Browsing by Author "ODIAKA, Ngozi Ifeoma"

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    Modelling the Impact of Key Pests of Watermelon on its Performance Using Linear Regression Models
    (Walailak J Sci & Tech, 2020-06-05) Emmanuel, OKRIKATA; OGUNWOLU, Emmanuel Oludele; ODIAKA, Ngozi Ifeoma
    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. gossypiidensity (r = −0.67, R2 = 44.9 %, Y= 184.048 – 50.444x; r = -0.65, R2 = 42.4 %, Y= 131.852 – 14.618x), and B tabacidensity (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 %.