Hostname: page-component-cd9895bd7-gbm5v Total loading time: 0 Render date: 2024-12-25T01:31:01.309Z Has data issue: false hasContentIssue false
  • English
  • Français

Near-term impact of climate variability on yam rot incidence over a humid tropical region: projections in CORDEX-Africa scenarios

Published online by Cambridge University Press:  05 April 2021

Ugochukwu K. Okoro Open the ORCID record for Ugochukwu K. Okoro [Opens in a new window] ,
Jacinta N. Akalazu  and
Nobert C. Nwulu
Ugochukwu K. Okoro*
Affiliation:
Atmospheric Physics Group, Department of Physics, Imo State University, Owerri, Nigeria
Jacinta N. Akalazu
Affiliation:
Department of Plant Science and Biotechnology, Imo State University, Owerri, Nigeria
Nobert C. Nwulu
Affiliation:
Atmospheric Physics Group, Department of Physics, Imo State University, Owerri, Nigeria
*
Author for correspondence: Ugochukwu K. Okoro, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

The global population is projected to be enormous by the mid-21st century, whereas, most essential crops being sustained by the rain-fed agriculture are threatened by climate change. Therefore, the study investigated the projected near-future effect of rainfall variability on rot incidence and yam production in humid tropical Nigeria. Production data from the Food and Agriculture Organization and the Nigeria National Bureau of Statistics showed the significant increasing trend in the annual yam output. The field survey conducted in 2018 showed that the maximum percentage of rot incidence occurred in July. Climate Research Unit observational rainfall data from 1979 to 2018 showed the nonsignificant trend in the interannual rainfall variability; however, it showed low variability and a significant decreasing trend in the July rainfall. A pathogenicity test on yam samples confirmed rot by fungi, bacteria and nematodes as virulent pathogens, whereas, the nutritional qualities of the rotted yams were indicated. Monthly rainfall and rot incidence showed positive correlation (r = 0.84, significant at 99% from t-test). The positive characteristic impact values indicated that increase (decrease) in the monthly rainfall corresponds to increase (decrease) in the magnitude of monthly percentage rot incidence. Thus, the significantly decreasing rainfall reduced the quantity of rot incidence and consequently increased the annual yam production for the period. Selected CoOrdinated Regional Downscaling EXperiment-Africa models and the ensemble mean showed a good measure of agreement with observational rainfall in the historical experiments. The efficiencies of the bias-corrected outputs in the representative concentration pathway (RCP) 4.5 and 8.5 indicated improved ‘reasonable’ performances. Bias-corrected projections of the July rainfall showed an increasing trend in both the RCPs, which indicate a potential increase in rot incidence and the consequent decline in annual yam production. The findings are imperative in sustaining the global food supply.

Keywords

Characteristic impactrainfall variabilityregional climate modelsrot incidencetrend
Type
Research Paper
Information
Renewable Agriculture and Food Systems , Volume 36 , Issue 5 , October 2021 , pp. 477 - 490
Check for updates
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Akinsanola, AA and Ogunjobi, KO (2017) Evaluation of present-day rainfall simulations over West Africa in CORDEX regional climate models. Environmental Earth Sciences 76, 366.CrossRefGoogle Scholar
Akinsanola, AA, Ogunjobi, KO, Ajayi, VO, Adefisan, EA, Omotosho, JA and Sanogo, S (2016) Comparison of five gridded precipitation products at climatological scales over West Africa. Meteorology and Atmospheric Physics 129, 669–689.CrossRefGoogle Scholar
Akoroda, MO (1993) Yams: Dioscorea spp. In Kalloo, G and Bergh, BO (eds), Genetic Improvement of Vegetable Crops. Pergamon Press, pp. 717–733.CrossRefGoogle Scholar
Amegbeto, NK, Manyong, VM, Coulibaly, O and Asiedu, R (2008) Estimating market demand for fresh yam characteristics using contingent valuation: implications for crop breeding and production choices. Agricultural Economics 39, 349–363.CrossRefGoogle Scholar
Amusa, NA (2000) Screening cassava and yam cultivars for resistance to anthracnose using toxic metabolite of Colletotrichum species. Mycopathologia 150, 137–142.CrossRefGoogle Scholar
Amusa, NA and Baiyewu, RA (1999) Storage and market disease of yam tubers in southwestern Nigeria. Ogun Journal of Agricultural Research (Nig) 11, 211–225.Google Scholar
Amusa, NA, Adegbite, AA, Muhammed, S and Baiyewu, RA (2003) Yam diseases and its management in Nigeria. African Journal of Biotechnology 2, 497–502.CrossRefGoogle Scholar
Angba, CW, Baines, RN and Butler, AJ (2020) Examining yam production in response to climate change in Nigeria: a co-integration model approach. Social Science 9, 42.CrossRefGoogle Scholar
Anjorin, TS, Nwokocha, OV and Sanni, AD (2014) Morphological characteristics and incidence of diseases of white yam Dioscorea rotundata (L. Poir) tubers in Abuja Nigeria. Nature and Science 17, 58–65.Google Scholar
Bashir, MR, Atiq, M and Mohsan, M (2018) The increasing carbon dioxide (CO2) due to global climate change strengthens the plants and inhibits pathogenic infection. Environmental Science and Pollution Research 25, 26850–26851.CrossRefGoogle ScholarPubMed
Bassey, EE and Akpan, US (2015) Evaluation of Guinea white yam (Dioscorea rotundata Poir.) for yield and yield components in Nigeria. American Journal of Experimental Agriculture 8, 216–223.CrossRefGoogle Scholar
Bekele, A and Bekele, E (2018) Proximate and mineral composition variability in Ethiopian yam (Dioscorea spp.). Journal of Food and Nutrition Sciences 6, 12–17.CrossRefGoogle Scholar
Bergh, K, Orozco, P, Gugerty, MK and Anderson, CL (2019) Yam value chain Nigeria. Gates Open Research 3, 1–28.Google Scholar
Buzby, JC and Hyman, J (2012) Total and per capita value of food loss in the United States. Food Policy 37, 561–570.CrossRefGoogle Scholar
Chen, X, Wang, L, Niu, Z, Zhang, M, Li, C and Li, J (2020) The effects of projected climate change and extreme climate on maize and rice in the Yangtze River Basin, China. Agricultural and Forest Meteorology 282, 107867.CrossRefGoogle Scholar
Claudius-Cole, AO, Omotayo, TO and Montes, AL (2020) Nodal vine cutting technique for assessing nematode resistance in yams. Tropical Plant Pathology 45, 56–63. doi: doi.org/10.1007/s40858-019-00325-9.CrossRefGoogle Scholar
Dania, VO, Fadina, OO, Ayodele, M and Kumar, PL (2016) Evaluation of isolates of Trichoderma, Pseudomonas and Bacillus species as treatment for the control of post-harvest fungal rot disease of yam (Dioscorea spp.). Archives of Phytopathology and Plant Protection 49, 456–470.CrossRefGoogle Scholar
Dania, VO, Fadina, OO, Ayodele, M and Kumar, PL (2019) Distribution and virulence of fungal species isolated from yam (Dioscorea spp.) tubers in three agroecological zones of Nigeria. International Journal of Pest Management 66, 252–261. doi: doi.org/10.1080/09670874.2019.1629041.CrossRefGoogle Scholar
Diallo, I, Giorgi, F, Deme, A, Tall, M, Mariotti, L and Gaye, AT (2016) Projected changes of summer monsoon extremes and hydroclimatic regimes over West Africa for the twenty-first century. Climate Dynamics 47, 3931–3954.CrossRefGoogle Scholar
Ejechi, BO and IIondu, ME (1999) Control of yam tuber (Dioscorea rotundata) rot agent Sclerotium rolfsii with Camwood (Baphia nitida Lodd) sawdust extract. African Journal of Root Tuber Crops 3, 13–15.Google Scholar
Enesi, RO, Hauser, S, Lopez-Montez, A and Osonubi, O (2018) Yam tuber and maize grain yield response to cropping system intensification in south-west Nigeria. Archives of Agronomy and Soil Science 64, 953–966.CrossRefGoogle Scholar
Etejere, EO and Bhat, RB (1986) Traditional and modern storage methods of underground root and stem crops in Nigeria. Turriaba 36, 33–37.Google Scholar
Eze, SC, Umeh, SI, Ugwuoke, KI, Ameh, GI and Onyeke, CC (2015) The potentials of pre-storage curing and nanobiotectnology in the control of postharvest losses of yam (Dioscorea rotundata Poir.) tuber. International Journal of Biosciences 6, 40–47.Google Scholar
Ezeonu, CS, Imo, C, Agwaranze, DI, Iruka, A and Joseph, A (2018) Antifungal effect of aqueous and ethanolic extracts of neem leaves, stem bark and seeds on fungal rot diseases of yam and cocoyam. Chemical and Biological Technologies in Agriculture 5, 18.CrossRefGoogle Scholar
Ezulike, TO, Udealor, A, Nwosu, KI and Asumugha, GN (2006) Rapid multiplication of seed yam by mini sett technique. Extension Guide No. 15, Extension Service Programme, National Root Crops Research Institute, Umudike, Nigeria, 1–10.Google Scholar
Fan, D, Zhong, H, Hu, B, Tian, Z, Sun, L, Fischer, G, Wang, X and Jiang, Z (2020) Agro-ecological suitability assessment of Chinese medicinal yam under future climate change. Environmental Geochemistry and Health 42, 987–1000.CrossRefGoogle ScholarPubMed
FAO (2019) Food and Agriculture Organization of the United Nations Statistics. Available at http://fao.org/faostatsite/en/#home.Google Scholar
FRNOG (2007) Legal notice on publication of the details of the breakdown of the national and state provisional totals 2006 census. Federal Republic of Nigeria Official Gazette 94, B175–B198.Google Scholar
Gilbert, RO (1987) Statistical Methods for Environmental Pollution Monitoring. New York: Van Nostrand Reinhold, p. 320.Google Scholar
Giorgi, F and Gutowski, WJ Jr (2015) Regional dynamical downscaling and the CORDEX initiative. Annual Review of Environment and Resources 40, 467–490.CrossRefGoogle Scholar
Giorgi, F and Mearns, LO (1999) Introduction to special section: regional climate modeling revisited. Journal of Geophysical Research: Atmospheres 104, 6335–6352.CrossRefGoogle Scholar
Gwa, VI and Abdulkadir, KH (2017) Biological control using Trichoderma harzianum against Penicillium purpurogenum, causal agent of white yam tuber (Dioscorea rotundata Poir) Rb. Journal of Bioresearch Communications 1, e106.Google Scholar
Gwa, VI and Ekefan, EJ (2017) Fungal organisms isolated from rotted white yam (Dioscorea rotundata) tubers and antagonistic potential of Trichoderma harzianum against Colletotrichum species. Agricultural Research & Technology: Open Access Journal 10, 555787.Google Scholar
Harris, IC and Jones, PD (2017) CRU TS4.01: Climatic Research Unit (CRU) Time-Series (TS) version 4.01 of high-resolution gridded data of month-by-month variation in climate (Jan. 1901–Dec. 2016). Centre for Environmental Data Analysis, December 4, 2017. doi: doi.org/10.5285/58a8802721c94c66ae45c3baa4d814d0.Google Scholar
Herrera, R, Verdecia, DM, Ramirez, JL, Garcia, M and Cruz, AM (2017) Secondary metabolites of Leucaena leucochephala. Their relationship with some climate elements, different expressions of digestibility and primary metabolites. Cuban Journal of Agricultural Science 51, 107–116.Google Scholar
Ibeawuchi, II and Ofoh, MC (2003) Effects of maize/cassava/food legume mixtures in soil nutrient status and weed control. Bionature 23, 59–64.Google Scholar
IITA (2013) International Institute for Tropical Agriculture. Healthy yam Seed Production. Ibadan: IITA Publications.Google Scholar
Ike, PC and Inoni, OE (2006) Determinants of yam production and economic efficiency among small-holder farmers in southeastern Nigeria. Journal of Central European Agriculture 7, 337–342.Google Scholar
Jacob, D, Elizalde, A, Haensler, A, Hagemann, S, Kumar, P, Podzun, R, Rechid, D, Remedio, AR, Saeed, F, Sieck, K and Teichmann, C (2012) Assessing the transferability of the regional climate model REMO to different coordinated regional climate downscaling experiment (CORDEX) regions. Atmosphere 3, 181–199CrossRefGoogle Scholar
Kader, AA (2005) Increasing food availability by reducing post harvest losses of fresh produce. Acta Horticulture 682, 2169–2176.CrossRefGoogle Scholar
Katung, PD, Idem, NUA and Onyibe, JE (2006) In Idem, NUA and Showemimo, FA (eds), Tuber and Fibre Crops of Nigeria. Principles of Production and Utilization, vol. XXII. Zaria: Ade Commercial Press, p. 239.Google Scholar
Knoben, WJM, Freer, JE and Woods, RA (2019) Technical note: inherent benchmark or not? Comparing Nash–Sutcliffe and Kling–Gupta efficiency scores. Hydrology and Earth System Sciences 23, 4323–4331.CrossRefGoogle Scholar
Kolombia, YA, Karssen, G, Viaene, N, Kumar, PL, De Sutter, N, Joos, L, Coyne, DL and Bert, W (2017) Diversity of root-knot nematodes associated with tubers of yam (Dioscorea spp.) established using isozyme analysis and mitochondrial DNA-based identification. Journal of Nematology 49, 177–188.CrossRefGoogle ScholarPubMed
Kolombia, YA, Kumar, PL, Adewuyi, O, Korie, S, Viaene, N, Bert, W and Coyne, DL (2020) Distribution, prevalence and severity of damages caused by nematodes on yam (Dioscorea rotundata) in Nigeria. Nematropica 50, 1–18.Google Scholar
Kumar, AS, Reddy, NPE, Reddy, KH and Devi, MC (2007) Evaluation of fungicidal resistance among Colletotrichum gloeosporioides isolates causing mango anthracnose in Agric. Export zone of Andhra Pradesh, India. Plant Pathology Bulletin 16, 157–160.Google Scholar
Manners, R and van Etten, J (2018) Are agricultural researchers working on the right crops to enable food and nutrition security under future climates? Global Environmental Change 53, 182–194.CrossRefGoogle Scholar
Manyong, VM, Smith, J, Weber, G, Jagtap, SS and Oyewole, B (1996) Macro-characterization of agricultural systems in West Africa. An overview. Resource and Crop Management Monograph No. 21, IITA, Ibadan, Nigeria.Google Scholar
Maule, CF (2014) Presentation of the DMI-HIRHAM5 CORDEX AFRICA-44 simulation-v2, September, 2014. Danish Meteorological Institute. Danish Climate Centre Report number, 14-02.Google Scholar
Meinshausen, M, Smith, SJ, Calvin, K, Daniel, JS, Kainuma, MLT, Lamarque, JF, Matsumoto, K, Montzka, SA, Raper, SCB, Riahi, K and Thomson, AGJMV (2011) The RCP greenhouse gas concentrations and their extensions from 1765 to 2300. Climatic Change 109, 213–241.CrossRefGoogle Scholar
Mignouna, DB, Abdoulaye, T, Alene, A, Aighewi, B, Pelemo, O, Manyong, VM, Asiedu, R and Akoroda, M (2013) Economic analysis of seed yam production systems in Nigeria. Journal of Root Crops 39, 221–229.Google Scholar
Mounkaila, MS, Abiodun, BJ and Omotosho, JB (2015) Assessing the capability of CORDEX models in simulating onset of rainfall in West Africa. Theoretical and Applied Climatology 119, 255–272.CrossRefGoogle Scholar
Nath, R, Cui, X, Nath, D, Graf, HF, Chen, W, Wang, L, Gong, H and Li, Q (2017) CMIP5 multimodel projections of extreme weather events in the humid subtropical Gangetic plain region of India. Earth's Future 5, 224–239.CrossRefGoogle Scholar
NBS (2019) National Bureau of Statistics Brief. Yam Consumption and Production in Nigeria. The Living Standards Measurement Study-Integrated Surveys on Agriculture (LSMS-ISA) Project. NBS Publications. Available at https://nigerianstat.gov.ng.Google Scholar
Nikiema, PM, Sylla, MB, Ogunjobi, K, Kebe, I, Gibba, P and Giorgi, F (2017) Multi-model CMIP5 and CORDEX simulations of historical summer temperature and precipitation variabilities over West Africa. International Journal of Climatology 37, 2438–2450.CrossRefGoogle Scholar
Nwaobiala, CU and Nottidge, DO (2015) Effect of climate variability on output of cassava in Abia State, Nigeria. Nigeria Agricultural Journal 46, 81–86.Google Scholar
Nweke, FU (2015) Some fungal pathogens of yam (Dioscorea spp.) in storage and the effects of their infection on the nutrient composition. Journal of Biology, Agriculture and Healthcare 5, 153–157.Google Scholar
Nwokocha, CO, Okoro, UK and Usoh, CI (2018) Photovoltaics in Nigeria—awareness, attitude and expected benefit based on a qualitative survey across regions. Renewable Energy 116, 176–182.CrossRefGoogle Scholar
Nyadanu, D, Dapaah, H and Agyekum, AD (2014) Resistance to post-harvest microbial rot in yam: integration of genotype and storage methods. African Crop Science Journal 22, 89–95.Google Scholar
Ogali, EL, Opadokun, JS and Okobi, AO (1991) Effect of lime and local gin on postharvest rot of yam. Tropical Science 31, 365–370.Google Scholar
Ogundana, SK, Naqvi, SHZ and Ekundayo, JA (1970) Fungi associated with soft rot of yam (Dioscorea spp.) in storage in Nigeria. Transactions of the British Mycological Society 54, 485–451.CrossRefGoogle Scholar
Ogungbenro, SB and Morakinyo, TE (2014) Rainfall distribution and change detection across climatic zones in Nigeria. Weather and Climate Extremes 5–6, 1–6.CrossRefGoogle Scholar
Okigbo, RN (2005) Biological control of postharvest fungal rot of yam (Dioscorea spp.) with Bacillus subtilis. Mycopathologia 159, 307–314.CrossRefGoogle Scholar
Okigbo, RN and Ikediugwu, EO (2002) Evaluation of water loss in different regions of yam (Dioscorea rotundata) tuber storage in Nigeria. Journal of Experimental and Applied Biology 3, 317–321.Google Scholar
Okigbo, RN, Chukwuma, NG and Ani, SE (2017) Fungitoxic attributes of Chromolaena odorata and Mimosa pudica leaf extracts on the pathogens causing yam rot. Nigeria Journal of Mycology 9, 95–104.Google Scholar
Okoedo-Okojie, DU and Onemolease, EA (2009) Factors affecting the adoption of yam storage technologies in the northern ecological zone of Edo state, Nigeria. Journal of Human Ecology 27, 155–160.CrossRefGoogle Scholar
Okoro, UK, Chen, W, Chineke, C and Nwofor, O (2014) Comparative analysis of gridded datasets and gauge measurements of rainfall in the Niger Delta region. Research Journal of Environmental Sciences 8, 373–390.CrossRefGoogle Scholar
Okoro, UK, Chen, W, Nath, D and Nnamchi, HC (2020) Variability and trends of atmospheric moisture in recent West African monsoon season and the coordinated regional downscaling experiment-Africa projected 21st century scenarios. International Journal of Climatology 40, 1149–1163.CrossRefGoogle Scholar
Olabiyi, TI, Afolabi, EA, Adewole, EI and Omomowo, IO (2017) Impact assessment of climate change on crop diseases incidence and severity in Nigeria. In Leal Filho, W, Belay, S, Kalangu, J, Menas, W, Munishi, P and Musiyiwa, K (eds), Climate Change Adaptation in Africa. Cham: Springer, pp. 235–244.CrossRefGoogle Scholar
Olasantan, FO (1999) Effect of time of mulching on soil temperature and moisture regime and emergence, growth and yield of white yam in western Nigeria. Soil & Tillage Research 50, 215–221.CrossRefGoogle Scholar
Oluwatayo, IB and Ojo, AO (2016) Awareness and adaptation to climate change among yam-based farmers in rural Oyo state, Nigeria. The Journal of Developing Areas 50, 97–108.CrossRefGoogle Scholar
Osunde, ZD and Orhevba, BA (2009) Effects of storage conditions and storage period on nutritional and other qualities of stored yam (Dioscorea spp.) tubers. African Journal of Food Agriculture Nutrition and Development 9, 678–690.CrossRefGoogle Scholar
Otusanya, MO and Jeger, MJ (1996) Effect of Aspergillus niger on shoot emergence and vine development in field-sown yams (Dioscorea spp.) and rot development under long-term storage conditions. International Biodeterioration & Biodegradation 38, 89–100.CrossRefGoogle Scholar
Panitz, HJ, Dosio, A, Büchner, M, Lüthi, D and Keuler, K (2014) COSMO-CLM (CCLM) climate simulations over CORDEX-Africa domain: analysis of the ERA-interim driven simulations at 0.44 and 0.22 resolution. Climate Dynamics 42, 3015–3038.CrossRefGoogle Scholar
Rosenzweig, C, Elliot, J, Deryng, D, Ruane, AC, Muller, C, Arneth, A, Boote, KJ, Folberth, C, Glotter, M, Khabarov, N and Neumann, K (2014) Assessing agricultural risks of climate change in the 21st century in a global gridded crop model intercomparison. Proceedings of the National Academy of Sciences of the United States of America 111, 3268–3273.CrossRefGoogle Scholar
Samuelsson, P, Jones, CG, Willén, U, Ullerstig, A, Gollvik, S, Hansson, ULF, Jansson, C, Kjellström, E, Nikulin, G and Wyser, K (2011) The Rossby Centre regional climate model RCA3: model description and performance. Tellus A 63, 4–23.CrossRefGoogle Scholar
Sanogo, S, Fink, AH, Omotosho, JA, Ba, A, Redl, R and Ermert, V (2015) Spatio-temporal characteristics of the recent rainfall recovery in West Africa. International Journal of Climatology 35, 4589–4605.CrossRefGoogle Scholar
Shiriki, D, Obochi, GO, Eke, MO and Shambe, T (2017) Postharvest loss control: synergistic plants extract inhibition of ten microbial yam rot organisms. Food and Nutrition Sciences 8, 725–732.CrossRefGoogle Scholar
Shiwachi, H, Kikuno, H, Fashola, R and Asiedu, R (2008) Enhancing off-season yam production in Nigeria. African Journal of Agricultural Research 3, 407–411.Google Scholar
Sidibe, M, Dieppois, B, Eden, J, Mahe, G, Paturel, JE, Amoussou, E, Anifowose, B, Van De Wiel, M and Lawler, D (2020) Near-term impacts of climate variability and change on hydrological systems in west and Central Africa. Climate Dynamics 54(3), 2041–2070. doi: doi.org/10.1007/s00382-019-05102-7.CrossRefGoogle Scholar
Sonder, K, Okonkwo, CC and Asiedu, R (2010) Predicted changes in suitability and agro climatic factors due to climate change for yam production in Nigeria. African Journal of Root and Tuber Crops 8, 51–59.Google Scholar
Sotomayor-Ramirez, D, Gonzalez-Velez, A and Roman-Paoli, E (2003) Yam (Dioscorea spp.) response to fertilization in soils of the semiarid southern coast of Puerto Rico. Journal of Agriculture of the University of Puerto Rico 87, 91–103.CrossRefGoogle Scholar
Srivastava, AK, Gaiser, T, Paeth, H and Ewert, F (2012) The impact of climate change on yam (Dioscorea alata) yield in the savanna zone of West Africa. Agriculture, Ecosystems and Environment 153, 57–64.CrossRefGoogle Scholar
Sun, Q, Miao, C, Duan, Q, Ashouri, H, Sorooshian, S and Hsu, K-L (2018) A review of global precipitation data sets: data sources, estimation, and intercomparisons. Reviews of Geophysics 56, 79–107.CrossRefGoogle Scholar
Tribune (2018) Yam export: Committee targets USD10 billion earnings. Nigerian Tribune, July 17. Available at https://tribuneonlineng.com.Google Scholar
UNDP (2015) National Human Development Report, Human Security and Human Development in Nigeria, UNDP:144.Google Scholar
van den Hurk, B, Siegmund, P and Tank, AK (eds) (2014) KNMI'14: Climate change scenarios for the 21st century—A Netherlands perspective. KNMI. Scientific Report Number, WR2014-01.Google Scholar
Velasquez, AC, Castroverde, CDM and He, SY (2018) Plant—pathogen warfare under changing climate conditions. Current Biology 28, R619–R634.CrossRefGoogle ScholarPubMed
Verte, N and Bečvařova, V (2015) An analysis of yam production in Nigeria. Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis 63, 659–665.CrossRefGoogle Scholar
Wei, J, Su, H and Yang, ZL (2016) Impact of moisture flux convergence and soil moisture on precipitation: a case study for the southern United States with implications for the globe. Climate Dynamics 46, 467–481.CrossRefGoogle Scholar
Wheatley, C, Scott, GJ, Best, R and Wisesema, S (1995) Adding Value to Root and Tuber Crops. A Manual on Product Development. Cali (Columbia): Centro International de Agriculture Tropical (CIAT).Google Scholar
WMO (2012) World Meteorological Organization: Standardized precipitation index user guide (Svoboda M, Hayes M and Wood D). (WMO-No. 1090), Geneva, p. 16.Google Scholar