(37)	-	0.7–10.6(27)	-
2019	3.8–18.4(31)	3.9–29.5(30)	0.0-28.1(27)	0.0-29.5(29)	0.1–9.4(33)	0.0-8.2(34)
2020	0.7–35.8(38)	0.5–48.1(38)	4.6–98.4(38)	0.0-80.6(38)	1.0-41.8(31)	1.3–46.5(31)
2021	1.2–13.7(38)	0.3–28.0(29)	0.5–17.4(40)	0.4–38.6(37)	1.8–15.2(33)	0.8–16.4(34)
2022	6.5–74.1(29)	11.1–84.1(29)	2.67-111.11(28)	4.43-146.22(28)	4.50–94.20	4.4-105.20 (30)

Table 3

Seasonal mean of whitefly population recorded from the experiment conducted under unsprayed conditions
Year	Sirsa		Sri Ganganagar		Bathinda
	Seasonal Mean /3 leaves (24–42 SMW)		Seasonal Mean /3 leaves (24–42 SMW)		Seasonal Mean /3 leaves (24–42 SMW)
	BG-II Genotype	Non Bt genotype	BG-II Genotype	Non Bt genotype	BG-II Genotype	Non Bt genotype
2012	3.8^h	3.50^g	15.4	12.1	19.5	-
2013	13.4^e	12.9^ef	-	12.8	-	28.9
2014	15.7^cd	14.2^cd	-	53.9	-	45.7
2015	20.3^b	20.9^b	-	-	-	-
2016	10.1^f	12.5^de	-	17.7	-	9.0
2017	16.5^c	16.4^c	15.8	19.1	13.8	3.2
2018	14.0^de	16.3^c	8.9	-	5.2	-
2019	11.1^f	13.9^cde	10.2	10.1	3.9	3.8
2020	13.4^e	16.5^c	35.8	32.1	3.8	14.1
2021	7.0^g	8.9^f	5.6	9.2	11.7	6.5
2022	33.5^a	38.5^a	52.51	47.88	25.89	28.10
*Different letters as superscripts within a column indicate significant differences (p < 0.05)

The seasonal mean of the whitefly recroded under different genotypes in unprotected conditions clearly indicated that the population of whitefly was significantly higher during 2022 than 2015 season of whitefly outbreak. In case of both genotypes BG-II Cotton hybrid and HS-6, Non-Bt hirsutum genotype seasonal means of whitefly during 2013, 2014, 2016, 2017, 2018, 2019 & 2020 were almost similar. The highest seasonal mean from 2012 to 2022 was during 2022 in the entire zone and was above than 2015, a year known for whitefly outbreak (Table 3)

The sucking pests in cotton are in conflict with each other due to interspecific competition among whitefly,leafhopper and thrips due to the coinciding activity period in cotton crop in North zone of India, however each sucking pest require a particular set of climatic and agronomic conditions. The maximum number of locations for whitefly (620 out of 1089 locations i.e. 56.93% ) crossed ETL during 2015 followed by 2022 (585 out of 1317 locations i.e. 44.42% ) whereas the minimum locations recorded above ETL during 2018 (54 out of 2485 i.e. 2.17%).The season 2022 was very particular as locations above ETL for the leafhopper population (18.38%) was also found highest (242 out of 1317 leafhopper) in 2022. The lowest number of locations recroded (2.36% i.e. 55 out of 2335) above ETL for leafhopper were during 2016. Thrips known to appear earlier than whitefly and leafhopper, the locations of thrips recorded above ETL were maximum during 2021 (152 out of 1220) and minimum (25 out of 2335 ie 1.07%) were recorded during 2016 (Table 4). Based on the data from 2015 onwards, during 2022 early whitefly infestation during the season was recorded, with the highest seasonal mean among all years with long persisting infestation above ETL consistently for more number of SMWs warranting more number of insecticidial sprays to bring down the pest below ETL to avoid the losses. But based on farmers field surveys higher number of locations were recorded above Economic Threshold Level during 2015 ( 620 out of 1089) in comparison to 2022 (585 out of 1317) indicating that unlike 2015, 2022 outbreak was not uniform in the entire zone wherein only few blocks of Punjab, Haryana and Rajasthan recorded severe infestations of whitefly .

Table 4

**Farmers’ field locations surveyed for insect pests infestation** Farmers’ field locations were surveyed in Hisar& Sirsa (Haryana), Bathinda & Faridkot (Punjab and Sriganganagar (Rajasthan) at weekly interval to study the incidence of whitefly and issue advisory to the farmers.
Year	Total no. of locations surveyed	Number and percentage of locations crossed Economic Threshold Level
		Whitefly		Leaf hopper		Thrips
		Numbers	Percent	Numbers	Percent	Numbers	Percent
2022	1317	585	44.42	242	18.38	29	2.20
2021	1220	84	6.89	113	9.26	152	12.46
2020	1622	380	23.43	79	4.87	153	9.43
2019	2125	73	3.44	72	3.39	127	5.98
2018	2485	54	2.17	92	3.70	75	3.02
2017	1956	125	6.39	82	4.19	79	4.04
2016	2335	132	5.65	55	2.36	25	1.07
2015	1089	620	56.93	-	-	-

In North zone, sowing is completed by 15th May (20th SMW) and generally incidence of insect starts after one month of sowing (23rd SMW onwards). The weather factors in general always have an impact on the activity of insect pests but whitefly specifically has interactions with multiple facors. Single favourable factor may help in initiation of incidence but more than one weather factors alongwith the agronomical issue especially crop age and stage supports prolifieration of the pest. A single location data of the zone has been correlated with the weather parameters where minimum temperature and relative humidity (evening) has more influence on the activity of the pest being correlated positively. Rainfall does have a negative impact on the activity of pest but it always require higher intensity rainfall which helps in dislodgement of the whitefly nymphs resulting into life cycle break (Table 5; Raw data presented in Supplementary Table 2 to 12).

Table 5

**Correlation coefficient between Whitefly and prevailing weather conditions at ICAR-CICR, Sirsa location** * Significant at 5% level of significance (p < 0.05), ** Significant at 1% level of significance (p < 0.01).
Year	Temperature (⁰C)		Humidity ( RH%)		Rainfall(mm)
Year	T max	Tmin	RH (M)	RH (E)	Rainfall(mm)
2012	-0.46	-0.66**	0.31	0.12	0.25
2013	0.16	0.44	0.25	0.16	0.02
2014	-0.46**	-0.01	0.62**	0.61**	0.38
2015	-0.46	0.39	0.32	0.63*	0.03
2016	-0.22	0.54*	0.50*	0.63**	0.17
2017	-0.20	0.48*	0.47*	0.56*	0.25
2018	0.16	0.52*	0.24	0.60**	0.19
2019	-0.48*	-0.41	0.54*	0.63**	0.30
2020	-0.28	-0.06	0.29	0.09	0.13
2021	-0.41	-0.08	0.56*	0.69*	-0.16
2022	0.04	0.46*	0.31	0.63**	0.45

* Significant at 5% level of significance (p<0.05), ** Significant at 1% level of significance (p<0.01).

Whitefly populations are mainly regulated by climatic factors such as temperature, rainfall, and humidity in general. Both high temperature and humidity correlates positively with whitefly population build-up (Pathania et al. 2020).The data recorded under unprotected conditions for eleven years indicate minimum temperature and relative humidity during evening exhibited positive correlation during majority of the years under study.Whereas moderate precipitation and high temperatures are generally favourable for B. tabaci leading to its population increases. Particularly,conditions with dry and hot climates with installed irrigation systems are favourable for B. tabaci. Considering their short generation time, large populations can develop in summer to migrate from other alternate hosts to the kharif season crop especially the cotton in North India ²⁰.The first outbreak of whitefly in cotton was reported in the late 1920s and early 1930s in Northern India ¹³⁷. Specifically in India whitefly occurrence and outbreak in all cotton growing zones ( Fig − 1) were reported mainly in Punjab- North zone (1930-43), Andhra Pradesh- South Zone (1984-87), Tamilnadu -South zone), Maharashtra -Central zone and Karnatka-South zone (1985-87), Gujarat- Central zone (1986-87), Haryana, Punjab and Rajasthan- North zone (2015 & 2022).

North cotton growing zone of India cultivated cotton in 18.0 lakh ha in 2020, 17.06 lakh ha in 2021 and 16.65 lakh ha during 2022 under irrigated condition and experienced two whitefly outbreaks. During the 2015, a serious outbreak of whitefly incidence was recorded during August onwards in the cotton growing areas of North zone (Haryana, Punjab and Rajasthan) leading to a heavy loss in crops ¹². The outbreak recorded during 2022 was advanced to July as compared to August in 2015 outbreak where in severity was more during August (Fig. 2; Raw data presented in Supplementary Table 1). The pest remained above ETL for a longer durations during 2022 (≥ 10SMW) as comaperd to 2015 (population stayed above ETL for 6 SMW only).The lowest North zone productivity (358.55 kg lint/ha) was reported during 2015 whereas zonal productivity during 2022 was 482.83 kg lint/ha more than 2015 because the outbreak of whitefly was restricted to few blocks of the zone during 2022 and was not observed uniformly across the zone.

4.1 Factors for Outbreak or Resurgence: Factors responsible for outbreak were categorized as agronomical, climatic and insecticide induced hormoligosis and their mixtures ¹⁰⁸ .Among cultural factors, sowing beyond recommended date either late or early has become very common practice. In North Zone cotton growing states of India, the normal recommended sowing time is from 15th April to 15th May of the year. However, based on the availability of canal water and cropping system i.e. cotton-wheat or cotton- mustard, the sowing window has been widened year after year. During 2022 sowing commenced from 25th March and continued till first week of June (> 60days sowing window) helped in whitefly proliferation creating sequential niche for the multiplication of the pest where eventually late sown cotton crop was adversely affected. Cotton is highly nutrient intensive crop and requires a balanced nutrition. However, imbalanced fertilizer application, either excessive use of nitrogenous fertilizers or under nutrition in the fear of whitefly and poor or improper application of phosphatic or potassic fertilizers is very common. Availability of alternative potential hosts during the season and off-season create favorable niche for this pest. Collateral host’s further support in build-up and subsequent outbreak especially summer moong in Punjab during 2022 was one of the major factors.

The region witnessed interspecific competition among sucking pests but the dominance of whitefly has well been proved and outbreak of these pests has been observed at frequent intervals ¹² .Whitefly is known to have about eleven generations during cotton growing season (April-October) in North zone and any development with respect to insecticide reaction in the form of resistance can easily be passed on to the next generation. The introduction of ‘synthetic pyrethroids in 1981 acted as initial trigger for whitefly upserge. Usage of some insecticides and their sub-lethal dosages are responsible for hormoligosis. Earlier experiments proved that acephate when sprayed four times at fortnight intervals led to heavy damage from whiteflies leading to plant death in the form resurgence ¹⁰. Tank-mix of pyrethroid + acephate more frequently used in north India led to quick surge in whiteflies resulting in outbreaks. Another insectide, Fipronil recently was found to cause whitefly resurgence in north India ¹¹. Faulty methods of insecticide applications add to the further development of resistance in whitefly against insecticides.The natural enemies are generally more susceptible to insecticides than insect pests. Predators (coccinellids, chrysopids & soiders) as well as parasites are generally present every where in the plant and more vulnerable to be exposed to insecticides. Insect pests become resistant quickly to insecticides whereas natural enemies due to their sensitivity towards insecticides take a longer time for resistance development. The destruction of natural enemies due to continuous insecticide applications even at sub lethal doses also hamper the activity of these generalist whitefly population regulators. Insecticide resistance is among the major factors responsible for outbreak of whitefly in 2015. Besides,there are very few effective insecticides available against whitefly. This has resulted in excessive and indiscriminate insecticide sprays that disrupted ecosystems, which led to severe whitefly outbreaks and further development of resistance. Insecticide resistance monitoring carried out by ICAR- Central Institute for Cotton Research (Rishi et al. unpublished ) showed a high level of insecticide resistance to neonicotinoids (acetamiprid & thiamethoxam) and organophosphate (triazophos & acephate) in use. Even some of the new generation insecticides used very frequently are at risk e.g.diafenthiuron, flonicamid etc. Among climatic factors, during 2015, rainfall of less than 100 mm up to July coupled with cloudy conditions leading to high humidity created conducive weather for the insect pest. Each factor favored whitefly proliferations. Due to favorable weather during 2022, second time after 2015, the whitefly has become a major limiting factor for cotton in North zone of India. Weather in general was drier with low rainfall, lower humidity and higher day and night temperatures. The crop was under stress at many locations due to the prevailing dry weather conditions.

A severe outbreak of whitefly was experienced in 2015 in North India on cotton followed by the outbreak during 2022 cotton season comparatively with higher seasonal mean of whitefly adults/ 3leaves during the 2022 cotton season. The incidence of pest initiated earlier in cotton and continued to survive and thrive above ETL for a longer duration as compared to 2015 outbreak.More number of locations above ETL during 2015 as compared to 2022 at farmers field ,indicated severity of 2022 outbreak was higher but it was only in few blocks unlike 2015 outbreak, which occurred in entire North zone. Factors for advancement in infestation and higher severity of whitefly in the north zone during 2022 compared to the past few years point towards availability of alternate hosts, susceptible genotypes and other seasonal agronomic factors.

6. AUTHOR’S CONTRIBUTION

RK : Conceptualization of the experiments, RK, SKS, SS, SP, RS, AJ, JK : Conduct of the experiments, RK and DP: Data analysis and Interpretation of the results, RK, SKS, YGP, AHP, SP and DP: Preparation of the Manuscript, Editing and Proofreading.

7. ACKNOWLEDGEMENT

The work was condcuted under All India Coordinated Resaerch Project on Cotton. The facilties and funding provided by Project Coordinator & Head, AICRP on Cotton and Director ICAR-CICR, Nagpur is highly acknowledged.

8. DECLARATION OF COMPETING INTERESTS: Authors declare no conflicts of interest

9. DATA AVAILABILITY STATEMENT: All data generated or analysed during this study are included in this article and its supplementary information files.

10. PLANT GUIDELINE STATEMENT: Experimental research and field studies on plants (either cultivated or wild) was as per the relevant institutional guidelines and legislation of ICAR-CICR, Nagpur, Maharashtra, India. No leave samples were collected and the data was taken from standing crop of farmers’ field locations in Hisar& Sirsa (Haryana), Bathinda & Faridkot (Punjab) and Sriganganagar (Rajasthan) with prior permission.

The authors also confirmed that no live animal/parts of the animal have used in the study.

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No competing interests reported.

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North cotton growing zone of India witnessed another whitefly outbreak within a decade

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