Assessment of Pull- and Push Technologies in Managing Spodoptera frugiperda in Maize and Multivariate Analysis of Associated Variables
Munsanda Walubita, Nchimunya Bbebe, Langa Tembo
Asian Journal of Research in Crop Science · pp. 30–37 · Published 5 Jul 2022
10.9734/ajrcs/2022/v7i230138Abstract
Aims: The effect of push and pull technology in controlling Spodoptera frugiperda in maize may vary depending on environment understudy and the cereal- legume combination treatment employed. The objectives of this study were therefore, to; i) assess the effectiveness of push-pull technologies in controlling Spodoptera frugiperda infestation in maize ii) cluster the technologies into distinct sets, and iii) identify the variables with high discriminating influence among clustered push-pull technology sets. Place and Duration of Study: The research was undertaken in Chilanga district, Zambia during the 2021/ 22 cropping season. Methodology: The experiment was laid as a randomised complete block design (RCBD) with three replications and 6 treatments. Four push –pull combinations and the two controls (Negative and Positive). Maize was used as a test crop. Data on Spodoptera frugiperda incidence was collected at weekly intervals for a period of 5 weeks and at harvest from maize crop. Analysis on measured variables was computed using analysis of variance (ANOVA) and principle component analysis (PCA), a multivariate tool. Results: Significant differences were obtained on all measured variables except harvest index with regards to push- pull treatments main effects (P =0.05). The evaluation of treatments using principal component analysis showed that push - pull treatments clustered into four sets, arising from a phenotypic variation explained of 89.1%. Conclusion: This study revealed Pearl millet/ Marigold push-pull treatment as the best performing treatment with a mean maize test yield value of 7.2 tons per hectare. For variables: number of damaged leaves, injury score leaves, egg batch, biomass with cobs, shelling %, plant height and grain yield were identified as important at differentiating the performance of push pull technologies.
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