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Evaluating the relationship between climate variability and agricultural crops under indeterminacy

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This study investigates the climate impact on rice yield. It takes temperature and rain as indicator for climate variation on stages of growth of rice as independent variables and yield of rice as dependent variable. This study uses neutrosophic estimation and compares this with classical estimation. Estimated results show that climate variability is negatively impacting the rice yield and the crop is more vulnerable to variation in temperature than rain. Impact of climate variations on geographical regions is different which also highlights the priority territories which are more vulnerable to climate change. Neutrosophic estimation seems comparatively reliable and gives more information than classical estimation.

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  • Almeselmani M, Deshmukh PS, Sairam RK, Kushwaha SR, Singh TP (2006) Protective role of antioxidant enzymes under high temperature stress. Plant Sci 171(3):382–388

    Article  Google Scholar 

  • Asklany SA, Elhelow K, Youssef IK, El-Wahab MA (2011) Rainfall events prediction using rule-based fuzzy inference system. Atmos Res 101(1–2):228–236

    Article  Google Scholar 

  • Aslam M (2018a) A new sampling plan using neutrosophic process loss consideration. Symmetry 10(5):132

    Article  Google Scholar 

  • Aslam M (2018b) Design of sampling plan for exponential distribution under neutrosophic statistical interval method. IEEE Access 6:64153–64158

    Article  Google Scholar 

  • Aslam M, Albassam M (2019) Application of neutrosophic logic to evaluate correlation between prostate cancer mortality and dietary fat assumption. Symmetry 11(3):330

    Article  Google Scholar 

  • Aznar-Sánchez JA, Piquer-Rodríguez M, Velasco-Muñoz JF, Manzano-Agugliaro F (2019) Worldwide research trends on sustainable land use in agriculture. Land Use Policy 87:104069

    Article  Google Scholar 

  • Bang S, Bishnoi R, Chauhan AS, Dixit AK, Chawla I (2019) Fuzzy logic based crop yield prediction using temperature and rainfall parameters predicted through ARMA, SARIMA, and ARMAX models. In 2019 Twelfth International Conference on Contemporary Computing (IC3) (pp. 1–6). IEEE

  • Bocchiola D, Brunetti L, Soncini A, Polinelli F, Gianinetto M (2019) Impact of climate change on agricultural productivity and food security in the Himalayas: a case study in Nepal. Agric Syst 171:113–125

    Article  Google Scholar 

  • Brown PR, Afroz S, Chialue L, Chiranjeevi T, El S, Grünbühel CM, Sacklokham S (2019) Constraints to the capacity of smallholder farming households to adapt to climate change in South and Southeast Asia. Clim Dev 11(5):383–400

    Article  Google Scholar 

  • Cao F, Dan L, Ma Z, Gao T (2020) Assessing the regional climate impact on terrestrial ecosystem over East Asia using coupled models with land use and land cover forcing during 1980–2010. Sci Rep 10(1):1–15

    Article  Google Scholar 

  • Centeno Maldonado PA, Puertas Martinez Y, Escobar Valverde GS, Inca Erazo JD (2019) Neutrosophic statistics methods applied to demonstrate the extra-contractual liability of the state from the Administrative Organic Code Neutrosophic Sets & Systems, 26

  • Chen J, Ye J, Du S, Yong R (2017) Expressions of rock joint roughness coefficient using neutrosophic interval statistical numbers. Symmetry 9(7):123

    Article  Google Scholar 

  • Chen Z, Wang W, Fu J (2020) Vegetation response to precipitation anomalies under different climatic and biogeographical conditions in China. Sci Rep 10(1):1–16

    Article  Google Scholar 

  • Coulter L, Serrao-Neumann S, Coiacetto E (2019) Climate Change Adaptation Narratives: Linking climate knowledge and future thinking. Futures

  • Degani E, Leigh SG, Barber HM, Jones HE, Lukac M, Sutton P, Potts SG (2019) Crop rotations in a climate change scenario: short-term effects of crop diversity on resilience and ecosystem service provision under drought. Agric Ecosyst Environ 285:106625

    Article  Google Scholar 

  • Deschênes O, Greenstone M (2007) The economic impacts of climate change: evidence from agricultural output and random fluctuations in weather. Am Econ Rev 97(1):354–385

    Article  Google Scholar 

  • Dixit P, Ahmed RR, Yadav AK, Lal RC (2019) Diversification of economy-an insight into inclusive growth & food security with special reference to Pakistan’s agriculture economy. Asian Journal of Agriculture and Rural. Development 9(1):82–98

    Google Scholar 

  • Dudu H, Çakmak EH (2018) Climate change and agriculture: an integrated approach to evaluate economy-wide effects for Turkey. Clim Dev 10(3):275–288

    Article  Google Scholar 

  • Eckstein D, Hutfils ML, Winges M (2019) Global climate risk index 2019. Germanwatch eV, Bonn

    Google Scholar 

  • Fandjinou K, Zhang KB, Folega F, Mukete B, Yang XH, Wala K, Akpagana K (2019) Analysis of climate variability and its relations to vegetation dynamics in Togo, western Africa from 1984 to 2017. Appl Ecol Environ Res 17(3):6761–6781

    Article  Google Scholar 

  • Gaupp F, Hall J, Mitchell D, Dadson S (2019) Increasing risks of multiple breadbasket failure under 1.5 and 2° C global warming. Agric Syst 175:34–45

    Article  Google Scholar 

  • Hasan MM, Alauddin M, Sarker MAR, Jakaria M, Alamgir M (2019) Climate sensitivity of wheat yield in Bangladesh: Implications for the United Nations sustainable development goals 2 and 6. Land Use Policy 87:104023

    Article  Google Scholar 

  • He LX, Chen YL, Zhang TT, Zheng AX, Cheng Y, Du P et al (2019) Effects of different temperature conditions on yield and physiological properties of rice (Oryza Sativa L.). Appl Ecol Environ Res 17(1):199–211

    Article  Google Scholar 

  • Intergovernmental Panel on Climate Change (2018) Global warming of 1.5° C: an IPCC special report on the impacts of global warming of 1.5° C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. Intergovernmental Panel on Climate Change

  • Jain SK, Kumar V, Saharia M (2013) Analysis of rainfall and temperature trends in northeast India. Int J Climatol 33(4):968–978

    Article  Google Scholar 

  • Kale SS, Patil PS (2019) Data mining technology with fuzzy logic, neural networks and machine learning for agriculture. In: Data management, analytics and innovation. Springer, Singapore, pp 79–87

    Chapter  Google Scholar 

  • Keswani B, Mohapatra AG, Mohanty A, Khanna A, Rodrigues JJ, Gupta D, de Albuquerque VHC (2019) Adapting weather conditions based IoT enabled smart irrigation technique in precision agriculture mechanisms. Neural Comput Applic 31(1):277–292

    Article  Google Scholar 

  • Khanal U, Wilson C, Hoang VN, Lee BL (2019) Autonomous adaptations to climate change and rice productivity: a case study of the Tanahun district, Nepal. Clim Dev 11(7):555–563

    Article  Google Scholar 

  • Kobata T, Palta JA, Tanaka T, Ohnishi M, Maeda M, KoÇ M, Barutçular C (2018) Responses of grain filling in spring wheat and temperate-zone rice to temperature: similarities and differences. Field Crop Res 215:187–199

    Article  Google Scholar 

  • Kuchimanchi BR, Nazareth D, Bendapudi R, Awasthi S, D’Souza M (2019) Assessing differential vulnerability of communities in the agrarian context in two districts of Maharashtra, India. Climate and Development, 11(10)L918–929

  • Kunene MN, Mthombeni DL, Antwi MA (2019) Perceptions of small-scale maize farmers on climate change impacts in Hhohho, Manzini and Shiselweni regions of the kingdom of Eswatini. Appl Ecol Environ Res 17(4):7345–7356

    Article  Google Scholar 

  • Li J, Zhang C, Zheng X, Chen Y (2020) Temporal-spatial analysis of the warming effect of different cultivated land urbanization of metropolitan area in China. Sci Rep 10(1):1–17

    Article  Google Scholar 

  • Mclntyre BD, Herren HR, Wakhungu J, Watson RT (2009) Global report (No. 338.927 G562). International Assessment of Agricultural Knowledge, Science and Technology for Development, Washington, DC (EUA)

  • Nair KP (2019) Achieving agricultural sustainability–the future challenge. Intelligent soil management for sustainable agriculture. Springer, Cham, pp 319–325

    Book  Google Scholar 

  • Olivier DW (2019) Urban agriculture promotes sustainable livelihoods in Cape Town. Dev South Afr 36(1):17–32

    Article  Google Scholar 

  • Pachauri RK, Reisinger A (2008) Climate change 2007. Synthesis report. contribution of working groups I, II and III to the fourth assessment report. Cambridge University Press, Cambridge

    Google Scholar 

  • Pakistan Economic Survey (2018–2019) Ministry of Finance, Government of Pakistan

  • Poortinga W, Whitmarsh L, Steg L, Böhm G, Fisher S (2019) Climate change perceptions and their individual-level determinants: a cross-European analysis. Glob Environ Chang 55:25–35

    Article  Google Scholar 

  • Saha S, Gayen A, Pourghasemi HR, Tiefenbacher JP (2019) Identification of soil erosion-susceptible areas using fuzzy logic and analytical hierarchy process modeling in an agricultural watershed of Burdwan district, India. Environ Earth Sci 78(23):649

    Article  Google Scholar 

  • Santika T, Wilson KA, Budiharta S, Law EA, Poh TM, Ancrenaz M, Meijaard E (2019) Does oil palm agriculture help alleviate poverty? A multidimensional counterfactual assessment of oil palm development in Indonesia. World Dev 120:105–117

    Article  Google Scholar 

  • Scott GJ, Petsakos A, Juarez H (2019) Climate change, food security, and future scenarios for potato production in India to 2030. Food Security 11(1):43–56

    Article  Google Scholar 

  • Sierra Morán JC, Enríquez Chuga JF, Arias Collaguazo WM, Maldonado Gudiño CW (2019) Neutrosophic statistics applied to the analysis of socially responsible participation in the community. Neutrosophic Sets Syst 26(1):4

    Google Scholar 

  • Smarandache F (2010) Neutrosophic logic-a generalization of the intuitionistic fuzzy logic Multispace & multistructure Neutrosophic transdisciplinarity, 4, 396

  • Smarandache F (2014) Introduction to neutrosophic statistics. Infinite Study

  • Smarandache F (2019) Nidus Idearum de Neutrosophia, Editions Pons. Bruxelles 1–7:2016–2019

    Google Scholar 

  • Thrillwall AP (2011) Economics of development: theory and evidence, 9th edn. Palgrave-Macmillan

  • Wang Y, Dang F, Zheng X, Zhong H (2019) Biochar amendment to further reduce methylmercury accumulation in rice grown in selenium-amended paddy soil. J Hazard Mater 365:590–596

    Article  Google Scholar 

  • Willer H, Lernoud J (eds) (2019) The World of organic agriculture. Statistics and emerging trends 2019. Research Institute of Organic Agriculture (FiBL), Frick and IFOAM – Organics International, Bonn

    Google Scholar 

  • Xing Y, Wang J, Shaheen SM, Feng X, Chen Z, Zhang H, Rinklebe J (2020) Mitigation of mercury accumulation in rice using rice hull-derived biochar as soil amendment: A field investigation. Journal of Hazardous Materials 388:121747.

  • Yawson DO, Adu MO, Armah FA (2020) Impacts of climate change and mitigation policies on malt barley supplies and associated virtual water flows in the UK. Sci Rep 10

  • Yongkai X, Wang C, Wude Y, Meichen F, Xingxing Q, Jinyao S (2020) Canopy hyperspectral characteristics and yield estimation of winter wheat (Triticum aestivum) under low temperature injury. Sci Rep (Nature Publisher Group) 10(1)

  • Zaja M, Angelova E (2019) Biomass from agriculture as renewable energy source in the Republic of Macedonia. J Hyg Eng Des 26:71–75

    Google Scholar 

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The authors are deeply thankful to the editor and reviewers for their valuable comments to improve the quality of the paper.

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Table 1 Yield and climate observations during rice phenology
Table 2 Summary statistics of classical analysis
Table 3 Summary statistics for neutrosophic analysis
Table 4 Classical correlation matrix
Table 5 Neutrosophic correlation matrix
Table 6 Comparison of neutrosophic and classical estimation

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Janjua, A.A., Aslam, M. & Sultana, N. Evaluating the relationship between climate variability and agricultural crops under indeterminacy. Theor Appl Climatol 142, 1641–1648 (2020).

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