Yield and adaptability evaluation of newly introduced tomato (solanum lycopersicum) varieties in Tabora Region
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Date
2014
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Abstract
Tomato (Solanum lycopersicum L.) is an important food and income generating crop among small
holder farmers in Tabora Region. High yield is a major ambition to tomato plant breeders and
farmers. The purpose of the study was to determine the influence of environmental conditions in
Tabora Region on the growth and yield of newly introduced tomato varieties. The tested varieties
were Duluti (LBR6), Meru (LBR 50 - 2) and Kiboko collected from AVRDC Arusha, Tanzania.
The experiment was conducted both in the screen house to see the performance of the varieties
under the controlled environment and the field at Tumbi Agricultural Research Institute. A screen
house experiment was laid out in a Completely Randomized Design (CRD) while Randomized
Complete Block Design (RCBD) was used in the field both had three replications. Yield, vegetative
and reproductive data were collected and subjected to analysis of variance using the GENSTAT
programme. Yield and yielding components varied among tomato varieties in both experiments. The
variety, Meru, with 92 ton/ha was significantly (p<0.001) higher than Duluti and Kiboko with 74 and
69 ton/ha respectively under field conditions. The forty tone/ha observed from Duluti was significant
(p<0.05) higher than the 32 ton/ha harvested from each of the other varieties. Variation in yield and
yielding components among tomato varieties in both experiments may be attributed to genetic and
environmental differences. Regardless, of such variations both varieties showed better production in
Tabora. Their good performance was attributed largely to their apparent better adaptation, which
enabled them to grow more vigorously. They will therefore be suggested for adoption by Tabora
growers.
Description
Tanzania Journal of Agricultural Sciences 2015, Vol. 13(1) :67-73
Keywords
Introduced tomato, Solanum lycopersicum, Yield and yielding components, Completely Randomized Design (CRD), Randomized Complete Block Design (RCBD)