Pa ge 1 Pa ge 91 American Journal of Environment and Climate (AJEC) Relationship between Climate Variables (Rainfall and Temperature) and Ginger Yield Across the Climate Belts of Nigeria Okoye N. N.1*, Nwagbara M. O.2, Weli V. E.3 Volume 2 Issue 3, Year 2023 ISSN: 2832-403X (Online) DOI: https://doi.org/10.54536/ajec.v2i3.1846 https://journals.e-palli.com/home/index.php/ajec Article Information ABSTRACT Received: September 27, 2023 Accepted: October 30, 2023 Published: November 08 2023 Rainfall and temperature are very important elements and factors of weather and climate needed in the successful production of crops, including ginger. The relationship of these elements and ginger yield has not been given the due attention in Nigeria. Therefore, this study examined the relationship between Climate (Rainfall and Temperature) and Ginger Yield across the Climate Belts of Nigeria. Rainfall and Temperaturedata were obtained for the study from Nigerian Meteorological Agency (NiMet), Abuja while ginger yield data were collected from the experimental farms of National Root Crops Research Institute (NRCRI), Umudike, Agricultural Development Programme (ADP) and Nigerian Bureau of Statistics, Abuja. These data covered a period of 40 years (1980 -2019) and were analysed using simple linear regression, correlation and Analysis of Variance (ANOVA). Results obtained showed thatrainfall and temperature significantly predicted ginger yield across the four climate belts at p<0.05:Tropical Monsoon(TM) (F,12.0934)and jointly explained 45.2% of variation in ginger yield(r=.672and the R2=.452);Tropical Savanna (TS)(F,17.3452)and jointly explained 35.6% of variation in ginger yield (r = .597 and R2= .356);Warm Semi-Arid (WSA) (F,24.9501)and jointly explained 20.9% of variation in ginger yield (r= .457 and R2= .209); and Warm Desert (WD)(F,29.8517) and jointly explained 30.1% of variation in ginger yield(r =.549 and R2= .301).Based on these results, it is concluded here that there is a significant relationship between rainfall and temperature and ginger yields over the years and across the climate belts. The study recommends among others that planting and harvesting of ginger by farmers should align with the seasons as found in each of the four climate belts. Keywords Climate Variables, Rainfal, Temperature, Ginger Yield, Climate Belts 1 Agro-met Unit, National Root Crops Research Institute, Umudike, Abia State, Nigeria 2 Department of Water Resources and Agrometeorology, Michael Okpara, University of Agriculture, Umudike, Abia State, Nigeria 3 Department of Geography and Environmental management, University of Port Harcourt, Chuba, Uturu, Abia State, Nigeria * Corresponding author’s e-mail: nkimoore@yahoo.com INTRODUCTION Ginger (Zingiber officinale Rosc.), belonging to the Zingiberaceae family originated from Southeast Asia (Shuhaimi et al., 2012) and has been cultivated for thousands of years for use as a spice and for herbal medicinal purposes (Akram et al., 2011) is a commercially important herbaceous perennial plant, usually grown as an annual spice. It is extensively cultivated in the tropical to temperate climates of the world for its flavour, and pungency, and aromatic and healing characteristics associated with its essential oil and oleoresin contents (Srinivasan et al., 2018). Ginger can be grown under both rainfed and irrigated conditions depending on the frequency and distribution of rainfall (Sharma & Sharma, 2012).The underground rhizomes are thick, hard and much branched, giving rise to primary, secondary and tertiary rhizomes. The mature roots of ginger are fibrous and the juice from old ginger roots is extremely potent and often used as spices and a quintessential ingredient of Chinese, Korea, Japanese and many South Asian cuisines for flavouring dishes (Jakes, 2007). It is also used largely as recipes such as ginger bread, cookies, crackers, cakes, ginger-ale and ginger beer. The medicinal values of these great ancient spices are widely recognized across the continents to contain a number of unique organic phytochemical ingredients that can take care of some human ailments. Recent studies on health related effects of ginger which have also stimulated farmers concern on the growth of the plant have shown the efficacy of the plant in some life challenging ailments such as entero- toxin induced diarrhoea, diabetic nephropathy, nausea, plasma antioxidant, vomiting, high cholesterol, high blood pressure and inflammation (Chen et al., 2019; Ernest and Pittler, 2008; Kim et al., 2010). The current major five exporting countries have been China, Nigeria, India, Jamaica, and Brazil Asumugha (2003). Nigeria is the fifth largest producer of ginger in the world (FAO, 2014) and the largest producer and exporter of ginger in Africa (FAO, 2008). Ginger is one of ten commodities identified by the United States of America International Department (USAID) and Nigerian Export Promotion Council (NEPC) in 2002 as having the greatest potential for creating increased economic growth, external and internal trade, opportunities for employment, and increased income and wealth for Nigerians (Sidi et al., 2014). The cultivation of ginger in recent years especially in the rainforest zone of Nigeria is on the increase (Egbuchua and Enujeke, 2013). For successful cultivation of the ginger, a moderate rainfall at the sowing time till the rhizomes sprout, fairly heavy and well-distributed showers during the growing period, and dry weather with a temperature of 280 to 350C for about a month before harvesting are necessary (Zaied & Zouabi, 2016; Garberof & Jäckering, 2021; Singh, et al., 2022). Temperature above 350C and sunlight can result in leave scorch particularly in young plants on Pa ge 92 https://journals.e-palli.com/home/index.php/ajec Am. J. Environ. Clim. 2(3) 91-100, 2023 the other hand, low temperatures induce dormancy while high humidity throughout the crop period is necessary (Pavlova et al., 2014, Byrnes & Bumb, 2017; Borras, et al., 2022, Salnikov et al., 2022; Karatayev et al., 2022). In Nigeria, ginger is a crop mostly grown in Tropical Savanna climate belt with Kaduna State as the chief producer (Ayodele & Sambo, 2014). Although, in recent times with the increase in population growth and demand, ginger is now being produced in other climate belts of Nigeria particularly in the Tropical Monsoon (such as Abia, Anambra, Cross River, Delta and Imo States), Tropical Savanna which includes Kaduna and Nasarawa States, Warm Semi-arid (Sokoto and Zamfara) and Warm Desert Climate (Bernard 2008, Ayodele & Sambo, 2014). In Nigeria, cultivation of crops is generally rain fed and with significant diurnal and seasonal variations in temperature thus making rainfall and temperature strong factors in crop production in the country. Rainfall does not start at the same time across the country and amounts also vary from the coast hinterland with the coastal areas receiving the highest while the extreme north receives the lowest. The success of ginger cultivation across Nigeria could be said to be largely dependent on rainfall and temperature, which are not only elements of weather and climate but also factors of climate. Despite this and the estimated magnitude of nutritional and potential economic importance of ginger farming in Nigeria, the impact of rainfall and temperature on the yields of ginger across the climate belts of Nigeria has not received the deserved attention. MATERIALS AND METHODS The study area is Nigeria and lies between longitudes 2° 49’E – 14° 37’E and latitudes 4° 16’N – 13° 52’N (Fig. 1). It is bounded on the North by the Republic of Niger, East by Cameroon and West by Benin Republic while the Southern boundary is Gulf of Guinea which is an arm of the Atlantic Ocean (Ofomata, 1975). Nigeria has four climate types following Koppen’s Climate Classification. These climate types are distinguishable from the southern part of Nigeria to the northern part through north- central Nigeria. They are Tropical Monsoon climate (Am), Tropical Savanna climate (Aw), Warm Semi-Arid Climate (Bsh), and Warm Desert Climate (SWh) (but for easy identification of these climate belts in this study, they were recoded as TM, TS, WSA and WD respectively). The Tropical monsoon climate has a very small temperature range. The temperature ranges are almost constant throughout the year. The southern part of Nigeria experiences heavy and abundant rainfall. These storms are usually convectional in nature due to the regions proximity, to the equatorial belt. The annual rainfall received in this region is very high, usually above the 2,000mm (78.7 in) rainfall totals giving for tropical rainforest climates worldwide. Over 4,000 m (157.5 in) of rainfall is received in the coastal region of Nigeria around the Niger delta area (Mmom, 2003).The Tropical Savannah Climate or Tropical Wet and Dry climate, is extensive in area and covers most of Western and north- central parts of Nigeria beginning from the Tropical Monsoon Climate boundary in Southern Nigeria to the Central part of Nigeria, where it exerts enormous influence on the region. This climate exhibits a well- marked rainy season and a dry season with a single peak known as the summer maximum due to its distance from the equator. Temperatures are above 18°C (64 °F) throughout the year (Obasi and Ikubuwaje, 2012). Rainfall total in Tropical Savanna Nigeria varies from 1,100 mm (43.3 in) in the lowlands of the river Niger Benue trough to over 2,000 mm (78.7 in) along the south western escarpment of the Jos Plateau (Okoh et al., 2017). The Warm Semi-arid Climate or Tropical Dry climate is the predominant climate type in the northern part of Nigeria. Annual rainfall totals are lower compared to the Figure 1: Map of Nigeria showing the Study Area (Tropical Monsoon Climate Belt) Pa ge 93 https://journals.e-palli.com/home/index.php/ajec Am. J. Environ. Clim. 2(3) 91-100, 2023 Tropical Monsoon and Tropical Savanna belts of Nigeria. The rainy season in this belt last for only three to four months (June–September) while the rest of the year is hot and dry with temperatures climbing as high as 40°C (Okoh et al., 2011). Due to their location in the tropics, this elevation is high enough to reach the temperate climate line in the tropics thereby giving the highlands, mountains and the plateau regions standing above this height, a cool mountain climate (Oluwole and Ike, 2013). Nigeria is covered by three types of vegetation: forests (where there is significant tree cover), savannahs (insignificant tree cover, with grasses and flowers located between trees), and montane land. (The latter is the least common, and is mainly found in the mountains near the Cameroon border.) Both the forest zone and the savannah zone are divided into three parts. Some of the forest zone’s most southerly portion, especially around the Niger River and Cross River deltas, is mangrove swamp. North of this is fresh water swamp, containing different vegetation from the salt water mangrove swamps, and north of that is rain forest (Olajuyigbe & Adaja, 2014).The Savannah zone’s three categories are divided into Guinean forest- savanna mosaic, made up of plains of tall grass which are interrupted by trees, the most common across the country; Sudan savannah, similar but with shorter grasses and shorter trees; and Sahel savannah patches of grass and sand found in the Northeast (Mohammed, 2013). The data used in this study included the primary and secondary data types. The secondary data are the climate data covering a period of 40 years from 1980 to 2019 included mean monthly maximum and minimum temperatures; and mean monthly rainfall were obtained from the office of Nigerian Meteorological Agency (NiMet), Abuja for this study, and data on ginger in tons per hectare were collected from the experimental farms of National Root Crops Research Institute (NRCRI), Umudike, Agricultural Development Programme (ADP) and Nigerian Bureau of Statistics, Abuja.. The study employed the use of Statistical Package for Social Sciences (SPSS) version 22. Simple linear regression and correlation were employed to explain the time series variations in meteorological parameters and ginger yield. The analysis of variance (ANOVA) was used because it has the capacity to determine the divergence in the mean of data, particularly, when the data sets are up to or more than three independent sets (Wahab & Jiao, 2020; Kumawat & Yadav, 2021). RESULTS AND DISCUSSIONS Table 1 shows the mean monthly distribution of rainfall amounts in the climate belts of Nigeria. During the study period, the month of January was wetter in the Tropical Monsoon (TM) Climate Belt with mean monthly rainfall of 33.5mm. The highest mean total rainfall amount of 348.4mm was recorded in the month of September whereas the lowest mean total rainfall amount of 33.1mm was recorded in the month of December. The month of July also recorded high amount of rainfall of 327.2mm followed by June that recorded 291.9mm mean amount of rainfall. There is rainfall in all the months of TM climate belt. The Warm Desert (WD) Climate Belt recorded the lowest amount of mean monthly rainfall. Its highest mean monthly rainfall of 202.1mm was in the month of August followed by the month of July which recorded 173.9mm amount of rainfall. The lowest amount of rainfall of 6.4mm was recorded in the month of April. The WD climate had total number of six months of rainfall which starts from the month of April and ends in the month of October. The WD climate recorded the highest number of months without rainfall (January, February, March, November and December). The mean monthly rainfall amount is higher than that of the Tropical Savanna (TS) Climate Belt which had a mean monthly rainfall for January as 9.3mm. In TS climate, the highest mean total amount of 265.5mm rainfall was recorded in the month of September as well whereas the lowest of 9.3mm of mean rainfall amount was recorded in the month of January. The month of July also recorded high amount of rainfall of 222.9mm, followed by June which recorded 210.4mm. TS climate had rainfall in all the months. The other two climate belts of Warm Semi-arid (WSA) Climate Belt and the Warm Desert Climate are exceptionally dry in the month of January with 0.2mm and 0mm of mean monthly rainfall respectively. The same pattern can be seen for February and March. Though, in April, the sign of wetness is witnessed in the Warm Desert Climate and a 6.4mm mean monthly rainfall is documented. For WSA climate, the highest mean monthly rainfall of 205.7mm was observed in the month of August and 179.4mm in the month of July while the lowest was 0.2mm in the month of January. However, the months of November and December recorded 0.0mm and 0.0mm respectively making it have total number of seven months of rainfall. Table 2 reveals the analysis of variance for differences in the seasonal amounts of rainfall in the study area. The Table 1: Monthly Rainfall (mm) distribution across the climate belts of Nigeria (1980-2019) Months Tropical Monsoon Climate Tropical Savanna Warm Semi-arid Climate Warm Desert Climate January 33.5 9.3 0.2 0 February 54.8 20.8 0.3 0 March 126.4 55.2 1.8 0.3 April 186 113.7 7.9 6.4 May 248.6 175.2 52.2 30.9 June 291.9 210.4 82.5 75.3 Pa ge 94 https://journals.e-palli.com/home/index.php/ajec Am. J. Environ. Clim. 2(3) 91-100, 2023 seasons were the December January and February (DJF), March April and May (MAM), June July and August (JJA), then September October and November (SON). The essence here was to see if there have been differences in the patterns of rainfall within the seasons of the year. It is also critical to understand that whereas the second season (MAM) is critical for the planting, the third season (JJA) is majorly for growth and maturity of root and tuber crops in Nigeria, while the fourth (SON) and the first (DJF) seasons are critical for the harvest and storage of root and tuber crops in Nigeria in the Tropical Monsoon Climate. Similarly, the second season (MAM). For the Tropical Monsoon, all the seasons appeared to have been significantly different at p<0.05. The same can be said about the other climate belts of the country. This explains in clear terms that there have been significant changes in the seasonal rainfall amounts across the climate belts of the country over the past 40years (1980 – 2019). The temperature data presented in Figure 2 shows that in the Tropical Monsoon Climate Belt, temperature ranged from 25.60C in July to 27.5 in May. The months of June July August, appear cooler due to the effect of the rainy season in this belt at this period of the year. The Tropical Savanna Climate belt observed the highest temperature a little differently from the Tropical Monsoon Climates’. In this belt the highest temperature was encountered in the months of March and April, with 28.50C and 28.70C respectively. The coolest temperature was recorded in September with a mean monthly temperature of 26.10C. In the Warm Semi-arid Climate, April also recorded the highest temperature of 29.50C. The coldest month was the month of January with a temperature of 230C. July 327.2 222.9 179.4 173.9 August 282.8 203.8 205.7 202.1 September 348.4 265.5 108.5 102.7 October 277.3 167.4 20.4 13.2 November 103.5 27.3 0 0 December 33.1 11.2 0 0.1 Mean 2313.7 1482.6 659 604.8 Table 2: Seasonal differences in rainfall in the climate belts Tropical Monsoon Months Groups Sum of Squares Df Mean Square F Sig. DJF Between 902365.12 3 157 7.1363 .006 Within 813565.23 116 22 MAM Between 848565.13 3 144 13.0909 .001 Within 712265.11 116 11 JJA Between 765165.13 3 163 11.6428 .003 Within 622365.15 116 14 SON Between 635565.21 3 164 13.6666 .000 Within 479765.11 116 12 Tropical Savanna DJF Between 772639.33 3 451 6.6323 .040 Within 684730.31 116 68 MAM Between 580822.56 3 131 7.7058 .031 Within 474914.16 116 17 JJA Between 259005.85 3 168 16.800 .000 Within 164097.54 116 10 SON Between 147189.23 3 289 15.2105 .000 Within 44280.22 116 19 Warm Semi-arid Climate DJF Between 880364.11 3 201 10.5789 .001 Within 704455.45 116 19 MAM Between 557547.15 3 189 12.6000 .000 Within 245638.24 116 15 JJA Between 644729.99 3 204 9.2727 .001 Within 192178.99 116 22 Pa ge 95 https://journals.e-palli.com/home/index.php/ajec Am. J. Environ. Clim. 2(3) 91-100, 2023 The reason for the low temperature in January is the closeness of the region to the Sahara Desert and the cold tropical continental air mass which is more boisterous at that time of the year thereby affecting temperature of the area. This same condition applies to the Warm Desert Climate, which also had its coldest mean monthly temperature in the month of January (22.60C). Table 3 reveals the ANOVA computations for differences in the seasonal mean temperature in the study area. For the Tropical Monsoon, all the seasons appeared to have been significantly different at p<0.05. In the Tropical Savanna belt all the other seasons of the year were significantly different at p<0.05, but DJF was not significant at p>0.05. This could be possibly caused by the closeness of the SON Between 843564.12 3 228 17.5384 .000 Within 563455.11 116 13 Warm Desert Climate DJF Between 868557.39 3 296 12.3333 .000 Within 622659.45 116 24 MAM Between 730354.01 3 189 14.5384 .000 Within 631255.7 116 13 JJA Between 606760.77 3 263 16.4375 .000 Within 550862.47 116 16 SON Between 499464.16 3 223 10.6190 .001 Within 239065.85 116 21 DJF=December, January, February; MAM=May, June, July; JJA=June, July, August; SON=September, October, November Figure 2: Mean monthly temperature distribution across the climate belts of Nigeria Table 3: Seasonal differences in temperature across the climate belts in Nigeria Tropical Monsoon Months Groups Sum of Squares Df Mean Square F Sig. DJF Between 900365.22 3 123 10.2500 .000 Within 854565.2 116 12 MAM Between 808765.17 3 181 12.0667 .000 Within 762965.15 116 15 JJA Between 717165.13 3 103 5.7222 .012 Within 671365.10 116 18 SON Between 625565.08 3 134 6.3810 .010 Within 579765.05 116 21 Tropical Savanna DJF Between 672639.08 3 89 1.4127 1.04 Within 586730.77 116 63 MAM Between 500822.47 3 112 5.8947 .034 Within 414914.16 116 19 JJA Between 329005.85 3 193 4.2889 .041 Within 243097.54 116 45 Pa ge 96 https://journals.e-palli.com/home/index.php/ajec Am. J. Environ. Clim. 2(3) 91-100, 2023 region to the region where the tropical continental air mass prevails at the time of the year. In the Warm Semi- Arid Climate, it was MAM that was not significant at p>0.05. The other seasons of the year were significant at p<0.05. Finally, the Warm Desert Climate had all seasons of the year statistically significantly different at p<0.05 except DJF season that was not significant at p>0.05. Figure 3a reveals the time series plot for rainfall in the Tropical Monsoon Climate belt. The plot yielded a model with an R2 0.6 and Y=1.85x + 2269.5. The model revealed a quasi-decadal pattern with no much noticed anomaly or deviation. Also, Figure 3b showed that there are some inherent anomalies in the rainfall distribution. Particularly, 1986 was exceptionaly dry and represented SON Between 157189.23 3 123 7.2352 .020 Within 71280.926 116 17 Warm Semi-arid Climate DJF Between 980364.23 3 108 9.8182 .000 Within 744455.67 116 11 MAM Between 508547.11 3 192 2.4304 .231 Within 272638.55 116 79 JJA Between 636729.99 3 134 9.5714 .003 Within 199178.56 116 14 SON 830564.006 3 117 7.8000 .005 624455.698 116 15 Warm Desert Climate DJF Between 718557.39 3 161 1.6598 .067 Within 662659.08 116 97 MAM Between 830354.01 3 110 5.0000 .001 Within 774455.7 116 22 JJA Between 606760.77 3 143 3.7632 .051 Within 550862.47 116 38 SON Between 494964.16 3 119 4.9583 0.041 Within 439065.85 116 24 DJF=December, January, February; MAM=May, June, July; JJA=June, July, August; SON=September, October, November. Figure 3: Rainfall and temperature time series and anomaly plots for the Tropical Monsoon Climate Belt. Pa ge 97 https://journals.e-palli.com/home/index.php/ajec Am. J. Environ. Clim. 2(3) 91-100, 2023 the year with the driest rainfall with anormaly value of -350mm. In Figure 3c the temperature timeseries plot is presented. In the figure the temperature ranges between 260C to 30.50C. The temperature appeared to be on the increase contineously, although with some anomalies. There are two deviations within the continum, as seen in the year 1995 and 2004. In Figure 3d showed the anormalies in the temperature data, where 1995 and 2002 were very cool with the temperature anomalies of -1.50C for each of them. Figure 4a reveals the time series plot for rainfall in the Tropical Savanna Climate belt. The plot yielded a model with an R2=0.046 and Y=58.15X. The model revealed a quasi-decadal pattern with no much anomaly or outliers. On the other hand, Figure 4b showed that there are some inherent anomalies in the rainfall distribution. Particularly, 1996 was abnormaly dry and represented the year with the driest rainfall with anormaly value of -45mm. In Figure 4c the temperature timeseries plot is presented. In the figure the temperature ranges between 260C to 29.50C. The temperature appeared to be on the increase contineously, although with some anomalies. There are two deviations within the continum, as seen in the year 2016 and 2018. In Figure 4d showed the anormalies in the temperature data, where 2013 and 2015 were very cool with the temperature anomalies of -0.130C Figure 4: Rainfall and Temperature time series and anomaly plots for the Tropical Savanna Climate Belt. and 0.150C respectively. Figure 5a reveals the time series plot for rainfall in the Warm Semi-arid Climate belt. The plot yielded a model with an R2 0.7 and Y=35.05X. The model revealed a quasi-decadal pattern with two peaks while Figure 5b shows that there are some inherent anomalies in the rainfall distribution. Particularly, 1995 was abnormaly dry and represented the year with the driest rainfall with anormaly value of -48mm. In Figure 5c, the temperature timeseries plot is presented. In the figure the temperature ranges between 260C to 280C. The temperature appeared to be on the increase contineously, although with some anomalies. There is one peak within the continum, as seen in the year 2010. In figure 5d,it is shown that the anormalies in the temperature data, where 2010 was very cool with the temperature anomaly of - 0.150C. Figure 6a reveals the time series plot for rainfall in the Warm Desert Climate belt. The plot yielded a model with an R2 = 0.55 and Y=1.17x + 692.73. The model revealed a quasi-decadal pattern with two peaks. However, Figure 6b showed that there are some inherent anomalies in the rainfall distribution. Particularly, 2000 was abnormaly dry and represented the year with the driest rainfall with anormaly value of -212mm. In Figure 6c, the temperature timeseries plot is presented. In figure 6c, the temperature ranges between 26.50C to 31.50C. The temperature appeared to be on the increase continuously, although with some anomalies and a decade long consistent temperature distribution. There is three peaks within the continum, as seen in the years 1988 (30.50C) 1997 (30.70C) and 2017 (310C). Figure 6d shows the anormalies in the temperature data, where 1997 was very hot with the temperature anomaly of 2.50C. Most of the agricultural practices in the country are climate dependent. It is therefore possible to trace the yields of crops to the climate type of the place. It is also very common to use the amount and buoyancy of rainfall and temperature to measure these relationships. This is because these elements of weather and climate are pervasive and have controlling effects on other components of the environment. Table 4indicates the Pa ge 98 https://journals.e-palli.com/home/index.php/ajec Am. J. Environ. Clim. 2(3) 91-100, 2023 Figure 5: Rainfall and Temperature time series and anomaly plots for the Warm Semi-Arid Climate Belt. Figure 6: RRainfall and temperature time series and anomaly plots for the Warm Desert Climate Belt. relationship between climate (rainfall and temperature) and the yields of ginger over the years. Here, the dependent variable (ginger) is regressed against rainfall and temperature (predictors). In the Tropical Monsoon Climate Belt, the rainfall and temperature significantly predicted ginger yield (F=12.0934; p<0.05) which indicates that temperature and rainfall play significant role in the yield of ginger in the Tropical Monsoon Climate Belt. The model revealed a positive relationship (r=0.672) and the R2 was .452. This means that rainfall and temperature jointly explained 45.2% of variation in ginger yield in the Tropical Monsoon Belt of Nigeria. In the Tropical Savanna Climate Belt, the rainfall and temperature significantly predicted ginger yield (F=17.3452; p<0.05) which indicates that temperature and rainfall play significant role in the yield of ginger in the Tropical Savanna Climate Belt. The model revealed a positive relationship (r=.597) and the R2 was .356. This Pa ge 99 https://journals.e-palli.com/home/index.php/ajec Am. J. Environ. Clim. 2(3) 91-100, 2023 means that rainfall and temperature jointly explained 35.6% of variation in ginger yield in the Tropical Savanna Belt of Nigeria. In the Warm Semi-Arid Climate Belt, the rainfall and temperature significantly predicted ginger yield (F=24.9501; p<0.05) which indicates that temperature and rainfall play significant role in the yield of ginger in the Warm Semi-Arid Climate Belt (b1= R; .173 P<0.05, b2= T.343 P<0.05). The model revealed a positive relationship (r=.457) and the R2 was .209. This means that rainfall and temperature jointly explained 20.9% of the variation in ginger yield in the Warm Semi- arid environment of Nigeria. Table 4: The relationship between ginger yields and climate (rainfall and temperature) in the climate belts of Nigeria Climate zone Regression weights N Beta R R2 F P-value TM Rainfall, Temp→Ginger 40 .332 .672 .452 12.0934 0.004 .423 TS Rainfall, Temp→Ginger 40 .354 .597 .356 17.3452 0.003 .341 WSA Rainfall, Temp→Ginger 40 .173 .457 .209 24.9501 0.040 .343 WD Rainfall, Temp→Ginger 40 .317 .549 .301 29.8517 0.002 .281 N:B: TM=Tropical Monsoon; TS=Tropical Savanna; WSA= Warm Semi-Arid Climate; WD=Warm Desert Climate. In the Warm Desert Climate environment, rainfall and temperature significantly predicted ginger yield (F=29.8517; p<0.05) which implies that temperature and rainfall play significant role in the yield of ginger in the Warm Desert Climate environment. The model revealed a positive relationship (r=.549) and the R2 was .301. This means that rainfall and temperature jointly explained 30.1% of variation in ginger yield in the Warm Desert Climate Belt of Nigeria. Discussion of Findings Climate, especially rainfall and temperature, is generally perceived to affect the growth, development and yield of crops in Nigeria (Agele & Bolarinwa, 2018). Annual, seasonal and monthly rainfall and temperature values have been seen from the results of the study that they vary with climate belt thus affecting the yields of ginger across the climate belts of Nigeria. The relatively low amounts of rainfall of WSA and WD Climate Belts as against TM and TS threatened the yield of ginger in the belts which call for irrigation if maximum yield is to be attained (Agele & Bolarinwa, 2018). This is corroborated by Zaied & Zouab, (2016), Garbero, & Jäckering (2021) and Singh, et al. (2022) who stated that successful production of ginger can be attained where a moderate rainfall at the sowing time till the rhizomes sprout, fairly heavy and well-distributed showers during the growing period, and dry weather with a temperature of 280 to 350C for about a month before harvesting are available. On the other hand, flooding and water-logging resulting from heavy rainfall and water stress such as drought resulting inadequate rainfall reduce the yields of root and tuber crops including ginger (Ayanlade, et al., 2010). Generally, the identified climate events that affect ginger farming are extreme rainfall (TM & TS), Flooding (TM, TS & WSA) and drought conditions (TS, WSA & WD). This is in line with the work of (Nwachukwu et al., 2012) who affirms that rainfall and temperature significantly affect agricultural production. The assessment of the mean monthly temperature for the various climatic belts showed that there has been a difference in the monthly temperatures which ranged from 0.50C to 2.10C. In the TM Climate Belt, the months of October and April were hottest, while December was coolest. The coldness experienced in December in this belt was caused by the prevailing harmattan wind, which blows over the TM climate belt at this time of the year. The changes in the temperature hotness or coldness were traceable largely to the controls of the climate of Nigeria. And these include; but not limited to air masses (Tropical Maritime and Tropical Continental), elevation, rotation and revolution. On the anthropogenic side, urbanization, transportation, gas flaring, deforestation and the burning of bushes could be held accountable (Onwuka, 2012), as climate change becomes a topic of concern around the world (Hamisi & Abdillah, 2022: Amosah et al., 2023). In the other belts that is, the TS, WSA and WD, the months of April, May and November were very critical as they stood out as the very hottest and erratic months of the year, when it came to temperature. This finding corroborated the finding of (Ayodele & Sambo, 2014). The temperature ranged from 25.6 0C in July to 27.5 0C in May for the TM. The months of June July August, were cooler because of the rainy season in this belt at this period of the year. The Tropical Savanna Climate belt observed the highest temperature a little differently from the Tropical Monsoon Climates belt in which temperature ranged from 26.10C in December to 28.70Cin April. In the Warm Semi-Arid Climate Belt, April also recorded the highest temperature of 29.5 0C. The coldest month was the month of January with a temperature of 230C. The adducible reason for this low temperature in January is the closeness of the region to the Sahara Desert and the cold tropical continental air mass which is more boisterous at Pa ge 10 0 https://journals.e-palli.com/home/index.php/ajec Am. J. Environ. Clim. 2(3) 91-100, 2023 that time of the, year thereby affecting temperature of the area. This same condition applies to the Warm Desert Climate Belt, which also had its coldest mean monthly temperature in the month of January (22.60C). This finding is in line with (Onyeka, 2014), who argued that the Sahara Desert and the Atlantic Ocean play significant roles in the climatic outcomes of Nigeria. Whereas, the Atlantic Ocean provides a cooling effect to the south, the Sahara Desert play both cooling and heating effect to the north section of the country (Onwuka, 2012).In general, the temperatures across the climate belts are relatively good for the successful production of ginger as the temperatures are not above 350C to leave scorch particularly in young plants and also not low to the extent of inducing dormancy.The works of Byrnes & Bumb(2017); Borras, et al. (2022) and Salnikov et al.(2022) corroborate this assertion. CONCLUSION There is a significant relationship between rainfall and temperature and ginger yield from 1980 to 2019. Also, rainfall is more variable than temperature over the period studied and across the climate belts. Ginger is purely a product of the rainfall and temperature as observed, other climate variables and factors notwithstanding. This study recommended that climate smart agriculture should be encouraged. Planting and harvesting of ginger by farmers should align with the seasons as found in each of the four climate belts. Also, improvement in the agricultural practice and technology for farming is greatly needed. If Nigeria continues to rely on rainfall for ginger production without involving irrigation when the rains are gone will make the country not maximize the yield of the crop, and by extension reducing the economic benefits from ginger. Therefore, dams should be built by governments at all levels (Federal, State and Local Government Area) so as to encourage irrigation. REFERENCES Akram, A., Merunka, D. and Shakaib Akram, M. (2011). Perceived brand globalness in emerging markets and the moderating role of consumer ethnocentrism. International Journal of Emerging Markets, 6(4), 291- 303. https://doi.org/10.1108/17468801111170329 Amosah J. Lukman T. & Nabomya E.D. (2023). Assessing Indigenous and Modern Adaptation Strategies to Climate Change among Legumes Producers in the Bongo District of the Upper East Region, Ghana. American Journal of Environment and Climate, 2(2), 1-14 Asumugha, G. N., Ayaegbunam, H. N., Ezulike, T. O., Nwosu, K. L. (2006). Guide to ginger production and marketing in Nigeria. National Root Crops Research Institute, Umudike Nigeria. Ext. Guide 7,1-7 Chen, G. T., Yuan, B., Wang, H. X., Qi, G. H. and Cheng, S. J. (2019). Characterization and antioxidant activity of polysaccharides obtained from ginger pomace using two different extraction processes. International Journal of Biological Macromolecules, 139, 801–809. https://doi.org/10.1016/ j.ijbiomac.2019.08.048 Egbuchua, C. N. & Enujeke, E. C. (2013). Growth and yield responses of ginger (Zingiber officinale) to three sources of organic manures in a typical rainforest zone, Nigeria. J. Hortic. For., 5(7), 109-114. Ernest, E, Pittler, M. H. (2008). Efficacy of Ginger for nausea and vomiting: A systematic review of randomized clinical trial. Br. J. Anesth. 84(3), 367-371. FAO (2008a). Soaring food prices: facts, perspectives, impacts and actions required. Document HLC/08/ INF/1 prepared for the High Level Conference on World Food Security: The Challenges of Climate Change and Bioenergy, 3–5 June 2008, Rome FAOSTAT (2014). Production– Crops (2014) data. Food and Agriculture Organization of the United Nations. www.fao.org/faostat. Garbero, A., & Jäckering, L. (2021). The potential of agricultural programs for improving food security: A multi-country perspective. Global Food Security, 29, 100529. https://doi.org/10.1016/j.gfs.2021.100529 Hamisi, S. H., & Abdillah, M. K. (2022). Role of Climate Change During the Covid-19 Pandemic. American Journal of Environment and Climate, 1(3), 12–16. J. M., Woodley, C. M., Cech, Jr., J. J., and Hansen. L. J., (2004). Effects of global climate change on marine and estuarine fishes and fisheries. Reviews in Fish Biology and Fisheries, 14, 251-275. Jakes J.S. (2007). Ginger as “Beverage of Champion”. J. Plant Nutr. 38(6), 45-56. Kim, J.S. and Kim, M.J. (2010). In vitro antioxidant activity of Lespedeza cuneata methanolic extracts. Paavola, J. (2003). Livelihoods, Vulnerability and Adaptation to Climate Change in the Morogoro Region, Tanzania Centre for Social and Economic Research on the Global Environment, University of East Anglia, Norwich NR4 7TJ, UK Working Paper EDM Roessig, Sharma M, Sharma R. (2011). Synergistic antifungal activity of Curcuma longa (turmeric) and Zingiber officinale (ginger) essential oils against dermatophyte infections. J Essent Oil Bear Plants., 14(1), 38–47. https://doi.org/10.1080/ 0972060X.2011.10643899. Shuhaimi-O. M., Nadzifah, Y., Umirah, N. S., Ahmad, A. K. (2012). Toxicity of metals to tadpoles of common Sunda toad, Duttaphrynus melanostictus . Toxicological and Environmental Chemistry. 94(2), 364–376. Singh, R. K., Joshi, P. K., Sinha, V. S. P., Kumar, M. (2022). Indicator Based Assessment of Food Security in SAARC Nations under the Influence of Climate Change Scenarios. Future Foods, 5100122. Srinivasan, K. (2018). Ginger rhizomes (Zingiber officinale): A spice with multiple health beneficial potentials. Pharma Nutrition, 5(1), 18–28. https:// doi. org/10.1016/j.phanu.2017.01.001 Zaied, Y. B., & Zouabi, O. (2016). Impacts of climate change on Tunisian olive oil output. Climatic Change, 139(3–4), 535–549. https://doi. org/10.1007/ s10584-016-1801-3