Cotton, as a cash crop, has huge economic importance. The high prevalence of pests, illnesses, weed pressure, the evolution of herbicide-resistant weeds, salinity, soil degradation, and climate anomalies such as droughts, floods, and heatwaves all limit cotton output around the world. Strategies like integrated pest management are employed to control the pest population across major cotton-producing countries. This method is effective as it aids in pest management and saves farmers a significant amount of money on pesticide purchases. Biotechnological advances have led to the development of Bt crops, which underwent a series of modifications according to the needs of farmers. Pyramid Bt and the effectiveness of RNA interference technology have been highlighted here. Also advances in the field of genomics have helped us understand plant-pest interaction. The following review is an overview of advancements in the field of cotton pests’ management and the role of genomics and other bioinformatics approaches to better understand the effective management of pests with the least effect on the ecosystem. There is a rising need to develop methods to achieve Sustainable Development Goals (SDGs) aimed at sustainable development. Developments in the field of cotton research for SDGs have also been discussed here.
Mathari JRJ, Mohideen HS. Cotton (Gossypium spp.) pest management in the era of next-generation sequencing: A review. J App Biol Biotech. 2023;11(Suppl 1):10-17. http://doi.org/10.7324/JABB.2023.149697
1. Subbiah A, Jeyakumar S. Cotton: White gold of India. Market Survey 2009. | |
2. Vitale J. Economic Importance of Cotton in Burkina Faso. Rome, Italy: Food and Agriculture Organization; 2018. | |
3. Das RC. Sustainability through total factor productivity growth in agriculture incorporating institutional factors: A post-globalized Indian Scenario. Int J Soc Ecol Sustain Dev 2023;14:1-6. https://doi.org/10.4018/IJSESD.319717 | |
4. Baffes J. Cotton, Biotechnology, and Economic Development. World Bank Policy Research Working Paper; 2011. https://doi.org/10.1596/1813-9450-5896 | |
5. Rana AW, Ejaz A, Shikoh SH. Cotton Crop: A Situational Analysis of Pakistan. Washington, DC: International Food Policy Research Institute; 2020. https://doi.org/10.2499/p15738coll2.133702 | |
6. Dai J, Dong H. Farming and cultivation technologies of cotton in China. In: Cotton Research. Vol. 77. London: IntechOpen; 2016. p. 97. https://doi.org/10.5772/64485 | |
7. Megantara FR, Purwanto Y, Setianingsih C. Detection of lettuce plant condition based on image using the convolutional neural network (cnn) Method. Proc Eng 2020;7:9330-8. | |
8. Chaudhry MR, Guitchounts A. Cotton Facts. Washington, DC, USA: International Cotton Advisory Committee; 2003. | |
9. Zhu YN, Shi DQ, Ruan MB, Zhang LL, Meng ZH, Liu J, et al. Transcriptome analysis reveals crosstalk of responsive genes to multiple abiotic stresses in cotton (Gossypium hirsutum L.). PLoS One 2013;8:e80218. https://doi.org/10.1371/journal.pone.0080218 | |
10. Tarazi R, Jimenez JL, Vaslin MF. Biotechnological solutions for major cotton (Gossypium hirsutum) pathogens and pests. Biotechnol Res Innov 2019;3:19-26. https://doi.org/10.1016/j.biori.2020.01.001 | |
11. Hussain SB, Rizwi M, Naqqash T, Zubair M, Sarwar S. Identifying genetic diversity of cotton leaf curl virus in commercial cotton (Gossypium hirsutum L.). Asian J Biochem Genet Mol Biol 2021;9:1-9. https://doi.org/10.9734/ajbgmb/2021/v9i430223 | |
12. El-Wakeil N, Abdallah A. Cotton Pests and the Actual Strategies for their Management Control. Vol. 400. New York: Nova Science Publishers, Inc.; 2012. p. 11788-3619. | |
13. Gulhane VA, Gurjar AA. Detection of diseases on cotton leaves and its possible diagnosis. Int J Image Process 2011;5:590-8. | |
14. Hasan I, Rasul S, Malik TH, Qureshi MK, Aslam K, Shabir G, et al. Present status of cotton leaf curl virus disease (CLCUVD): A major threat to cotton production. Int J Cotton Res Technol 2019;1:1-3. https://doi.org/10.33865/IJCRT.001.01.0240 | |
15. Rahman MA, Wilcock CC. A report on flavonoid investigation in some Bangladesh asclepiads. Bangladesh J Bot 1991;20:175-8. | |
16. Deguine JP, Ferron P, Russell D. Sustainable pest management for cotton production. A review. Agron Sustain Dev 2008;28:113-37. https://doi.org/10.1051/agro:2007042 | |
17. Cao G, Lu Q, Zhang L, Guo F, Liang G, Wu K, et al. Toxicity of chlorantraniliprole to Cry1Ac-susceptible and resistant strains of Helicoverpa armigera. Pestic Biochem Physiol 2010;98:99-103. https://doi.org/10.1016/j.pestbp.2010.05.006 | |
18. Llandres AL, Almohamad R, Brévault T, Renou A, Téréta I, Jean J, et al. Plant training for induced defense against insect pests: A promising tool for integrated pest management in cotton. Pest Manag Sci 2018;74:2004-12. https://doi.org/10.1002/ps.5039 | |
19. El-Hadary WA, Ahmed SY. Seasonal abundance of piercing sucking insect pests associated with cotton plant and their relation to natural enemies. J Plant Prot Pathol 2021;12:167-71. https://doi.org/10.21608/jppp.2021.154426 | |
20. Singh JK, Yadav KK, Kumar V. Integrated pest management: Conservation practices for agriculture and environment. ESSENCE Int J. Environ Rehabil Conserv 2017;8:17-28. | |
21. Bilbo TR, Reay-Jones FP, Reisig DD, Greene JK. Susceptibility of corn earworm (Lepidoptera: Noctuidae) to Cry1A. 105 and Cry2Ab2 in North and South Carolina. J Econ Entomol 2019;112:1845-57. https://doi.org/10.1093/jee/toz062 | |
22. Potin DM, Machado AV, Barbosa PR, Torres JB. Multiple factors mediate insecticide toxicity to a key predator for cotton insect pest management. Ecotoxicology 2022;31:490-502. https://doi.org/10.1007/s10646-022-02526-6 | |
23. Sahu BK, Samal I. Sucking pest complex of cotton and their management: A review. Pharma Innov J 2020;9:29-32. | |
24. Nalli S, Cooper DG, Nicell JA. Metabolites from the biodegradation of di-ester plasticizers by Rhodococcus rhodochrous. Sci Total Environ 2006;366:286-94. https://doi.org/10.1016/j.scitotenv.2005.06.020 | |
25. Kairon MS. Recent Advances in Cotton Production for Efficient Insect Pest Management. In: Proceedings World Cotton Conference-2, Athens, Greece; 1998. p. 6-12. | |
26. Carson R. Silent Spring. United States: Houghton Mifflin Harcourt; 2002. | |
27. Gupta M, Singh S, Kaur G, Pandher S, Kaur N, Goel N, et al. Transcriptome analysis unravels RNAi pathways genes and putative expansion of CYP450 gene family in cotton leafhopper Amrasca biguttula (Ishida). Mol Biol Rep 2021;48:4383-96. https://doi.org/10.1007/s11033-021-06453-3 | |
28. Boyd ML, Phipps BJ, Wrather JA, Newman M, Sciumbato GL. Cotton Pests: Scouting and Management 2004. | |
29. Luttrell RG. Cotton pest management: Part 2. A US perspective. Annu Rev Entomol 1994;39:527-42. https://doi.org/10.1146/annurev.en.39.010194.002523 | |
30. Chohan S, Perveen R, Abid M, Tahir MN, Sajid M. Cotton diseases and their management. In: Cotton Production and Uses: Agronomy, Crop Protection, and Postharvest Technologies. Berlin: Springer; 2020. p. 239-70. https://doi.org/10.1007/978-981-15-1472-2_13 | |
31. Yu SJ. Insecticide resistance in the fall armyworm, Spodoptera frugiperda (JE Smith). Pestic Biochem Physiol 1991;39:84-91. https://doi.org/10.1016/0048-3575(91)90216-9 | |
32. Kumar B, Omkar. Insect Pest Management. Berlin: Springer Singapore; 2018. https://doi.org/10.1007/978-981-10-8687-8_27 | |
33. Wu KM, Guo YY. The evolution of cotton pest management practices in China. Annu Rev Entomol 2005;50:31-52. https://doi.org/10.1146/annurev.ento.50.071803.130349 | |
34. Ramalho FD. Cotton pest management: Part 4. A Brazilian perspective. Annu Rev Entomol 1994;39:563-78. https://doi.org/10.1146/annurev.en.39.010194.003023 | |
35. Padaliya SR, Thumar RK, Borad MG, Patel NK. Bio-efficacy of different ready-mix insecticides against thrips, Scirtothrips dorsalis Hood infesting Bt cotton. Int J Curr Microbiol App Sci 2018;7:2904-5. https://doi.org/10.20546/ijcmas.2018.707.340 | |
36. Saeed R, Razaq M, Abbas N, Jan MT, Naveed M. Toxicity and resistance of the cotton leaf hopper, Amrasca devastans (Distant) to neonicotinoid insecticides in Punjab, Pakistan. Crop Prot 2017;93:143-7. https://doi.org/10.1016/j.cropro.2016.11.032 | |
37. Ahmad M, Arif MI, Ahmad Z, Denholm I. Cotton whitefly (Bemisia tabaci) resistance to organophosphate and pyrethroid insecticides in Pakistan. Pest Manag Sci 2002;58:203-8. https://doi.org/10.1002/ps.440 | |
38. Ahmad M, Iqbal Arif M. Resistance of Pakistani field populations of spotted bollworm Earias vittella (Lepidoptera: Noctuidae) to pyrethroid, organophosphorus and new chemical insecticides. Pest Manag Sci 2009;65:433-9. https://doi.org/10.1002/ps.1702 | |
39. Dhawan AK. Integrated pest management in cotton. In: Integrated Pest Management in the Tropics. Vol. 16. New Delhi: New India Publishing Agency; 2016. p. 499-575. | |
40. Peshin R, Dhawan AK, editors. Integrated Pest Management. Dissemination and Impact. Vol. 2. Berlin: Springer Science & Business Media; 2009. https://doi.org/10.1007/978-1-4020-8990-9 | |
41. Wei W, Mushtaq Z, Ikram A, Faisal M, Wan-Li Z, Ahmad MI. Estimating the economic viability of cotton growers in Punjab Province, Pakistan. Sage Open 2020;10:2158244020929310. https://doi.org/10.1177/2158244020929310 | |
42. Peshin R. Farmers' adoptability of integrated pest management of cotton revealed by a new methodology. Agron Sustain Dev 2013;33:563-72. https://doi.org/10.1007/s13593-012-0127-4 | |
43. Kogan M. Integrated pest management: Historical perspectives and contemporary developments. Annu Rev Entomol 1998;43:243-70. https://doi.org/10.1146/annurev.ento.43.1.243 | |
44. Van Den Berg H, Von Hildebrand A, Ragunathan V, Das PK. Reducing vector-borne disease by empowering farmers in integrated vector management. Bull World Health Organ 2007;85:561-6. https://doi.org/10.2471/BLT.06.035600 | |
45. Mancini F, Van Bruggen AH, Jiggins JL. Evaluating cotton integrated pest management (IPM) farmer field school outcomes using the sustainable livelihoods approach in India. Exp Agric 2007;43:97-112. https://doi.org/10.1017/S001447970600425X | |
46. Swezey SL, Murray DL, Daxl RG. Nicaragua's revolution in pesticide policy. Environ Sci Policy Sustain Dev 1986;28:6-36. https://doi.org/10.1080/00139157.1986.9929866 | |
47. Purcell JP, Perlak FJ. Global impact of insect-resistant (Bt) cotton. AgBioForum 2004;7:27-30. | |
48. Qaim M, Subramanian A, Naik G, Zilberman D. Adoption of Bt cotton and impact variability: Insights from India. Appl Econ Perspect Policy 2006;28:48-58. https://doi.org/10.1111/j.1467-9353.2006.00272.x | |
49. Perlak FJ, Oppenhuizen M, Gustafson K, Voth R, Sivasupramaniam S, Heering D, et al. Development and commercial use of Bollgard® cotton in the USA-early promises versus today's reality. Plant J 2001;27:489-501. https://doi.org/10.1046/j.1365-313X.2001.01120.x | |
50. Pray CE, Huang J, Hu R, Rozelle S. Five years of Bt cotton in China-the benefits continue. Plant J 2002;31:423-30. https://doi.org/10.1046/j.1365-313X.2002.01401.x | |
51. Tabashnik BE, Van Rensburg JB, Carrière Y. Field-evolved insect resistance to Bt crops: Definition, theory, and data. J Econ Entomol 2009;102:2011-25. https://doi.org/10.1603/029.102.0601 | |
52. Tabashnik BE. Evolution of resistance to Bacillus thuringiensis. Annu Rev Entomol 1994;39:47-79. https://doi.org/10.1146/annurev.en.39.010194.000403 | |
53. Ma W, Zhang T. Next-generation transgenic cotton: Pyramiding RNAi with Bt counters insect resistance. In: Transgenic Cotton: Methods and Protocols. United States: Humana; 2019. p. 245-56. https://doi.org/10.1007/978-1-4939-8952-2_21 | |
54. Tabashnik BE, Sisterson MS, Ellsworth PC, Dennehy TJ, Antilla L, Liesner L, et al. Suppressing resistance to Bt cotton with sterile insect releases. Nat Biotechnol 2010;28:1304-7. https://doi.org/10.1038/nbt.1704 | |
55. Tabashnik BE, Brévault T, Carrière Y. Insect resistance to Bt crops: Lessons from the first billion acres. Nat Biotechnol 2013;31:510-21. https://doi.org/10.1038/nbt.2597 | |
56. Grada A, Weinbrecht K. Next-generation sequencing: Methodology and application. J Invest Dermatol 2013;133:e11. https://doi.org/10.1038/jid.2013.248 | |
57. Cottrell P. Advantages and Drawbacks of Next Generation Sequencing; 2018. https://doi.org/10.2139/ssrn.3183340 | |
58. Kukurba KR, Montgomery SB. RNA sequencing and analysis. Cold Spring Harbor Protoc 2015;2015:951-69. https://doi.org/10.1101/pdb.top084970 | |
59. Firmino AA, Fonseca FC, de Macedo LL, Coelho RR, de Souza JD Jr., Togawa RC, et al. Transcriptome analysis in cotton boll weevil (Anthonomus grandis) and RNA interference in insect pests. PLoS One 2013;8:e85079. https://doi.org/10.1371/journal.pone.0085079 | |
60. Shin H, Hirst M, Bainbridge MN, Magrini V, Mardis E, Moerman DG, et al. Transcriptome analysis for Caenorhabditis elegans based on novel expressed sequence tags. BMC Biol 2008;6:30. https://doi.org/10.1186/1741-7007-6-30 | |
61. Legrand S, Valot N, Nicolé F, Moja S, Baudino S, Jullien F, et al. One-step identification of conserved miRNAs, their targets, potential transcription factors and effector genes of complete secondary metabolism pathways after 454 pyrosequencing of calyx cDNAs from the Labiate Salvia sclarea L. Gene 2010;450:55-62. https://doi.org/10.1016/j.gene.2009.10.004 | |
62. Costa V, Aprile M, Esposito R, Ciccodicola A. RNA-Seq and human complex diseases: Recent accomplishments and future perspectives. Eur J Hum Genet 2013;21:134-42. https://doi.org/10.1038/ejhg.2012.129 | |
63. Costa V, Angelini C, De Feis I, Ciccodicola A. Uncovering the complexity of transcriptomes with RNA-Seq. J Biomed Biotechnol 2010;2010:853916. https://doi.org/10.1155/2010/853916 | |
64. Soreq L, Guffanti A, Salomonis N, Simchovitz A, Israel Z, Bergman H, et al. Long non-coding RNA and alternative splicing modulations in Parkinson's leukocytes identified by RNA sequencing. PLoS Comput Biol 2014;10:e1003517. https://doi.org/10.1371/journal.pcbi.1003517 | |
65. Wang Z, Gerstein M, Snyder M. RNA-Seq: A revolutionary tool for transcriptomics. Nat Rev Genet 2009;10:57-63. https://doi.org/10.1038/nrg2484 | |
66. Ungerer MC, Johnson LC, Herman MA. Ecological genomics: Understanding gene and genome function in the natural environment. Heredity (Edinb) 2008;100:178-83. https://doi.org/10.1038/sj.hdy.6800992 | |
67. Metzker ML. Sequencing technologies-the next generation. Nat Rev Genet 2010;11:31-46. https://doi.org/10.1038/nrg2626 | |
68. Wang Y, Zhang H, Li H, Miao X. Second-generation sequencing supply an effective way to screen RNAi targets in large scale for potential application in pest insect control. PLoS One 2011;6:e18644. https://doi.org/10.1371/journal.pone.0018644 | |
69. Tian L, Zeng Y, Xie W, Wu Q, Wang S, Zhou X, et al. Genome?wide identification and analysis of genes associated with RNA interference in Bemisia tabaci. Pest Manag Sci 2019;75:3005-14. https://doi.org/10.1002/ps.5415 | |
70. Noriega DD, Arias PL, Barbosa HR, Arraes FB, Ossa GA, Villegas B, et al. Transcriptome and gene expression analysis of three developmental stages of the coffee berry borer, Hypothenemus hampei. Sci Rep 2019;9:12804. https://doi.org/10.1038/s41598-019-49178-x | |
71. Chen H, Li Y, Ma X, Guo L, He Y, Ren Z, et al. Analysis of potential strategies for cadmium stress tolerance revealed by transcriptome analysis of upland cotton. Sci Rep 2019;9:86. https://doi.org/10.1038/s41598-018-36228-z | |
72. Sharif I, Aleem S, Farooq J, Rizwan M, Younas A, Sarwar G, et al. Salinity stress in cotton: Effects, mechanism of tolerance and its management strategies. Physiol Mol Biol Plants 2019;25:807-20. https://doi.org/10.1007/s12298-019-00676-2 | |
73. Sureshan SC, Mohideen HS, Nair TS. Gut metagenomic profiling of gossypol induced Oxycarenus laetus (Hemiptera: Lygaeidae) reveals gossypol tolerating bacterial species. Indian J Microbiol 2022;62:54-60. https://doi.org/10.1007/s12088-021-00964-0 | |
74. Dubey NK, Goel R, Ranjan A, Idris A, Singh SK, Bag SK, et al. Comparative transcriptome analysis of Gossypium hirsutum L. in response to sap sucking insects: aphid and whitefly. BMC Genomics 2013;14:241. https://doi.org/10.1186/1471-2164-14-241 | |
75. Artico S, Ribeiro-Alves M, Oliveira-Neto OB, de Macedo LL, Silveira S, Grossi-de-Sa MF, et al. Transcriptome analysis of Gossypium hirsutum flower buds infested by cotton boll weevil (Anthonomus grandis) larvae. BMC Genomics 2014;15:854. https://doi.org/10.1186/1471-2164-15-854 | |
76. Huang XZ, Chen JY, Xiao HJ, Xiao YT, Wu J, Wu JX, et al. Dynamic transcriptome analysis and volatile profiling of Gossypium hirsutum in response to the cotton bollworm Helicoverpa armigera. Sci Rep 2015;5:11867. https://doi.org/10.1038/srep11867 | |
77. Xing L, Yuan C, Wang M, Lin Z, Shen B, Hu Z, et al. Dynamics of the interaction between cotton bollworm Helicoverpa armigera and nucleopolyhedrovirus as revealed by integrated transcriptomic and proteomic analyses. Mol Cell Proteomics 2017;16:1009-28. https://doi.org/10.1074/mcp.M116.062547 | |
78. Li ZQ, Zhang S, Luo JY, Wang CY, Lv LM, Dong SL, et al. Ecological adaption analysis of the cotton aphid (Aphis gossypii) in different phenotypes by transcriptome comparison. PLoS One 2013;8:e83180. https://doi.org/10.1371/journal.pone.0083180 | |
79. Li J, Zhu L, Hull JJ, Liang S, Daniell H, Jin S, et al. Transcriptome analysis reveals a comprehensive insect resistance response mechanism in cotton to infestation by the phloem feeding insect Bemisia tabaci (whitefly). Plant Biotechnol J 2016;14:1956-75. https://doi.org/10.1111/pbi.12554 | |
80. Kumar S, Kanakachari M, Gurusamy D, Kumar K, Narayanasamy P, Kethireddy Venkata P, et al. Genome?wide transcriptomic and proteomic analyses of bollworm?infested developing cotton bolls revealed the genes and pathways involved in the insect pest defence mechanism. Plant Biotechnol J 2016;14:1438-55. https://doi.org/10.1111/pbi.12508 | |
81. Pinto CP. In silico approaches for the ecdysone receptor of Hemiptera: The first step for rational pesticide discovery. Int J Curr Microbiol App Sci 2019;8:261-70. https://doi.org/10.20546/ijcmas.2019.801.029 | |
82. Bedre R. Genome-wide Transcriptome Analysis of Cotton (Gossypium hirsutum L.) to Identify Genes in Response to Aspergillus flavus Infection, and Development of RNA-Seq Data Analysis Pipeline. United States: Louisiana State University and Agricultural and Mechanical College; 2016. | |
83. He X, Sun Q, Jiang H, Zhu X, Mo J, Long L, et al. Identification of novel microRNAs in the Verticillium wilt-resistant upland cotton variety KV-1 by high-throughput sequencing. Springerplus 2014;3:564. https://doi.org/10.1186/2193-1801-3-564 | |
84. Lira EC, Bolzan A, Nascimento AR, Amaral FS, Kanno RH, Kaiser IS, et al. Resistance of Spodoptera frugiperda (Lepidoptera: Noctuidae) to spinetoram: Inheritance and cross?resistance to spinosad. Pest Manag Sci 2020;76:2674-80. https://doi.org/10.1002/ps.5812 | |
85. Xiong GH, Xing LS, Lin Z, Saha TT, Wang C, Jiang H, et al. High throughput profiling of the cotton bollworm Helicoverpa armigera immunotranscriptome during the fungal and bacterial infections. BMC Genomics 2015;16:321. https://doi.org/10.1186/s12864-015-1509-1 | |
86. Rosario K, Capobianco H, Ng TF, Breitbart M, Polston JE. RNA viral metagenome of whiteflies leads to the discovery and characterization of a whitefly-transmitted Carlavirus in North America. PLoS One 2014;9:e86748. https://doi.org/10.1371/journal.pone.0086748 | |
87. do Nascimento AR, Pavinato VA, Rodrigues JG, Silva-Brandão KL, Consoli FL, Michel A, et al. There is more than chitin synthase in insect resistance to benzoylureas: Molecular markers associated with teflubenzuron resistance in Spodoptera frugiperda. J Pest Sci 2022;95:129-44. https://doi.org/10.1007/s10340-021-01373-4 | |
88. Xie W, Meng QS, Wu QJ, Wang SL, Yang X, Yang NN, et al. Pyrosequencing the Bemisia tabaci transcriptome reveals a highly diverse bacterial community and a robust system for insecticide resistance. PLoS One 2012;7:e35181. https://doi.org/10.1371/journal.pone.0035181 | |
89. Rachman T. Application of the rapidminer application to predict the rupiah exchange rate against the US dollar using the linear regression method. Angew Chemie Int Ed 2018;6:951-2. | |
90. Srivastava CP, Chakravarty S. Advances and prospects of biotechnological approaches in integrated pest management. J Exp Zool India 2021;24:815-23. | |
91. Batista BD, Singh BK. Realities and hopes in the application of microbial tools in agriculture. Microb Biotechnol 2021;14:1258-68. https://doi.org/10.1111/1751-7915.13866 | |
92. Mandrioli M, Zambonini G, Manicardi GC. Comparative gene mapping as a tool to understand the evolution of pest crop insect chromosomes. Int J Mol Sci 2017;18:1919. https://doi.org/10.3390/ijms18091919 | |
93. Baxter SW, Davey JW, Johnston JS, Shelton AM, Heckel DG, Jiggins CD, et al. Linkage mapping and comparative genomics using next-generation RAD sequencing of a non-model organism. PLoS One 2011;6:e19315. https://doi.org/10.1371/journal.pone.0019315 | |
94. Aggarwal R, Benatti TR, Gill N, Zhao C, Chen MS, Fellers JP, et al. A BAC-based physical map of the Hessian fly genome anchored to polytene chromosomes. BMC Genomics 2009;10:293. https://doi.org/10.1186/1471-2164-10-293 | |
95. Ren X, Wang X, Yuan H, Weng Q, Zhu L, He G. Mapping quantitative trait loci and expressed sequence tags related to brown planthopper resistance in rice. Plant Breed 2004;123:342-8. https://doi.org/10.1111/j.1439-0523.2004.01003.x | |
96. Kriticos D, Venette R, Koch F, Rafoss T, Van der Werf W, Worner S. Invasive alien species in the food chain: Advancing risk assessment models to address climate change, economics and uncertainty. NeoBiota 2013;18:1-7. https://doi.org/10.3897/neobiota.18.6108 | |
97. Tang ZH, Gong KY, You ZP. Present status and countermeasures of insecticide resistance in agricultural pests in China. Pestic Sci 1988;23:189-98. https://doi.org/10.1002/ps.2780230212 | |
98. Brown LC, Cathey GW, Lincoln C. Growth and development of cotton as affected by toxaphene-DDT, methyl parathion, and calcium arsenate. J Econ Entomol 1962;55:298-301. https://doi.org/10.1093/jee/55.3.298 | |
99. Naranjo SE. Impacts of Bt crops on non-target invertebrates and insecticide use patterns. CABI Rev 2009;4:1. https://doi.org/10.1079/PAVSNNR20094011 | |
100. Ellgehausen H, Guth JA, Esser HO. Factors determining the bioaccumulation potential of pesticides in the individual compartments of aquatic food chains. Ecotoxicol Environ Saf 1980;4:134-57. https://doi.org/10.1016/0147-6513(80)90015-9 | |
101. Malaguerra F, Albrechtsen HJ, Thorling L, Binning PJ. Pesticides in water supply wells in Zealand, Denmark: A statistical analysis. Sci Total Environ 2012;414:433-44. https://doi.org/10.1016/j.scitotenv.2011.09.071 | |
102. Trapero C, Wilson IW, Stiller WN, Wilson LJ. Enhancing integrated pest management in GM cotton systems using host plant resistance. Front Plant Sci 2016;7:500. https://doi.org/10.3389/fpls.2016.00500 |
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