Impact of Predators and Some Commercial Insecticides on Thrips tabaci Lindeman and Amrasca biguttula Ishida Populations in Bt Cotton under Arid Climate

Azhar Abbas Khan*, Humaira Kanwal, Sumair Batool, Zeshan Hassan, Jawad Munawar Shah, Hafiz Muhammad Aatif, Ahmad Nawaz, Hasan Taha and Yasir Ishfaq

College of Agriculture, Bahauddin Zakariya University, Bahadur Campus Layyah-31200, Pakistan.

ABSTRACT

Insect pests and their vectored diseases are the most common factors which cause severe damage to the cotton crop. In this two year study, the effectiveness of Commando plus®, Oshin®, Talstar®, Radiant®, Movento® and Maximal® was evaluated against Thrips tabaci, Amrasca biguttula and their impact on bio-control agents in Bt cotton. More reduction in T. tabaci was observed with Radiant® and Talstar® for both years at the first application as compared to other treatments through 9 days after treatment. The second application of treatments also showed minimal differences from first application and again plots treated with Radiant® showed the best reduction in thrips population for both years. Generally, Radiant® found friendly toward predators as compared to other chemistries. The findings for tested chemicals showed that bio-based insecticides i.e. spinetoram (Radiant®) and nitenpyram (Maximal®) showed less impact on natural enemies in addition to suppression of T. tabaci and A. bigutulla.

Article Information

Received 12 May 2020

Revised 23 June 2020

Accepted 20 July 2020

Available online 14 January 2021

(early access)

Published 19 November 2021

Authors’ Contribution

AAK conceived the experiments and wrote the manuscript. HK, SB and HT performed the experiment. JMS and ZH helped in writing manuscript and data analysis. AN, HMA and YI edited manuscript.

Key words

Cotton, Insect pests, Predators, Insecticides resistance, Economy

DOI: https://dx.doi.org/10.17582/journal.pjz/20200512190543

* Corresponding author: [email protected]

0030-9923/2022/0001-0137 $ 9.00/0

Copyright 2022 Zoological Society of Pakistan

INTRODUCTION

Insect pests are the most common factors which cause severe damages to field crops (37% reduction), additionally, viruses and pathogens can cause an 11% loss if they are kept untreated (Oerke and Dehne, 2004). Surveys indicate that a massive loss of cotton produce (up to 70%) may occur due to insect pest’s infestation in the absence of any compatible control measure (Rehman et al., 2017). Many insect pests including whitefly, mealybug, jassid, dusky cotton bug, and many lepidopterans are responsible for decreasing the profit and output of cotton crops. About 18.78% less has been observed in cotton yield due to infestation of jassid (Ali, 1992). Huge yield losses (40-50%) to cotton crops have also been recorded during a severe attack of thrips and jassid in cotton field plots (Naqvi, 1976). If these insects are not managed properly, they may cause damages to cotton from cotyledon to fiber formation. Farmers can reduce insect pests damage by the integration of different methods including chemical, biological, cultural, and agronomic practices (Abrantes et al., 1978; Francis and Clegg, 1990).

By killing certain insect pests, Bt toxin can be helpful in minimizing the use of chemical insecticides (Wu et al., 2008). The midgut of pests is disrupted by Bt toxin at target places which finally kills the insect (Morin et al., 2003). Due to potentially high yield with low insect pest incidence, Bt cotton is grown over several million hectares. However, over time, many insect pests have developed resistance against Bt toxin which decreases its efficiency (Ferré and Rie, 2002; Tabashnik et al., 2003, 2013). Moreover, Bt toxin helps control chewing insects especially the lepidopterans. Therefore, attention must be paid to manage a variety of sucking insect pests of cotton, for instance, jassids and thrips, which show 20-40% level of resistance against chemical insecticides (Smith, 2016). Insect pest’s infestation is the major reason for huge losses in the production which could be up to 70% in the absence of pest control measures (Rehman et al., 2017).

The integration of different pest control strategies including the use of biocontrol agents is the best choice for farmers to keep damages below the threshold level. The proper use of biological control results in limited chemical applications and a way to conserve bio-control agents in the agro-ecosystem. Also, these friendly insecticides ensure chemical free safe crop production (James, 2014).

The presence of a wide range of generalist predators has been reported in cotton field crops, which suppress the pest population in addition to the crop pollination facilitation (Isaacs et al., 2009). Most important predators found in cotton crop includes Chrysopperla carnea, Coccinella septempunctata, Geocoris spp., Menochilus sexmaculatus, parasitoids Trichogramma spp., Apanteles spp. and predatory spiders. C. carnea have excessive potential for the natural control of thrips (Khan et al., 2012; Rashid et al., 2012; Solangi et al., 2013; Sarwar, 2014). Certain predatory thrips are useful in decreasing the population of thrips. The predators of thrips include members of Anthocoridae, Lygaeidae, and mites. But their role in controlling thrips is limited, although there is no biological control of jassid due to its activity, but mites can control jassid to some extent and C. carnea is more effective for thrips (Zia et al., 2008).

The fluctuating scenario of spatiotemporal status of cotton requires alternate methods for pest control. Manipulation in cropping patterns of cotton, trap crops, crop rotation, and conservation tillage may limit the use of chemical insecticides. These practices also provide a space for the beneficial insects and farmer-friendly natural enemies of insect pests in cotton crops. However, integration of these practices with other applied solutions for pest management may also provide safer and effective pest control (Mari et al., 2007).

MATERIALS AND METHODS

Experimental layout plan and field preparation

Current research was conducted for two years consecutively during the summer season of 2017 and 2018 at the research farm of BZU, Bahadur Sub Campus Layyah (30° 57’ 53.1000’’ N and 70° 56’ 23.7624’’ E). The Bt cotton (FH-142) was sown on an area of 1012 m2, further divided into 49 plots for seven treatments, with four replications for each treatment. The sowing was done on ridges through a hand-operated mini drill, keeping a distance of R×R 30 cm and P×P 75cm. A buffer zone of one meter was kept in between each treatment and two meters for each replication and walking path and water channels were adjusted in buffer zones. The experiment was made under Randomized Complete Block Design (RCBD). Irrigation was done every week or depending upon the soil condition and crop requirement. Fertilizer applications were made as recommended commercially and were applied in split doses i.e. at sowing, vegetative and flowering stage.

Field application of treatments

Before insecticides application (Table I), it was confirmed that the pest population (Thrips tabaci and Amrasca biguttula) reaches to economic injury level in each plot. Natural enemies (predatory spider and C. carnea) were observed twice a week pre and post-treatments. All the treatments were applied by using a hand-operated Knap Sack sprayer, which was calibrated before treatment application with a Turbo T-jet wide-angle spray tip nozzle. Treatments were applied three times in 2017 (10 July, 12 August) and 2018 (20 July, 22 August), while control plots were left untreated.

Data collection/sampling and analysis

Insect pest infestation appeared at the vegetative stage; the data regarding pests and bio-control agents was recorded. Five plants were selected for data collection from each plot. The richness of T. tabaci, A. bigutulla, lacewing, and spiders were observed by hand lens and visually examining leaves pre-treatment (24 h), post-treatment (24 h), 3, 6, and 9 days after treatment (DAT) of the last insecticide application until almost all the insects on each examined plant were observed.

The data for both years were analyzed separately. The normality of collected data was confirmed through the Kolmogorov-Simonov test. Analysis of variance (one-way) followed by Tukey’s test was used to discern the mean densities of tested arthropods among the experimental field plots for different treatments. The statistical package (Statistic 8.1®) was used for analyses of whole data.

 

Table I. List of synthetic chemical insecticides and their application rate used in the experimental field plots.

Treatments	Active ingredient	Chemical group	Brand name	Application rate	Company name
T1	Acephate	Organophosphate	Commando plus®	300gm/ac	FMC
T2	Necotinoid	Neonicotinoid	Oshin®	100gm/ac	Arysta life Sciences
T3	Bifenthrin	Pyrethroid	Talstar®	250ml/ac	FMC
T4	Spinetoram	Miscellaneous	Radiant®	100ml/ac	Dow Agrosciences
T5	Spirotetramate	Miscellaneous	Movento®	80ml/ac	Bayer crop science
T6	Nitenpyram	Miscellaneous	Maximal®	120gm/ac	FMC
T7	Control	----	untreated	----	----

 

Note: Commercially recommended insecticide dozes were used in experiment.

RESULTS

There was no significant difference in the T. tabaci population for both years (2017 and 2018) before the application of any chemicals. All treatments provided a significant reduction in T. tabaci for both years compared to control 9 DAT except Talstar® 24h post-treatment (df = 6, F = 0.87, P = 0.5102) at the first application in the year 2018. However, Radiant® through 6 DAT (df = 6, F = 8.29, P ≤0.05) at first application and at 9 DAT (df = 6, F = 4.04, P = 0.0028) showed most significant difference among all the treatments at first application in 2018. More reduction in T. tabaci was observed with Radiant®, Talstar®, and Movento® at the first and second applications as compared to other treatments through 9 DAT during both years 2017 and 2018. The lowest population of T. tabaci post-treatment was found in Radiant® treated plots, followed by Movento® and Talstar® treated plots (Table II).

All treatments provided a significant reduction in the population of A. bigutulla post-treatment application of different insecticides, 9 DAT for both the years (2017 and 2018). However, Radiant® and Talstar® showed a maximum mortality of A. biguttula. The same trend was recorded for the proceeding year 2018 (Table III).

The preliminary analysis showed similar trend of predator’s densities during 2017 and 2018, therefore data of both years were pooled. Most of the chemicals showed adverse effects toward C. carnea and Lycosids, more drastically than the Radiant® followed by Talstar®. Overall, there was a significant difference between densities of C. carnea (F = 6.09, P ≤0.05, df = 6), Lycosids (F = 6.45, P ≤0.05, df = 6) between treated and untreated plots. However, the post-hoc tests revealed that the fluctuation of the predator’s densities was due to varying effects of chemical insecticides (Figs. 1 and 2).

The results regarding correlation between abiotic factors, predators (C. carnea and Lycosidae spp.), and insect pests (A. biguttula and T. tabaci) in the Bt cotton field plots are positively correlated and in a few cases, it was negative i.e. A. bigutulla with C. carnea and T. tabaci with Lycosids. This negative correlation between pests and predators is a good sign for biocontrol agents (Table IV).

DISCUSSION

A wide range of systemic pesticides are being utilized by cotton producers against sucking insect pests, but they are less useful, most probably because of field evolved resistance in these pests against most widely used synthetic conventional insecticides (Luttrell et al., 2015).

 

Table II. Effect of synthetic commercial insecticides on number (Mean±SEM) of T. tabaci per leaf on cotton field crop plants during 2017 and 2018. The data recorded pre-24 h, post-24 h and 3, 6, 9 days after treatment (DAT).

Treatments	Pre-24h		24h		3 DAT		6 DAT		9 DAT
	2017	2018	2017	2018	2017	2018	2017	2018	2017	2018
First Application (July 10, 2017 and July 20, 2018)
Control	3.63±0.15a	2.56±0.25a	7.04±1.42a	4.18±0.68a	4.75±0.36a	2.01±0.27a	3.08±1.02a	2.62±0.1a	4.22±0.88a	3.51±0.32a
Commando plus®	3.10±0.09a	2.92±0.37a	1.95±0.36b	1.22±0.22c	0.75±0.31b	1.03±0.16b	0.88±0.20b	0.92±0.06b	0.81±0.18b	1.00±0.06bc
Oshin®	2.99±0.09a	3.03±0.23a	1.56±0.77b	1.68±0.47c	0.96±0.44b	1.03±0.15b	1.00±0.32b	0.87±0.11b	0.87±0.22b	1.04±0.14bc
Talstar®	3.33±0.10a	3.64±0.18a	1.90±0.57b	2.93±1.00b	1.37±0.52b	1.29±0.11b	0.68±023b	1.00±0.02b	0.81±0.35b	0.96±0.20c
Radiant®	3.17±0.10a	2.99±0.46a	2.43±0.47b	1.31±0.24c	1.06±0.30b	0.58±0.09c	0.80±0.40b	0.36±0.07c	0.62±0.26b	0.67±0.28c
Movento®	3.38±0.12a	2.98±0.36a	1.97±0.50b	1.07±0.39c	0.95±0.26b	0.83±0.23b	0.87±0.58b	1.02±0.05b	1.31±0.36b	0.88±0.21c
Maximal ®	2.90±0.09a	2.84±0.31a	2.15±0.40b	2.06±0.27bc	0.97±0.36b	1.65±0.27ab	0.65±0.30b	1.17±0.04b	1.20±0.26b	1.34±0.14b
Second Application (August 12, 2017 & August 22, 2018)
Control	3.60±0.45a	2.84±0.31b	3.81±0.29a	3.37±0.34a	2.01±0.24a	3.56±0.38a	3.20±0.35a	2.68±0.43a	3.43±0.30a	3.10±0.20a
Commando plus®	2.94±0.31a	2.82±0.35b	1.87±0.29c	1.47±0.11b	1.03±0.23b	1.12±0.06b	0.87±0.12b	0.96±0.16c	0.55±0.10cd	1.00±0.27c
Oshin®	3.21±0.14a	2.63±0.41b	2.13±0.47c	1.55±0.17b	0.87±0.21b	1.22±0.12b	1.00±0.04b	1.34±0.14b	0.77±0.12cd	1.05±0.45b
Talstar®	3.71±0.29a	2.48±0.48b	2.96±0.42ab	1.39±0.10b	1.02±0.09b	0.93±0.07c	0.83±0.17ab	1.06±0.20bc	0.94±0.14c	0.98±0.27b
Radiant®	3.53±0.13a	3.02±0.46b	2.11±0.43c	1.45±0.12b	0.68±0.18bc	0.92±0.10c	0.61±0.13c	0.77±0.08c	0.32±0.10d	0.42±0.07c
Movento®	3.62±0.30a	4.56±0.29a	0.66±0.49d	1.39±0.07b	1.75±0.26a	1.20±0.08b	1.37±0.27ab	1.19±0.31b	2.06±0.19b	1.33±0.16b
Maximal ®	3.56±0.25a	3.53±0.16ab	3.34±0.36a	1.38±0.13b	0.81±0.23b	1.22±0.07b	1.27±0.28ab	1.51±0.22b	1.43±0.45b	1.08±0.28b

 

Note: Values in columns having same superscript are non-significant at P≤0.05

 

Table III. Effect of synthetic commercial insecticides number (Mean±SEM) of A. bigutulla per leaf on cotton field crop plants during 2017 and 2018. The data recorded pre-24 h, post-24 h and 3, 6, 9 days after treatment (DAT).

Treatments	Pre-24h		24h		3 DAT		6 DAT		9 DAT
	2017	2018	2017	2018	2017	2018	2017	2018	2017	2018
First application (July 10, 2017 & July 20, 2018)
Control	2.95±0.10a	3.56±0.25a	3.01±0.27a	4.18±0.68a	3.10±0.20a	4.01±0.27a	2.56±0.30a	2.22±0.17a	2.74±0.15a	3.21±0.2a
Commando plus®	2.09±0.17b	1.92±0.37b	1.13±0.17b	1.22±0.22c	1.20±0.27c	0.93±0.07c	1.07±0.27b	1.02±0.06b	1.32±0.23b	1.16±0.16c
Oshin®	2.05±0.74b	3.03±0.83a	1.03±0.13b	2.68±0.47b	2.25±0.45b	1.03±0.33b	1.50±0.25b	0.99±0.10b	1.13±0.05b	2.34±0.14b
Talstar®	2.00±0.58b	3.64±0.44a	1.29±0.11b	0.93±0.50d	0.72±0.27d	0.29±0.11d	0.27±0.06c	0.42±0.06c	0.34±0.14c	0.56±0.20d
Radiant®	2.35±0.35b	4.02±1.46a	1.18±0.09b	1.31±0.24c	0.20±0.03e	0.28±0.12d	0.00±0.00d	0.22±0.02d	0.12±0.01d	0.00±0.00e
Movento®	2.14±0.42b	2.98±0.96a	0.43±0.13c	0.97±0.29d	0.33±0.16e	0.43±0.23d	1.09±0.25b	0.56±0.08c	1.00±0.16b	1.19±0.31c
Maximal ®	2.11±0.27b	2.84±0.71a	1.10±0.06b	2.06±0.77b	2.01±0.27b	1.65±0.27b	1.12±0.47b	1.27±0.26b	1.13±0.35b	1.32±0.22c
Second application (August 12, 2017 and August 22, 2018)
Control	3.04±0.28a	3.78±0.27a	2.56±0.15a	3.37±0.34a	2.84±0.29a	3.56±0.38a	2.94±0.37a	2.68±0.43 a	3.03±0.25a	3.10±0.20a
Commando plus®	2.33±0.33a	1.29±0.24b	1.13±0.07c	1.47±0.11b	1.37±0.15b	1.12±0.06b	1.46±0.23b	1.46±0.16b	1.81±0.29b	2±0.27b
Oshin®	1.83±0.15b	3.14±0.54a	1.05±0.03c	1.55±0.17b	1.50±0.25b	1.22±0.12b	1.13±0.05b	1.34±0.14b	1.95±0.19b	2.25±0.45b
Talstar®	0.99±0.12c	1.00±0.42b	1.12±0.11c	0.81±0.10c	0.27±0.06c	1.03±0.07b	0.54±0.14c	0.54±0.20c	0.43±0.19c	0.72±0.27c
Radiant®	0.32±0.03d	0.50±0.04c	0.00±0.00e	0.00±0.00e	0.03±0.01d	0.00±0.00d	0.12±0.10d	0.00±0.00d	0.36±0.12c	0.05±0.03d
Movento®	1.67±0.16b	1.19±0.42b	0.62±0.22d	0.39±0.07d	0.89±0.25c	0.41±0.08c	0.90±0.16c	0.29±0.11c	0.36±0.08c	0.33±0.10c
Maximal ®	2.10±0.85a	1.63±0.12b	2.01±0.27b	1.38±0.13b	2.56±0.30a	1.12±0.07b	1.74±0.15b	1.51±0.22b	1.81±0.28b	2.08±0.28b

 

Note: Values in columns having same superscript are non-significant at P≥0.05.

 

Table IV. Correlation matrix of insect pests, natural enemies and abiotic factors during cropping season of year 2017.

	Temperature	C. carnea	RHo	A. bigutulla	Lycosids
C. carnea	-0.0723
P =	0.8327
RHo	-0.8179	0.3045
P =	0.0021	0.3625
A. bigutulla	-0.3857	-0.0877	0.2335
P =	0.2414	0.7976	0.4896
Lycosid	0.0316	-0.0307	0.0045	0.0803
P =	0.9265	0.9286	0.9895	0.8144
T. tabaci	-0.3259	0.3997	0.5487	0.0647	-0.5706
P =	0.3281	0.2233	0.0805	0.8501	0.0668

 

Moreover, environmental contamination and non-target effects on beneficial fauna, including insect predators (ants, coccinellid beetles and green lacewings) and parasitoids (wasps), are other contemporary issues of these irrationally used broad-spectrum insecticides (Simon-Delso et al., 2015). Therefore, there is a need to evaluate and screen out more target-specific pesticide formulations against sucking insect pests which would be relatively safer for insect natural enemies. It is likewise important to lessen the utilization of synthetic chemicals and to improve the utilization of natural control because new chemical insecticides are unsafe for bio-control agents (Raees et al., 2017). Recently, Haider et al. (2017) proposed that biological control is eco-friendly control of insect pests than the use of synthetic pesticides. Along these lines, there is a need to lessen the utilization of synthetic concoctions to keep the environment safe and to save the number of inhabitant’s natural enemies (Huang et al., 2018). The current study was directed to assess the efficacy of some new chemical insecticides (Radiant®, Movento® and Maximal®) and conventional insecticide formulations (Talstar®, Commando Plus® and Oshin®) against the above-mentioned sucking insect pest and their natural enemies under field conditions.

Current results showed that all used insecticides provided a significant reduction in thrips and jassids population as compared to untreated control plants indicating that they all were very useful in reducing sucking insect pests’ populations. However, the exception

 

 

of reduced effectiveness of the treatments was observed and Radiant® showed the most significant differences among all the treatments through 6 DAT and 9 DAT at first application in 2018. All treatments significantly reduced T. tabaci for both years compared to control through 9 DAT except Talstar®, 24h post-treatment, which might be due to the environmental factor and due to the growth stage at which treatment was applied. Radiant® showed the most significant differences among all the treatments through 6 DAT and at 9 DAT at first application in 2018. More reduction was observed in T. tabaci with Radiant®, Talstar®, and Movento® at the first and second applications as compared to others through 9 DAT during both years 2017-2018. Talstar® and radiant showed no significant difference among the population of insects after the application of insecticides. The same results were stated by Nault et al. (2012) in the field plots where spinetoram shows low thrips larval population compared to the plots treated with spirotetramat.

In the experimental results of 2018, the maximum mortality was recorded in plots treated with Radiant® after 24h (0.91, 1.31) to 9 DAT (0.81, 2.00) respectively. Dripps et al. (2008) and Sparks et al. (2008) described that spinetoram is a semi-synthetic active ingredient demonstrating the spinosyn chemical class of insecticides. This molecule has demonstrated higher levels of efficacy compared to that of spinosad against lepidopterous pests, thrips, and leaf miners in a broad range of horticultural and crops. Waters and Walsh (2010) found that spinetoram was effective against onion thrips; however, only spirotetramat provided adequate control of thrips. Subramanian et al. (2010) evaluated the efficacy of chemical insecticides and botanicals against thrips and reported that all tested synthetic insecticides and botanicals were effective. All treatments provided significant mortality in the A. bigutulla population post-treatment of different insecticides through 9 DAT for the both years (2017 and 2018). However, Radiant® and Talstar® showed a maximum mortality of A. biguttula. These results are similar to those who reported that acephate was efficient control against jassid (Stefanov and Dimetrov, 1986). These results also support the discoveries that acephate was found the most effective against sucking pests (Wahla et al., 1997).

Chemical control is one of the quick strategies and takes a vital role in IPM strategy to decrease the pest of cotton crop (Gogi et al., 2006). In the present study, we noticed better results of these pesticides against all insects. It was observed that transgenic cultivars were attacked by the sucking complex particularly jassids which were observed on the cotton crop (Zia et al., 2013). Regarding the effect of insecticides on non-target insect species, most of the insecticide formulations tested caused more than 50% reduction of all beneficial insect fauna. However Radiant was more friendly towards all biocontrol agents under the current study. This is not in agreement with the results of a recent study done by Sarwar (2014) which reported no significant effect of endosulfan 35% EC and monocrotophos 36% SL on cotton insect pests and natural enemies complex. Many new insect growth regulators such as pyriproxyfen and buprofezin have been demonstrated as very target specific and with least residual effects on non-target species of insect predators and regulators (Naranjo et al., 2004; Messelink et al., 2014).

Results with regard to the correlation of natural enemies and abiotic factors demonstrated that there was a correlation among all insects including natural enemies of insect pests with abiotic factors. The above conclusions regarding green lacewing and predatory spiders were in conformity with those of Boda and Ilyas (2017). Mahmood et al. (1990) showed that low temperature was associated with the pest population. Moreover, humidity, temperature, and rainwater effect the thrips and leafhopper population. Thrips are less incredible and adversely associated with an increase in the temperature. Thrips decrease their activities in hot condition since temperature variance impacts the thrips population.

CONCLUSIONS

For keeping the populations of T. tabaci and A. bigutulla under check, the repeated use of insecticides during the vegetative stage of cotton is of much importance. However, to safeguard the environment and farmer’s friendly arthropods, the use of safe chemicals is needed. The findings for tested chemicals showed that bio-based insecticides i.e. spinetoram (Radiant®) and nitenpyram (Maximal®) showed less impact on natural enemies in addition to suppression of T. tabaci and A. bigutulla. These milder new insecticides may be more suitable for integrated pest management programs and for habitats where conventional insecticides are not allowed or appropriate such as organic farming and urban peri-urban areas. The evidence of pests’ resistance to some commonly used broad-spectrum insecticides including neonicotinoid and acephate also indicate the need for reduced use of strong chemical insecticides and their integration with other milder chemicals.

Statement of conflict of interest

The authors have declared no conflict of interest.

References

Abrantes, I., Morais, M., Susana, M. and Santos, 1978. Nemátodos plants hospedeiras identificados em Coimbra, Portugal, durante 1972-1977. Cicnc Biol. (Purtagal), 4: 23-44.

Ali, A., 1992. Physio-chemical factors affecting resistance in cotton against jassid, Amrasca devastans (Dist.) and thrips, Thrips tabaci (Lind.) in Punjab, Pakistan. Ph. D Dissert. Dept. Entomol. Univ. Agric. Faisalabad, Pakistan, pp. 430.

Boda, V. and Ilyas, M., 2017. Population dynamics of predatory insects in cotton ecosystem and their correlation with abiotic factors. Bull. environ. Pharmacol. Life Sci., 6: 164-166.

Dripps, J., Olson, B., Sparks, T. and Crouse, G., 2008. Spinetoram: how artificial intelligence combined natural fermentation with synthetic chemistry to produce a new spinosyn insecticide. Pl. Hlth. Prog. Web page: http://www.plantmanagementnetwork.org/pub/php/perspective/2008/spinetoram/).

Ferré, J. and Rie, J.V., 2002. Biochemistry and genetics of insect resistance to Bacillus thuringiensis. Annu. Rev. Ent., 47: 501-533. https://doi.org/10.1146/annurev.ento.47.091201.145234

Francis, C. and Clegg, M., 1990. Crop rotations in sustainable production systems. Sust. Agric. Sys., pp. 107-122.

Gogi, M.D., Sarfraz, R.M., Dosdall, L.M., Arif, M.J., Keddie, A.B. and Ashfaq, M., 2006. Effectiveness of two insect growth regulators against Bemisia tabaci (Gennadius) (Homoptera: Aleyrodidae) and Helicoverpa armigera (Hübner) (Lepidoptera: Noctuidae) and their impact on population densities of arthropod predators in cotton in Pakistan. Pest Manage. Sci., 62: 982-990. https://doi.org/10.1002/ps.1273

Haider, I., Suhail, A. and Aziz, A., 2017. Toxicity of some insecticides against cotton jassid (Amrasca devastans Dist.) and its predator (Chrysoperla carnea Steph). J. agric. Res., 55: 311-321.

Huang, J., Zhou, K., Deng, X.Y., Werf, W.V.Z., Lu, Y., Wu, K. and Rosegrant, M., 2018. Uncovering the economic value of natural enemies and true costs of chemical insecticides to cotton farmers in China. Environ. Res. Lett., 13: 064027. http://iopscience.iop.org/article/10.1088/1748-9326/aabfb0/meta. https://doi.org/10.1088/1748-9326/aabfb0

Isaacs, R., Tuell, J., Fiedler, A., Gardiner, M. and Landis, D., 2009. Maximizing arthropod mediated ecosystem services in agricultural landscapes: the role of native plants. Front. Ecol. Environ., 7: 196-203. https://doi.org/10.1890/080035

James, C., 2014. Global status of commercialized biotech/GM crops: ISAAA brief no. 49. Int. Serv. Acqui.s Agric. Biotech. App.

Khan, H.A.A., Sayyed, A.H., Akram, W., Razald, S. and Ali, M., 2012. Predatory potential of Chrysoperla carnea and Cryptolaemus montrouzieri larvae on different stages of the mealybug, Phenacoccus solenopsis: A threat to cotton in South Asia. J. Insect Sci., 12: 147. https://doi.org/10.1673/031.012.14701

Luttrell, R.G., Teague, T.G. and Brewer, M.J., 2015. Cotton insect pest management. In: Cotton, 2nd ed., Agron. Monogr. 57. ASA, CSSA, and SSSA, Madison, WI, pp. 509-546. https://doi.org/10.2134/agronmonogr57.2014.0072

Mahmood, T., Khokar, K.M., Banaras, M. and Ashraf, M., 1990. Effect of environmental factors on the density of leafhopper, Amrasca devastans (Distant) on okra. Trop. Pest. Manage., 36: 279-284. https://doi.org/10.1080/09670879009371488

Mari, J.M., Nizamani, S.M. and Lohar, K.M., 2007. Population fluctuation of sucking insect pests and predators in cotton ecosystem. Afr. Crop Sci. Conf. Proc., 8: 929-934.

Messelink, G.J., Bennison, J., Alomar, O., Ingegno, B., Tavella, L., Shipp, L., Palevsky, E. and Wäckers, F., 2014. Approaches to conserving natural enemy populations in greenhouse crops: Current methods and future prospects. Biol. Control, 59: 377-393. https://doi.org/10.1007/s10526-014-9579-6

Morin, S., Biggs, R.W., Sisterson, M.S., Shriver, L., Ellers-Kirk, C.D., Higginson, D., Holley, L.J., Gahan, D.G., Heckel and Carriere, Y., 2003. Three cadherin alleles associated with resistance to Bacillus thuringiensis in pink bollworm. Proc. natl. Acad. Sci., 100: 5004-5009. https://doi.org/10.1073/pnas.0831036100

Naqvi, K.M., 1976. Crop protection to boost up cotton production. Seminar organized by ESSO, Fert. Co. Ltd. Pakistan. pp. 74.

Naranjo, S.E., Ellsworth, P.C. and Hagler, J.R., 2004. Conservation of natural enemies in cotton: Role of insect growth regulators in management of Bemisia tabaci. Biol. Control, 30: 52-72. https://doi.org/10.1016/j.biocontrol.2003.09.010

Nault, B.A., Hsua, C.L. and Hoepting, C.A., 2013. Consequences of co-applying insecticides and fungicides for managing Thrips tabaci (Thysanoptera: Thripidae) on onion. Pest Manage. Sci., 68:841-9. https://doi.org/10.1002/ps.3444

Oerke, E.C. and Dehne, H.W., 2004. Safeguarding production losses in major crops and the role of crop protection. J. Crop Protec., 23: 275-285. https://doi.org/10.1016/j.cropro.2003.10.001

Raees, A., Babar, S., Tanvir, A. and Muhammad, M., 2017. Analysis of sustainable cotton initiative in the Punjab; The impact on insect/pest risk management. J. agric. Res., 55: 197-211.

Rashid, M.M., Khattak, U., Abdullah, M.K., Amir, K., Tariq, M. and Nawaz, S., 2012. Feeding potential of Chrysoperla carnea and Cryptolaemus montrouzieri on cotton mealybug, Phenacoccus solenopsis. J. Anim. Pl. Sci., 2: 639-664.

Rehman, A., Jingdong, L., Chandio, A.A., Hussain, I., Wagan, S.A. and Memon, Q.A., 2016. Economic perspectives of cotton crop in Pakistan: A time series analysis (1970–2015) (Part 1). J. Saudi Soc. agric. Sci., 18: 49-54.

Sarwar, M., 2014. Influence of host plant species on the development, fecundity and population density of pest Tetranychus urticae Koch (Acari: Tetranychidae) and predator Neoseiulus pseudolongispinosus (Xin, Liang and Ke) (Acari: Phytoseiidae). N. Z. J. Crop Hortic. Sci., 42: 10-20. https://doi.org/10.1080/01140671.2013.817444

Simon-Delso, N., Amaral-Rogers, V., Belzunces, L.P., Bonmatin, J.M., Chagnon, M., Downs, C. and Goulson, D., 2015. Systemic insecticides (neonicotinoids and fipronil): Trends, uses, mode of action and metabolites. Environ. Sci. Pollut. Res., 22: 5-34. https://doi.org/10.1007/s11356-014-3470-y

Smith, R., 2016. Three things to know about cotton thrips resistance today. Alabama Cooperative Extension System. Available at: https://www.farmprogress.com/cotton/3-things-know-about-cotton-thrips-resistance-today.

Solangi, A.W., Lanjar, A.G., Baloch, N., Rais, M.U.N. and Khuhro, S.A., 2013. Population, host preference and feeding potential of Chrysoperla carnea (Stephens) on different insect hosts in cotton and mustard crops. Sindh Univ. Res. J. (Sci. Ser.), 45: 213-218.

Sparks, T.C., Crouse, G.D., Dripps, J.E., Anzeveno, P., Martynow, J., DeAmicis, C.V. and Gifford, J., 2008. Neural network-based QSAR and insecticide discovery: spinetoram. J. Comput. Aided Mol. Des., 22: 393-401. https://doi.org/10.1007/s10822-008-9205-8

Stefanov, S.G. and Dimetrov, Y.A., 1986. Effective preparation for the control of thrips and aphids on cotton. Annu. Rev. appl. Ent., 76: 70-75.

Subramanian, S., Muthuswami, M., Krishnan, R., Thangamalar, A. and Indumathi, P., 2010. Bioefficacy of botanicals and insecticides against mulberry thrips, Pseudodentro thrips mori Niwa. Karnataka J. agric. Sci., 23: 47-50.

Tabashnik, B.E., Brévault, T. and Carrière, Y., 2013. Insect resistance to Bt crops: lessons from the first billion acres. Nat. Biotechnol., 31: 510-521. https://doi.org/10.1038/nbt.2597

Tabashnik, B.E., Carrière, Y., Dennehy, T.J., Morin, S., Sisterson, M.S., Roush, R.T., Shelton, A.M. and Zhao, J.Z., 2003. Insect resistance to transgenic Bt crops: Lessons from the laboratory and field. J. econ. Ent., 96: 1031-1038. https://doi.org/10.1093/jee/96.4.1031

Wahla, M.A., Tufail, M. and Iqbal, P., 1997. The comparative effectiveness of different doses of Confidor 200SL and Tamaron 600SL against cotton thrips, Thrips tabaci Lind. on FH-582, cotton. Pakistan Entomol., 19: 8-10.

Waters, T.D. and Walsh, D.B., 2010. Onion thrips control in Washington State. Dept. Entomology, Washington State University, Prosser. http://www.unce.unr.edu/.

Wu, K.M., Lu, Y.H., Feng, H.Q., Jing, Y.Y. and Zhao, J.Z., 2008. Suppression of cotton bollworm in multiple crops in China in areas with Bt toxin–containing cotton. Science, 321: 1676-1678. https://doi.org/10.1126/science.1160550

Zia, K., Hafeez, F., Khan, R.R., Arshad, M. and Ullah, U.N., 2008. Effectiveness of Chrysoperla carnea (Stephens) (Neuroptera: Chrysopidae) on the population of Bemisia tabaci (Genn.) (Homoptera: Aleyrodidae) in different cotton genotypes. J. Agric. Soc. Sci., 4: 112–116.

Zia, K., Hafeez, F., Bashir, M.H., Khan, B.S., Khan, R.S. and Khan, H.A.A., 2013. Severity of cotton whitefly (Bemisia tabaci Genn.) population with special reference to abiotic factors. Pak. J. agric. Sci., 50: 217-222.