Modelling the Impact of Key Pests of Watermelon on its Performance Using Linear Regression Models


  • Emmanuel OKRIKATA Department of Biological Sciences, Federal University Wukari, Taraba State, Nigeria
  • Emmanuel Oludele OGUNWOLU Department of Crop and Environmental Protection, Federal University of Agriculture Makurdi, Benue State, Nigeria
  • Ngozi Ifeoma ODIAKA Department of Crop Production, Federal University of Agriculture Makurdi, Benue State, Nigeria



Flower sex ratio, Generalized linear regression, Leaf-feeding beetles, Leaf injury, Plant survival rate


Despite the economic, health, and nutritional values of watermelon, insect pests remain a key limitation to its production globally. However, there has, hardly been any research that has statistically modeled the impact of insect pests on its performance. Therefore, this study aims to determine the relationship between the performance of watermelon and the density of its key pests with the aid of correlation and linear regression models, thereby presenting models for forecasting crop performance vis-à-vis pest density for optimum pest management. Data were collected from 40 m2 plots grouped into 4 replicates (10 plots/replicate) in field experiments (arranged in a randomized complete block design) in the early- and late-sown crops of 2016 and 2017 in the Research Farm of Federal University, Wukari, Nigeria. Plant survival rate (%) negatively and significantly (P 0.05) correlated with each of mean number leaf-feeding beetles (r = −0.80, R2 = 63.5 %, Y = 92.023 – 3.145x; r = −0.79, R2 = 62.1 %, Y = 95.986 – 5.975x), A. gossypii density (r = −0.67, R2 = 44.9 %, Y = 184.048 – 50.444x; r = -0.65, R2 = 42.4 %, Y = 131.852 – 14.618x), and B tabaci density (r = −0.67, R2 = 45.2 %, Y = 188.832 – 11.138x; r = −0.66, R2 = 43.3 %, Y = 178.738 – 3.701x) in both the early- and late-sown crop of 2016, respectively, with a similar trend in those of 2017. All parameters significantly (P 0.05) fitted the linear regression model. Densities of all major pests consistently correlated negatively and significantly with fruit yield. Student’s t-test detected significant differences between the early- and late-sown crops of both years. We therefore conclude that watermelon experiences multiple pest infestations whose compositions and intensities vary between seasons, and that their influence on agronomic performance, as shown by the coefficient of determination (R2) values (which were indicative of the reliability of the models with respect to the effect of pests on crop performance), were largely close or > 50 %.


Download data is not yet available.


Metrics Loading ...


T Nordey, C Basset-Mens, HD Bon, T Martin, E Déletré, S Simon, L Parrot, H Despretz, J Huat, Y Biard, T Dubois and E Malézieux. Protected cultivation of vegetable crops in sub-Saharan Africa: Limits and prospects for smallholders: A review. Agr. Sus. Dev. 2017; 37, 53.

S Shagufta. Fruits and vegetables production. African Publishing House, Ibadan, Nigeria, 2012.

J Kranz. Interactions in pest complexes and their effects on yield. J. Plant Dis. Protec. 2005; 112, 366-85.

EC Oerke. Crop losses to pests. J. Agr. Sci. 2006; 144, 31-43.

AF Olaitan and TA Adebayo. Comparative efficacy of Tephrosia vogelii and Moringa oleifera against insect pests of watermelon. Int. Lett. Nat. Sci. 2015; 35, 71-8.

E Okrikata, EO Ogunwolu and MU Ukwela. Diversity, spatial and temporal distribution of above-ground arthropods associated with watermelon in the Nigerian Southern Guinea Savanna. J. Insect Biodivers. Systemat. 2019; 5, 11-32.

E Okrikata and E Ogunwolu. Determination of the critical period of cyper-diforce® treatment against arthropod fauna and productivity of watermelon. Iraqi J. Sci. 2019; 60, 1904-19.

PD Esker, S Savary and N McRoberts. Crop loss analysis and global food supply: Focusing now on required harvests. CAB Rev. 2012; 7, 1-14.

JPM Whish, NI Herrmann, NA White, AD Moore and DJ Kriticos. Integrating pest population models with biophysical crop models to better represent the farming system. Environ. Model. Software 2015; 72, 418-25.

M Donatelli, RD Magarey, S Bregaglio, L Willocquet, JPM Whish and S Savary. Modelling the impacts of pests and diseases on agricultural systems. Agr. Syst. 2017; 155, 213-24.

JO Odhiambo, P Ngare, P Weke and RO Otieno. Modelling of COVID-19 transmission in Kenya using poisson regression model. J. Adv. Math. Compt. Sci. 2020; 35, 101-11.

E Okrikata and OA Yusuf. Diversity and abundance of insects in Wukari, Taraba State, Nigeria. Int. Biol. Biomed. J. 2016; 2, 156-66.

R Trusca, I Grozea and R Stef. Attractiveness and injury levels of adults by Diabrotica virgifera virgifera (Le Conte) on different host plant. J. Food Agr. Environ. 2013; 2, 773-6.

SS Shapiro and MB Wilk. An analysis of variance test for normality (complete samples). Biometrika 1965; 52, 591-611.

E Okrikata, EO Ogunwolu and MU Ukwela. Efficiency and economic viability of neem seed oil emulsion and cyper-diforce® insecticides in watermelon production within the Nigerian Southern Guinea Savanna zone. J. Crop Protec. 2019; 8, 81-101.

M Poornima. 2013, Effect of weather parameters on incidence of major pests and their natural enemies in few selected kharif and rabi crops. Ph.D. Thesis. University of Dhaward, Karnataka, India.

JS Bale, GJ Masters, ID Hodkinson, C Awmack, TM Bezemer, VK Brown, J Butterfield, A Buse, JC Coulson, J Farrar, JEG Good, R Harrington, S Hartley, TH Jones, RI Lindroth, MC Press, I Symrnioudis, AD Watt and JB Whittaker. Herbivory in global climate change research: Direct effects of rising temperature on insect herbivores. Global Change Biol. 2002; 8, 1-16.

MM Degri and HS Sharah. Field evaluation of two aqueous plant extracts on watermelon Citrullus lanatus (Thunb.) insect pest in Northern Guinea Savannah of Nigeria. Int. Lett. Nat. Sci. 2014; 14, 59-67.

J Liu, S Legarrea and MR Kent. Tomato reproductive success is equally affected by herbivores that induce or that suppress defenses. Front. Plant Sci. 2017; 8, 2128.

G Zehnder. Management of cucumber beetles and bacterial wilts of cucurbits. Alabama cooperative extension system. Alabama A and M University and, Auburn University, USA, 1997.

TW Sappington, LS Hesler, KC Allen, RG Lutrell and SK Papiernik. Prevalence of sporadic insect pests of seedling corn and factors affecting risk of infestation. J. Int. Pest Mgt. 2018; 9, 1-27.




How to Cite

OKRIKATA, E. ., OGUNWOLU, E. O. ., & ODIAKA, N. I. . (2021). Modelling the Impact of Key Pests of Watermelon on its Performance Using Linear Regression Models. Walailak Journal of Science and Technology (WJST), 18(7), Article 9052 (11 pages).