Research Article

Response of Sucking Insect Pest Fauna Towards Bt and Non Bt Cotton Genotypes under Varying Climatic Condition

Tamoor Ali1*, Muhammad Hamid Bashir1, Bilal Saeed Khan1, Abdul Ghaffar2, Danish Riaz3, Muhammad Zia ul Haq1, Shoaib Nawaz1, Aneeb Ali1, Iftikhar ul Hassan1, Ikram Ul Haq4, Muhammad Khuram Shahzad1, Usama Saleem5 and Tamsila Nazir2

1Department of Entomology, University of Agriculture, Faisalabad, Pakistan; 2Ayub Agriculture Research Institute, Faisalabad, Pakistan; 3Department of Zoology, Division of Science and Technology, University of Education, Lahore, Pakistan; 4Department of Pest Warning and Quality Control of Pesticides, Punjab, Pakistan; 5Department of Zoology, Government College University, Faisalabad, Pakistan.

Received | July 10, 2021; Accepted | December 28, 2021; Published | December 25, 2021

*Correspondence | Tamoor Ali, Department of Entomology, University of Agriculture, Faisalabad, Pakistan; Email: [email protected]

Citation | Ali, T., Bashir, M.H., Khan, B.S., Ghaffar, A., Riaz, D., Haq, M.Z., Nawaz, S., Ali, A., Hassan, I., Haq, I.U., Shahzad, M.K., Saleem, U., and Nazir, T., 2021. Response of sucking insect pest fauna towards Bt and Non Bt cotton genotypes under varying climatic condition. Journal of Innovative Sciences, 7(2): 304-311.

DOI | https://dx.doi.org/10.17582/journal.jis/2021/7.2.304.311

Keywords | Cotton, Sucking pest fluctuation, Weather impact, Regression model

1. Introduction

About 18 %, agriculture contributes in Gross Domestic Product (GDP). Cotton has 0.8 % share in the economy and 4.5% in the agriculture values of Pakistan. Cotton is an important crop that’s why it is believed as the lifeline of the Pakistan (Anonymous, 2018). Cotton is the world’s most important fibrous crop and it grows in both tropical and sub-tropical areas of universe (Bala et al., 2019). Throughout the year of 2018 and 2019, the cotton production keeps on at 9.861 million bales. Sometime the production of the crop was also affected by meteorological factors. The production of the cotton crop in 2019 remained at the 2373 Ha while the yield was 606 Kgs/Ha. Textile is the major sector of the Pakistan. The exports of the cotton and cotton textile during 2019 from July-March remained at 9771 US Million dollars (Anonymous, 2018). Pakistan is at 4th after US, China and India in case of cotton production (Anonymous, 2018). In between sucking pests of cotton; whitefly, jassid, thrip, recorded as greatest damaging pests (Arif et al., 2006; Ali and Aheer, 2007; Salman et al., 2011). Lint quality and the quality deteriorate and gradually decrease due to the attack of sucking pests (Amin et al., 2008; Shah, 2014). The stats told that during the previous years the whitefly was the major pest of crop which causes damage (Ali et al., 1993; Aheer et al., 1999). Due to this some disease also transferred to the cotton crop (Harrison et al., 1997).

jassid on the other hand, has played a significant influence in the destruction of cotton plants (Gupta et al., 1997; Inee-Gogoi et al., 2000).

For the management of insect pest, the cotton genotype grows in specific condition of climate (Ali and Aheer, 2007; Amin et al., 2008; Yousafi et al., 2013). Additionally, it is seen that different aspects like RH, temperature and precipitation also support in the expansion and fluctuation of cotton’s pest as documented in initial studies (Aheer et al., 1994; Mohapatra, 2008; Akram et al., 2013). The population of jassid increases by the temperature and humidity. (Inee-Gogoi et al., 2000). Ali et al. (1993) explained that temperature disclosed a significant and positive role for jassid population r= 0.297 and precipitation presented adverse and significant effect r= 0.483, while the consequence of RH was non-significant.

In the same way, it is studied that the influence of rainfall, temperature and humidity having fifty percent impact on whitefly, jassid and thrips populace (Arif et al., 2006; Mohapatra, 2008; Akram et al., 2013).

The contemporary study was directed to determine the attraction of sucking pest towards four Bt and one non-Bt cotton genotypes. Furthermore, the effect of temperature, sunshine duration, rainfall and RH also recorded on these genotypes. All this experiment was conducted under unsprayed condition in the region of Faisalabad.

2. Materials and Methods

The research was conducted in the University of Agriculture trials area in Faisalabad, Pakistan in 2018. The climatic condition of the Faisalabad region is very hot during the summer. Investigated the genotypes IUB-2015, MNH-886, FH-142, CEMB-33 and FH 942. FH 942 was the non Bt variety while the other was the Bt varieties. Experiment was designed under randomized complete block design with three replications. Field was divided into 15 plots and dimension of small plot was 6 x 10 ft. R-R and P-P distance remained at 2.5 ft and 30cm, respectively. Seed were sown in start of May by using the dibbling method. Data regarding the whitefly, thrips and jassid was noted on per leaf basis once a week at morning time between the 5:00 am to 6:30 am at lower surface of leaf. The data regarding the meteorological factors was taken from the Crop Physiology Department, University of Agriculture, Faisalabad, Pakistan. R software was used for the analysis of data.

3. Results and Discussion

3.1 Whitefly

The cumulative data showed the average population whitefly was maximum (4.707) was recorded on 12-July 2018 while the lowest population (0.487) was recorded on 11-October 2018 in Figure 2. Different cotton varieties showed different level of population of whitefly. In all varieties of cotton, the maximum population was recorded in July while the lower density was recorded in October in Figure 1.

 

Khanzada et al. (2016) detected that the populace of whitefly was highest in July (24.45±0.15). Temperature and humidity show a vital part in increasing the population of whitefly. Maximum population of whitefly was recorded MNH-886, FH-942, CEMB-33, FH 142 and IUB 2015, respectively in Figure 3.

The relationship of whitefly population showed the FH-142 it displayed the positive relationship

 

 

 

with the least in addition extreme temperature and moisture while the adverse showed with the rainfall, relative humidity and sunshine duration. CEMB-33, IUB-2015, MNH-886 and FH-942 exhibited positive relationship with maximum temperature, minimum temperature while negative exhibited with the moisture, rainfall, relative humidity and sunshine duration in Figure 5. Saleem et al. (2018) conducted a similar study in which it is revealed that the maximum population was recorded on MNH 886 which is the cotton variety and also explained that temperature is directly proportional to temperature while negative response was observed with the relative humidity and rainfall.

 

3.2 Thrips

The cumulative data showed the average population thrips was maximum (4.073 per leaf basis) population was recorded in 12-July while the lowest population (0.253 per leaf basis) was recorded on Aug after that again the population buildup and then in October again the population was at its lower level (0.273 per leaf basis) in Figure 6. Different cotton varieties showed different level of population of thrips. In all varieties of cotton, the maximum population was recorded in July while the lower density was recorded in August and October Figure 5. Maximum population of thrips was recorded CEMB-33, MNH-886, FH-942, FH-142, IUB-2015 respectively in Figure 7. Correlation of thrips population with the abiotic factors displayed that in CEMB-33, FH-142, FH-942, IUB-2015 and MNH-886 had positive relationship with the maximum temperature and the minimum temperature while the other factors including moisture, rainfall, relative humidity and sunshine duration showed the negation link in Figure 8. Khanzada et al. (2016) revealed that the population of thrips was at its peak position (15.60+0.78) in July and meteorological factors temperature and relative humidity also played an important role in increasing the population. Ashfaq et al. (2010) reported that maximum jassid population start buildup in July and it has positive correlation with the temperature while relative humidity and rainfall had negative effect.

 

 

 

 

3.3 Jassid

The cumulative data showed the average population jassid was maximum (3.940 per leaf basis) population was recorded in 12-July while the lowest population (0.227 per leaf basis) was recorded on October in Figure 10. Different cotton varieties showed different level of population of jassid. In all varieties of cotton the maximum population was recorded in July while the lower density was recorded in October in Figure 9. Maximum population of jassid was recorded FH-942, FH-142, MNH886, CEMB-33, IUB-2015, respectively Figure 11. Correlate the population of jassid with the abiotic factors displayed that CEMB-33, FH-142, FH-942, IUB-2015 and MNH-886 had positive relationship with the maximum temperature, minimum temperature, moisture level, rainfall while the negative showed with the relative humidity and sunshine duration in Figure 12. Similar type of work done by the Salman et al. (2011) in which it was observed that the six cotton varieties grown in the NIAB, Faisalabad had maximum population of jassid in 3rd and 4th week of July. Arif et al. (2006) reported that the temperature and rainfall had positive relationship while the relative humidity had negative relationship. Mahmood et al. (2002), who reported about the correlation effect. It is observed that highest and the least temperature was positively correlated although relative humidity and rainfall was negatively linked.

 

 

 

3.4 Regression studies and yield

Based on regression study by taking sucking pest population “Y” as dependent variable while weather parameters “X” as independent variables following equations were fitted for the year 2018. The population of whitefly 0.342, 0.126, 0.086, 0.072, 0.098 had relationship with the minimum temperature, RH, rain, light duration and moisture. The population of jassid increases with the 0.297, 0.047, 0.06, 0.252 and 0.252 per three leaves per week with the increase in the minimum temperature, rainfall, sunshine duration and with the moisture. Thrip’s population 0.211, 0.041 and 0.058 increases with the minimum temperature, rainfall and sunshine duration (Table 1). The variable PCA Figure 13 tell us that moisture, minimum temperature jassid population, whitefly population, thrips population and maximum temperature had close relationship while the relative humidity and rainfall also having positive effect. The sunshine duration had negative relationship with the other factors. The Figure 14 showed that the population of pest having influence on the yield factor. This displayed that attack of whitefly (1.25 per leaf basis) , thrips (0.52 per leaf basis) and jassid (0.36 per leaf basis) had average yield of IUB-2015 was 1.19 kg. The cotton variety FH-142 having average yield 1.23 kg with the attack of whitefly (1.12 per leaf basis), thrips (0.42 per leaf basis) and jassid (0.44 per leaf basis). The cotton variety MNH-886 having average yield 080 kg with the attack of whitefly (0.91 per leaf basis), thrips (0.39 per leaf basis) and jassid (0.38 per leaf basis). The cotton variety CEMB-33 having average yield 1.25 kg with the attack of whitefly (0.83 per leaf basis), thrips (0.39 per leaf basis) and jassid (0.48 per leaf basis). The cotton variety FH-942 having average yield 0.45 kg with the attack of whitefly (0.75 per leaf basis), thrips (0.35 per leaf basis) and jassid (0.21 per leaf basis).

 

 

Conclusions and Recommendations

This study was done to check the attack of whitefly, thrips and jassid on different cultivars of cotton crop under unsprayed condition. Results indicated that whitefly population was low on IUB-2015 as compared to other. Same result was found when thrips and jassid attack. Abiotic factors also played an important role. In case of whitefly, jassid and thrips minimum temperature, maximum temperature showed positive role while in case of jassid moisture level also had significant role.

 

Table 1: Regression equation of sucking pests with weather parameters on Bt cotton and non-Bt cotton in Faisalabad region.

Sucking pests	Regression equation	R2 value
Whitefly	Y1= 10.017+0.342X1-0.26X2-0.126X3+0.086X4+0.072X5+0.098X6	0.334
Jassid	Y1= 10.842+0.297X1-0.271X2-0.109X3+0.047X4-0.06X5+0.252X5+0.252X6	0.266
Thrips	Y1=04.054+0.211X1-0.097X2-0.072X3+0.041X4+0.058X5-0.585X6	0.277

 

Acknowledgements

This work would not have been possible without the support of the worthy supervisor Dr. Muhammad Hamid Bashir. I am also indebted to Dr Abdul Ghaffar, Agricultural Research Officer, Ayub Agriculture Research Institute, Faisalabad, Pakistan and Muhammad Zia-ul-Haq, who have actively worked to provide me with protected academic time to pursue my professional goals and who have been supportive of my career ambitions. I am thankful to everyone who work and help during this scientific study.

I would especially like to thank respected Dr. Muhammad Hamid Bashir, the chairman of my committee. He taught me more than I could ever give him credit for as my teacher and mentor. He has demonstrated what a good scientist (and person) should be through his activities. The members of my family have been more valuable to me in the pursuit of this project than anybody else. I am thankful to my fellows, Aneeb Ali, Shoaib Nawaz, Iftikhar-ul-Hasan who provide unending inspiration.

Novelty Statement

The experiment was done under trial area of Univeristy of Agriculture Faisalabad. Main purpose of this is to note different abiotic factors under different conditions. All the results noted by using graphical data as well to get better and accurate result.

Author’s Contribution

Tamoor Ali: Did Experiments.

Muhammad Hamid Bashir, Bilal Saeed Khan, Ikram Ul Haq and Abdul Ghaffar: Supervised the experiment.

Danish Riaz, Muhammad Zia ul Haq, Shoaib Nawaz, Aneeb Ali, Iftikhar ul Hassan, Muhammad Khuram Shahzad, Usama Saleem and Tamsila Nazi: Supported throughout experiment.

Conflict of interest

The authors have declared no conflict of interest.

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