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Climate Resilient Cotton Production System: A Case Study in Pakistan

Abstract

Cotton production is most vulnerable to climate change particularly in Pakistan, and sustainable cotton yield is critical to accomplish the future demand of the country. Climate change has negative impact on cotton production in major parts of the cotton-growing regions. It hampers not only the yield but also quality of fiber and has negative impact on socioeconomic conditions of farmers. Climate, crop, and economic multidisciplinary modeling approach are being used to assess the impact of climate change and development of adaptation strategies for sustainable cotton production. Climate change scenarios revealed the increase in both maximum and minimum temperature and uncertain rainfall patterns throughout the world and especially in dry and arid areas of the world like Pakistan. Rainfall would increase and decrease as projected by multi-GCMs and RCPs, and it is fact that these changes in climate would lead to negative effect on cotton crop production, and sustainable cotton production in the future is under threat due to climate variablity. Generally, mostly general circulation model (GCM) scenario projected the reduction in cotton yield as compared with the baseline during both timer periods and RCPs tested. Adaptation strategies can minimize the negative impact of climate change. So, changes in crop management practices (sowing, planting density, irrigation, and plant protection) may be good adaptation strategies for sustainable cotton production under changing climate scenarios of the world. Climate resilient cotton production system has potential to minimize the negative impacts of climate change on cotton crop by developing heat and drought resilient germplasm, mitigation technology to reduce GHG emission, and application of decision support system (DSS) and use of ICT-based technologies for sustainable cotton crop production. It is time to adopt climate, energy, and water smart cotton production technologies and practices for sustainable cotton production in the future.

Keywords

  • Climate change
  • Phenology
  • Adaptation
  • Resilient
  • Sustainable
  • DSSAT

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Abbreviations

AEZ:

Arid irrigated zone

BVT:

Bee vectoring technology

CO2 :

Carbon dioxide

DSSAT:

Decision Support System for Agrotechnology Transfer

GCMs:

General circulation models

GHG:

Greenhouse gas

GIS:

Geographical information system

ICT:

Information and communication technologies

IPM:

Integrated pest management

RCPs:

Representative concentration pathways

SR:

Solar radiation

References

  • Abbas Q, Ahmad S (2018) Effect of different sowing times and cultivars on cotton fiber quality under stable cotton-wheat cropping system in southern Punjab, Pakistan. Pak J Life Soc Sci 16:77–84

    Google Scholar 

  • Achilea O, Ronen E, Elharrar G (2005) Haifa Nurti-Net–a comprehensive crop Nutrition software, operated over the web. EFITA/WCCA, pp 25–28

    Google Scholar 

  • AgMIP (2013a) Guide for running AgMIP climate scenario generation tools with R in windows. AgMIP. http://www.agmip.org/wp-content/uploads/2013/10/Guide-forRunning-AgMIP-Climate-Scenario-Generation-with-R-v2.3.pdf

  • AgMIP (2013b) The coordinated climate-crop modeling project C3MP: an initiative of the agricultural model inter comparison and improvement project. C3MP protocols and procedures. AgMIP. http://research.agmip.org/download/attachments/1998899/C3MP+Protocols+v2.pdf

  • AgMIP (2014) Guide for regional integrated assessments: handbook of methods and procedures, Version 5.1. AgMIP. http://www.agmip.org/wpcontent/uploads/2013/06/AgMIPRegional%20Research-Team-Handbook-v4.2.pdf

  • Ahmad S, Raza I (2014) Optimization of management practices to improve cotton fiber quality under irrigated arid environment. J Food Agric Environ 2(2):609–613

    Google Scholar 

  • Ahmad S, Raza I, Ali H, Shahzad AN, Atiq-ur-Rehman, Sarwar N (2014) Response of cotton crop to exogenous application of glycinebetaine under sufficient and scarce water conditions. Braz J Bot 37(4):407–415

    Google Scholar 

  • Ahmad A, Ashfaq M, Rasul G, Wajid SA, Khaliq T, Rasul F, Saeed U, Rahman MH, Hussain J, Baig IA, Naqvi SAA, Bokhari SAA, Ahmad S, Naseem W, Hoogenboom G, Valdivia R (2015) Impact of climate change on the rice–wheat cropping system of Pakistan. In: Rosenzweig C, Hillel D (eds) Handbook of climate change and agro ecosystems: the agricultural model inter comparison and improvement project integrated crop and economic assessments, Part 2. Imperial College Press, London

    Google Scholar 

  • Ahmad S, Abbas Q, Abbas G, Fatima Z, Atique-ur-Rehman, Naz S, Younis H, Khan RJ, Nasim W, Habib ur Rehman M, Ahmad A, Rasul G, Khan MA, Hasanuzzaman M (2017a) Quantification of climate warming and crop management impacts on cotton phenology. Plants 6(1):E7. https://doi.org/10.3390/plants6010007

    CrossRef  PubMed  Google Scholar 

  • Ahmad A, Ashfaq M, Rasul G, Wajid SA, Khaliq T, Rasul F, Saeed U, Ahmad I, Nasir J, Baig IA (2017b) AgMIP-Pakistan RRT final report. Agric Model Intercomp Improv Proj. 1–76

    Google Scholar 

  • Ahmad S, Iqbal M, Muhammad T, Mehmood A, Ahmad S, Hasanuzzaman M (2018) Cotton productivity enhanced through transplanting and early sowing. Acta Sci Biol Sci 40:e34610

    CrossRef  Google Scholar 

  • Ahmad I, Wajid SA, Ahmad A, Cheema MJM, Judge J (2019) Optimizing irrigation and nitrogen requirements for maize through empirical modeling in semi-arid environment. Environ Sci Pollut Res Int 26(2):1227–1237

    CAS  PubMed  CrossRef  Google Scholar 

  • Ali H, Afzal MN, Ahmad F, Ahmad S, Akhtar M, Atif R (2011) Effect of sowing dates, plant spacing and nitrogen application on growth and productivity on cotton crop. Int J Sci Eng Res 2(9):1–6

    Google Scholar 

  • Ali H, Abid SA, Ahmad S, Sarwar N, Arooj M, Mahmood A, Shahzad AN (2013a) Integrated weed management in cotton cultivated in the alternate-furrow planting system. J Food Agric Environ 11(3&4):1664–1669

    Google Scholar 

  • Ali H, Abid SA, Ahmad S, Sarwar N, Arooj M, Mahmood A, Shahzad AN (2013b) Impact of integrated weed management on flat-sown cotton (Gossypium hirsutum L.). J Anim Plant Sci 23(4):1185–1192

    CAS  Google Scholar 

  • Ali H, Hameed RA, Ahmad S, Shahzad AN, Sarwar N (2014a) Efficacy of different techniques of nitrogen application on American cotton under semi-arid conditions. J Food Agric Environ 12(1):157–160

    Google Scholar 

  • Ali H, Hussain GS, Hussain S, Shahzad AN, Ahmad S, Javeed HMR, Sarwar N (2014b) Early sowing reduces cotton leaf curl virus occurrence and improves cotton productivity. Cer Agron Moldova XLVII(4):71–81

    Google Scholar 

  • Amin A, Nasim W, Mubeen M, Nadeem M, Ali L, Hammad HM, Sultana SR, Jabran K, Habib ur Rehman M, Ahmad S, Awais M, Rasool A, Fahad S, Saud S, Shah AN, Ihsan Z, Ali S, Bajwa AA, Hakeem KR, Ameen A, Amanullah, Rehman HU, Alghabar F, Jatoi GH, Akram M, Khan A, Islam F, Ata-Ul-Karim ST, Rehmani MIA, Hussain S, Razaq M, Fathi A (2017) Optimizing the phosphorus use in cotton by using CSM-CROPGRO-cotton model for semi-arid climate of Vehari-Punjab, Pakistan. Environ Sci Pollut Res 24(6):5811–5823

    CAS  Google Scholar 

  • Amin A, Nasim W, Mubeen M, Ahmad A, Nadeem M, Urich P, Fahad S, Ahmad S, Wajid A, Tabassum F, Hammad HM, Sultana SR, Anwar S, Baloch SK, Wahid A, Wilkerson CJ, Hoogenboom G (2018) Simulated CSM-CROPGRO-cotton yield under projected future climate by SimCLIM for southern Punjab. Pak Agric Syst 167:213–222

    CrossRef  Google Scholar 

  • Arora R, Jindal V, Rathore P, Kumar R, Singh V, Bajaj L (2011) Integrated pest management of cotton in Punjab, India. Radcliffe’s IPM world Textb., St. Paul University, Minnesota. http://www.ipmworld.umn.edu/chapters/Arora.html

  • Arshad M, Wajid A, Maqsood M, Hussain K, Aslam M, Ibrahim M (2007) Response of growth, yield and quality of different cotton cultivars to sowing dates. Pak J Agric Sci 44:208–212

    Google Scholar 

  • Ashraf S, Iftikhar M (2013) Mitigation and adaptation strategies for climate variability: a case of cotton growers in the Punjab, Pakistan. Int J Agric Ext 1(1):30–35

    Google Scholar 

  • Asseng S, Ewert F, Rosenzweig C, Jones JW, Hatfield JL, Ruane AC, Boote KJ, Thorburn PJ, Rötter RP, Cammarano D, Brisson N, Basso B, Martre P, Aggarwal PK, Angulo C, Bertuzzi P, Biernath C, Challinor AJ, Doltra J, Gayler S, Goldberg R, Grant R, Heng L, Hooker J, Hunt LA, Ingwersen J, Izaurralde RC, Kersebaum KC, Müller C, Kumar NS, Nendel C, O’Leary G, Olesen JE, Osborne TM, Palosuo T, Priesack E, Ripoche D, Semenov MA, Shcherbak I, Steduto P, Stöckle C, Stratonovitch P, Streck T, Supit I, Tao F, Travasso M, Waha K, Wallach D, White JW, Williams JR, Wolf J (2013) Uncertainty insimulating wheat yields under climate change. Nat Clim Chang 3:827–832

    CAS  CrossRef  Google Scholar 

  • Bange MP, Milroy SP (2004) Impact of short term exposure to cold temperatures on early development of cotton (Gossypium hirsutum L.). Aust J Agric Res 55:655–664

    CrossRef  Google Scholar 

  • Bange MP, Caton SJ, Milroy SP (2008) Managing yields of high fruit retention in transgenic cotton (Gossypium hirsutum L.) using sowing date. Aust J Agric Res 59:733–741

    CrossRef  Google Scholar 

  • Batool S, Saeed F (2017) Mapping the cotton value chain in Pakistan: a preliminary assessment for identification of climate vulnerabilities & pathways to adaptation. Sustainable Development Policy Institute, Islamabad, Pakistan, pp 1–60

    Google Scholar 

  • Bhaskar KS, Rao MRK, Mendhe PN, Suryavanshi MR (2005) Micro irrigation management in cotton. CICR Technical Bulletin No. 31. Cent. Inst. Cott. Res., Nagpur, India

    Google Scholar 

  • Bradow JM, Davidonis GH (2000) Quantitation of fiber quality and the cotton production-processing interface: a physiologist’s perspective. J Cotton Sci 4:34–64

    Google Scholar 

  • Braunack MV, Bange MP, Johnston DB (2012) Can planting date and cultivar selection improve resource use efficiency of cotton systems? Field Crop Res 137:1–11

    CrossRef  Google Scholar 

  • Chastain DR, Snider JL, Choinski JS, Collins GD, Perry CD, Whitaker J, Grey TL, Sorensen RB, van Iersel M, Byrd SA, Porter W (2016) Leaf ontogeny strongly influences photosynthetic tolerance to drought and high temperature in Gossypium hirsutum. J Plant Physiol 199:18–28

    CAS  PubMed  CrossRef  Google Scholar 

  • Collins M, Knutti R, Arblaster J, Dufresne JL, Fichefet T, Friedlingstein P, Gao X, Gutowski WJ, Johns T, Krinner G, Shongwe M, Tebaldi C, Weaver AJ, Wehner M (2013) Long term climate change: projections, commitments and irreversibility. In: Stocker TF, Qin D, Plattner GK, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change. The physical science basis. Contribution of working group I to the fifth assessment report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK, pp 1029–1036. https://doi.org/10.1017/CBO9781107415324.024

    CrossRef  Google Scholar 

  • Conaty WC, Burke JJ, Mahan JR, Neilsen JE, Sutton BG (2012) Determining the optimum plant temperature of cotton physiology and yield to improve plant-based irrigation scheduling. Crop Sci 52:1828–1836

    CrossRef  Google Scholar 

  • Constable GA, Bange MP (2006) What is cotton’s sustainable yield potential? Aust Cotton Grower 26:6–10

    Google Scholar 

  • Cottee NS, Tan DKY, Bange MP, Cothren JT, Campbell LC (2010) Multi-level determination of heat tolerance in cotton (Gossypium hirsutum L.) under field conditions. Crop Sci 50:2553–2564

    CrossRef  Google Scholar 

  • Cotton Incorporated (2009) Summary of life cycle inventory data for cotton (field to bale – version 1.12 July 2009). Cary, NC, Cotton Incorporated, p 31

    Google Scholar 

  • Dağdelen N, Başal H, Yılmaz E, Gürbüz T, Akcay S (2009) Different drip irrigation regimes affect cotton yield, water use efficiency and fiber quality in western Turkey. Agric Water Manag 96(1):111–120

    CrossRef  Google Scholar 

  • FAO (2010) “Climate-smart” agriculture policies, practices and financing for food security, adaptation and mitigation. Food and Agriculture Organization of the United State of America (FAO), Rome, Italy, pp 1–49. http://www.fao.org/docrep/013/i1881e/i1881e00.htm. Accessed 21 Dec 2018

    Google Scholar 

  • FAO (2013) Climate smart agriculture sourcebook. Food and Agriculture Organization of the United Nations (FAO), Rome. http://www.fao.org/docrep/018/i3325e/i3325e.pdf

    Google Scholar 

  • FAO (2017) FAOSTAT Pakistan. Food and Agriculture Organization of the United Nations (FAO), Rome. http://www.fao.org/faostat/en

    Google Scholar 

  • FAO (Food and Agriculture Organisation of the United Nations) (2012) The state of food and agriculture - investing in agriculture for a better future. FAO, Rome, Italy

    CrossRef  Google Scholar 

  • FAO (Food and Agriculture Organisation of the United Nations) (2016) AQUASTAT website. http://www.fao.org/nr/water/aquastat/main/index.stm

  • Ghazala N, Rasul G (2009) Water requirement of wheat crop in Pakistan. Pak J Meteorol 6(11):89–97

    Google Scholar 

  • Gibbons MM, Fawcett CP, Warings RJ, Dearne K, Dampney P, Richardson SJ (2005) PLANET nutrient management decision support system–a standard approach to fertilizer recommendations. EFITA/WCCA, pp 25–28

    Google Scholar 

  • GOP (2016) Final crop estimates. 2016, Crop Reporting Service, Governmement of Punjab, Lahore. http://crs.agripunjab.gov.pk

  • GOP (Government of Punjab) (2018) Cotton under drip irrigation system - a case study. Directorate General Agriculture (Water Managment), Government of Punjab, Lahore. http://ofwm.agripunjab.gov.pk

  • Grantz DA (2003) Ozone impacts on cotton: towards an integrated mechanism. Environ Pollut 126:331–344

    CAS  PubMed  CrossRef  Google Scholar 

  • Hillocks RJ (2005) Integrated management of insect pests, diseases and weeds of cotton in Africa. Integr Pest Manag Rev 1:31–47

    CrossRef  Google Scholar 

  • Hoogenboom G (2000) Contribution of agrometeorology to the simulation of crop production and its applications. Agric For Meteorol 103:137–157

    CrossRef  Google Scholar 

  • Huang J (2016) Different sowing dates affected cotton yield and yield components. Int J Plant Prod 10:63–84

    Google Scholar 

  • Imran MA, Ali A, Ashfaq M, Hassan S, Culas R, Ma C (2018) Impact of climate smart agriculture (CSA) practices on cotton production and livelihood of farmers in Punjab. Pak Sustain 10:2101. https://doi.org/10.3390/su10062101

    CrossRef  Google Scholar 

  • IPCC (2013a) Summary for policymakers. In: Climate change 2013. The physical science basis. Contribution of working group I to the fifth assessment report of the Intergovernmental Panel on Climate Change, p 33. https://doi.org/10.1017/CBO9781107415324

    Google Scholar 

  • IPCC (2013b) Summary for policymakers. In: Stocker TF, Qin D, Plattner G-K, Tignor M, Allen SK, Boschung J, Nauels A, Xia Y, Bex V, Midgley PM (eds) Climate change 2013: the physical science basis. Contribution of working group I to the fifth assessment report of the Intergovernmental Panel on Climate Change. IPCC, Cambridge, UK. http://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WGIAR5_SPM_brochure_en.pdf

    Google Scholar 

  • IPCC (2014a) Climate change 2014. Synthesis report summary chapter for policymakers 31. IPCC. https://doi.org/10.1017/CBO9781107415324

    Google Scholar 

  • IPCC (2014b) Summary for policymakers. In: C.B. Field, V.R. Barros, D.J. Dokken, K.J. Mach, M.D. Mastrandrea, T.E. Bilir, M. Chatterjee, K.L. Ebi, Y.O. Estrada, R.C. Genova, B. Girma, E.S. Kissel, A.N. Levy, S. MacCracken, P.R. Mastrandrea, and L.L. White Editor. Climate change 2014: impacts, adaptation, and vulnerability. Part A: Global and sectoral aspects. Contribution of working group II to the fifth assessment report of the Intergovernmental Panel on Climate Change, 2014, IPCC: Cambridge, UK. 1–32. http://ipcc-wg2.gov/AR5/images/uploads/WG2AR5_SPM_FINAL.pdf

  • ITC (2011) Trade map. International Trade Centre, Switzerland. http://www.trademap.org/

    Google Scholar 

  • Jalota SK, Sood A, Chahal GBS, Choudhary BU (2006) Crop water productivity of cotton (Gossypium hirsutum L.) – wheat (Triticum aestivum L.) system as influenced by deficit irrigation, soil texture and precipitation. Agric Water Manag 84:137–146

    CrossRef  Google Scholar 

  • Jones JW, Hansen JW, Royce FS, Messina CD (2000) Potential benefits of climate forecasting to agriculture. Agric Ecosyst Environ 82:169–184

    CrossRef  Google Scholar 

  • Khan MB, Khaliq A, Ahmad S (2004) Performance of mashbean intercropped in cotton planted in different planting patterns. J Res (Sci) 15(2):191–197

    Google Scholar 

  • Khatri-Chhetri A, Aryal JP, Sapkota TB, Khurana R (2016) Economic benefits of climate-smart agricultural practices to smallholder farmers in the Indo-Gangetic Plains of India. Curr Sci 110:1251–1256

    Google Scholar 

  • Khatri-Chhetri A, Aggarwal PK, Joshi PK, Vyas S (2017) Farmers’ prioritization of climate-smart agriculture (CSA) technologies. Agric Syst 151:184–191

    CrossRef  Google Scholar 

  • Loi NK, Tangtham N (2005) Decision support system (DSS) for sustainable watershed management in Dong Nai Watershed-Vietnam. In: Synergistic approach to appropriate forestry technology for sustaining rainforest ecosystems: proceedings International Forestry Seminar. Universiti Putra, Malaysia

    Google Scholar 

  • Luo Q, Bange M, Clancy L (2014) Cotton crop phenology in a new temperature regime. Ecol Model 285:22–29

    CrossRef  Google Scholar 

  • Luo Q, Bange M, Braunack M, Johnston D (2016) Effectiveness of agronomic practices in dealing with climate change impacts in the Australian cotton industry–a simulation study. Agric Syst 147:1–9

    CrossRef  Google Scholar 

  • Makhdum AH, Khan HN, Ahmad S (2011) Reducing cotton footprints through implementation of better management practices in cotton production; a step towards better cotton initiative. In: Proceedings of the fifth meeting of the Asian Cotton Research and Development Network, Lahore, Pakistan, 23–26 Feb 2011, pp 1–18. https://www.icac.org/tis/regional_networks/asian_network/meeting_5/. Accessed 4 Jan 2018

  • Manik SN, Pengilley G, Dean G, Field B, Shabala S, Zhou M (2019) Soil and crop management practices to minimize the impact of waterlogging on crop productivity. Front Plant Sci 10:140. https://doi.org/10.3389/fpls.2019.00140

    CrossRef  PubMed  PubMed Central  Google Scholar 

  • Manpreet S, Gumber RK, Brar AS, Mukesh S (2007) Performance of drip irrigation systems in cotton in relation to lateral patterns and irrigation levels. In: World Cotton Research Conference-4, Lubbock, Texas, USA, 10–14 Sept 2007. International Cotton Advisory Committee (ICAC)

    Google Scholar 

  • Mir SA, Quadri SMK (2009) Decision support systems: concepts, progress and issues–a review. In: Lichtfouse E (ed) Climate change, intercropping, pest control and beneficial microorganisms, Sustainable agricultural reviews, vol 2. Springer, Dordrecht, pp 373–399

    CrossRef  Google Scholar 

  • Muthamilselvan M, Rangasamy K, Ananthakrishnan D, Manian R (2007) Mechanical picking of cotton: a review. Agric Rev 28:118–126

    Google Scholar 

  • Nazli H, Orden D, Sarker R, Meilke K (2012) Bt cotton adoption and wellbeing of farmers in Pakistan. In: Proceedings of the International Association of Agricultural Economists (IAAE) Triennial Conference, Foz do Iguaçu, Brazil, 18–24 Aug 2012, pp 1–26. ageconsearch.umn.edu/bitstream/126172/

  • Pasha HA (2015) Growth of the provincial economies. Institute for Policy Reforms (IPR), Pakistan. http://ipr.org.pk/wp-content/uploads/2016/04/GROWTH-OF-PROVINCIAL-ECONOMICS-.pdf

    Google Scholar 

  • Perumal NK, Hebba KB, Rao MRK, Singh P (2006) Physiological disorders in cotton. Central Institute for Cotton Research, Nagpur, pp 1–25

    Google Scholar 

  • Pettigrew WT, Johnson JT (2005) Effects of different seeding rates and plant growth regulators on earlyplanted cotton. J Cotton Sci 9:189–198

    CAS  Google Scholar 

  • Petzoldt C, Seaman A (2006) Climate change effects on insects and pathogens. Clim Change Agric: Promoting Practical Profitable Responses 3:6–16

    Google Scholar 

  • Rahman H, Malik SA, Saleem M (2004) Heat tolerance of upland cotton during the fruiting stage evaluated using cellular membrane thermos stability. Field Crop Res 85:149–158

    CrossRef  Google Scholar 

  • Rahman MH, Ahmad A, Wajid A, Hussain M, Akhtar J, Hoogenboom G (2016) Estimation of temporal variation resilience in cotton varieties using statistical models. Pak J Agric Sci 53:787–807

    Google Scholar 

  • Rahman MH, Ahmad A, Wajid A, Hussain M, Rasul F, Ishaque W, Islam MA, Shelia V, Awais M, Ullah A, Wahid A, Sultana SR, Saud S, Khan S, Fahad S, Hussain M, Hussain S, Nasim W (2017) Application of CSMCROPGRO-Cotton model for cultivars and optimum planting dates: evaluation in changing semi-arid climate. Field Crop Res. https://doi.org/10.1016/j.fcr.2017.007

  • Rahman MH, Ahmad A, Wang X, Wajid A, Nasim W, Hussain M, Ahmad B, Ahmad I, Ali Z, Ishaque W, Awais M, Shelia V, Ahmad S, Fahad S, Alam M, Ullah H, Hoogenboom G (2018) Multi-model projections of future climate and climate change impacts uncertainty assessment for cotton production in Pakistan. Agric For Meteorol 253–254:94–113

    CrossRef  Google Scholar 

  • Rane J, Nagarajan S (2004) High temperature index—for field evaluation of heat tolerance in wheat varieties. Agric Syst 79(2):243–255

    CrossRef  Google Scholar 

  • Rasul G, Mahmood A, Sadiq A, Khan SI (2012) Vulnerability of the Indus Delta to climate change in Pakistan. Pak J Meteorol 8(16):89–107

    Google Scholar 

  • Rasul F, Gull U, Rahman MH, Hussain Q, Chaudhary HJ, Matloob A, Shahzad S, Iqbal S, Shelia V, Masood S, Bajwa HM (2016) Biochar an emerging technology for climate change mitigation. J Environ Agric Sci 9:37–43

    Google Scholar 

  • Raza A, Ahmad M (2015) Analysing the impact of climate change on cotton productivity in Punjab and Sindh, Pakistan. Pakistan Institute of Development Economics (PIDE), Islamabad, Pakistan, pp 1–32

    Google Scholar 

  • Reddy KR, Zhao D (2005) Interactive effects of elevated CO2 and potassium deficiency on photosynthesis, growth, and biomass partitioning of cotton. Field Crop Res 94:201–213

    CrossRef  Google Scholar 

  • Reddy KR, Doma PR, Mearns LO, Boone MYL, Hodges HF, Richardson AG, Kakani VG (2002) Simulating the impacts of climate change on cotton production in the Mississippi delta. Clim Res 22:271–281

    CrossRef  Google Scholar 

  • Reddy KR, Koti S, Davidonis GH, Reddy VR (2004) Interactive effects of carbon dioxide and nitrogen nutrition on cotton growth, development, yield, and fiber quality. Agronomy 96:1148–1157

    CrossRef  Google Scholar 

  • Reddy KC, Malik RK, Reddy SS, Nayakatawa EZ (2007) Cotton growth and yield response to nitrogen applied through fresh and composted poultry litter. J Cotton Sci 11:26–34

    Google Scholar 

  • Rosenzweig C, Elliott J, Deryng D, Ruane AC, Müller C, Arneth A, Boote KJ, Folberth C, Glotter M, Khabarov N, Neumann K, Piontek F, Pugh TAM, Schmid E, Stehfest E, Yang H, Jones JW (2014) Assessing agricultural risks of climate change in the 21st century in a global gridded crop model inter comparison. Proc Natl Acad Sci U S A 111:3268–3273

    CAS  PubMed  CrossRef  Google Scholar 

  • Ruane AC, Cecil LD, Horton RM, Gordón R, McCollum R, Brown D, Killough B, Goldberg R, Greeley AP, Rosenzweig C (2013) Climate change impact uncertainties for maize in Panama: farm information, climate projections, and yield sensitivities. Agric For Meteorol 170:132–145

    CrossRef  Google Scholar 

  • Ruane AC, Goldberg R, Chryssanthacopoulos J (2015a) Climate forcing datasets for agricultural modeling: merged products for gap-filling and historical climate series estimation. Agric For Meteorol 200:233–248

    CrossRef  Google Scholar 

  • Ruane AC, Winter JM, McDermid SP, Hudson NI (2015b) AgMIP climate datasets and scenarios for integrated assessment. In: Rosenzweig C, Hillel D (eds) Handbook of climate change and agroecosystems: the agricultural model inter comparison and improvement project (AgMIP) integrated crop and economic assessments, Part 1, ICP series on climate change impacts, adaptation, and mitigation, vol 3. Imperial College Press, London, pp 45–78

    CrossRef  Google Scholar 

  • Sala S (2009) Information and communication technologies for climate change adaptation, with a focus on the agricultural sector. In: Thinkpiece for CGIAR science forum workshop on “ICTs transforming agricultural science, research and technology generation” Wageningen, Netherlands, pp 16–17

    Google Scholar 

  • Singh RP, Vara Prasad PV, Sunita K, Giri SN, Reddy KR (2007) Influence of high temperature and breeding for heat tolerance in cotton: a review. Adv Agron 93:313–385

    CAS  CrossRef  Google Scholar 

  • Tariq M, Yasmeen A, Ahmad S, Hussain N, Afzal MN, Hasanuzzaman M (2017) Shedding of fruiting structures in cotton: factors, compensation and prevention. Trop Subtrop Agroecosyst 20(2):251–262

    Google Scholar 

  • Tariq M, Afzal MN, Muhammad D, Ahmad S, Shahzad AN, Kiran A, Wakeel A (2018) Relationship of tissue potassium content with yield and fiber quality components of Bt cotton as influenced by potassium application methods. Field Crop Res 229:37–43

    CrossRef  Google Scholar 

  • Turner NC (1979) Drought resistance and adaptation to water deficits in crop plants. In: Mussell H, Staples RC (eds) Stress physiology in crop plants. Wiley, New York, pp 343–372

    Google Scholar 

  • USDA (United States Department of Agriculture) (2018) Pakistan sugar annual report. Global Agricultural Information Network. https://gain.fas.usda.gov

  • Usman M, Ahmad A, Ahmad S, Irshad M, Khaliq T, Wajid A, Hussain K, Nasim W, Chattha TM, Trethowan R, Hoogenboom G (2009) Development and application of crop water stress index for scheduling irrigation in cotton (Gossypium hirsutum L.) under semiarid environment. J Food Agric Environ 7(3&4):386–391

    Google Scholar 

  • Van Vuuren DP, Edmonds J, Kainuma M et al (2011) The representative concentration pathways: an overview. Clim Chang 109:5. https://doi.org/10.1007/s10584-011-0148-z

    CrossRef  Google Scholar 

  • Vara Prasad PV, Allen LH, Boote KJ (2005) Crop responses to elevated carbon dioxide and interactions with temperature. J Crop Improv 13:113–155

    CrossRef  Google Scholar 

  • Wajid A, Ahmad A, Hussain M, Rahman MH, Khaliq T, Mubeen M, Rasul F, Bashir U, Awais M, Iqbal J, Sultana SR, Hoogenboom G (2014) Modeling growth, development and seed-cotton yield for varying nitrogen increments and planting dates using DSSAT. Pak J Agric Sci 51:639–647

    Google Scholar 

  • Walker P, White DH (2001) INSIGHT: a framework for determining impacts of changes in land and water policies. Environ Int 27:127–132

    CAS  PubMed  CrossRef  Google Scholar 

  • Wang S, Li X, Lu J, Hong J, Chen G, Xue X, Li J, Wei Y, Zou J, Liu G (2013) Effects of controlled-release urea application on the growth, yield and nitrogen recovery efficiency of cotton. Agric Sci 4:33–38

    Google Scholar 

  • Watto MA, Mugera AW (2015) Econometric estimation of groundwater irrigation efficiency of cotton cultivation farms in Pakistan. J Hydrol Reg Stud 4:193–211

    CrossRef  Google Scholar 

  • Williams A, White N, Mushtaq S, Cockfield G, Power B, Kouadio L (2015) Quantifying the response of cotton production in Eastern Australia to climate change. Clim Chang 129:183–196

    CAS  CrossRef  Google Scholar 

  • Woodfin CA, Rosenow DT, Clark LE, Johnson JW (1979) Differential response of sorghum cultivars to drought stress. Am Soc Agron Abstr, p 82

    Google Scholar 

  • Wrather JA, Phipps BJ, Stevens WE, Phillips AS, Vories ED (2008) Cotton planting date and plant population effects on yield and fiber quality in the Mississippi Delta. J Cotton Sci 12:1–7

    Google Scholar 

  • Zhu T, Ringler C, Iqbal MM, Sulser TB, Goheer MA (2013) Climate change impacts and adaptation options for water and food in Pakistan: scenario analysis using an integrated global water and food projections model. Water Int 38:651–669

    CrossRef  Google Scholar 

  • Zulfiqar F, Datta A, Thapa GB (2017) Determinants and resource use efficiency of “better cotton”: an innovative cleaner production alternative. J Clean Prod 166:1372–1380

    CrossRef  Google Scholar 

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Correspondence to Muhammad Habib ur Rahman .

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Rahman, M.H. et al. (2020). Climate Resilient Cotton Production System: A Case Study in Pakistan. In: Ahmad, S., Hasanuzzaman, M. (eds) Cotton Production and Uses. Springer, Singapore. https://doi.org/10.1007/978-981-15-1472-2_22

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