Suitability of semolina, cracked wheat and cracked maize as feeding commodities for Tribolium castaneum (Herbst; coleoptera: Tenebrionidae)

Abstract

In the current study it was investigated the suitability of semolina, cracked wheat and cracked maize as feeding commodities for the red flour beetle, Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae). The pest completed its development on all tested commodities. The developmental time of larvae was lower on cracked wheat (59.6 days) and cracked maize (54.6 days) compared to semolina (72.8 days). The developmental time of pupae did not differ significantly among tested commodities, ranging from 6.2 to 6.6 days. Female and male longevities were 70.9 and 77.1 days, 92.2 and 77.9 days and 177.0 and 183.7 days, when T. castaneum was fed on semolina, cracked wheat and cracked maize, respectively. The highest fecundity (28.7 eggs/female) was recorded when T. castaneum was fed on semolina, followed by cracked wheat (2.7 eggs/female) and cracked maize (1.2 eggs/female). The prolonged adult longevity, which was observed on cracked maize, may be attributed to the absence of the cost of reproduction, due to low fecundity on this commodity. The values of the intrinsic rate of increase were 0.014 and −0.021 females/female/day when it was fed on semolina and cracked wheat, respectively, while no demographic analysis was carried out for cracked maize due to high early larval mortality and low fecundity on this commodity. The net reproductive rate and mean generation time were 6.19 females/female and 127.5 days and 0.16 females/female and 91.9 days, when it was fed on semolina and cracked wheat, respectively. Based on demographic analysis, T. castaneum population growth is favored only on semolina. We expect semolina to act as a suitable commodity for T. castaneum, while cracked wheat and cracked maize allow only its survival by acting as alternative commodities. The estimated demographic parameters of T. castaneum on the tested commodities could be used as a useful tool to predict its population outcome in storage facilities.