Effect of Larval Density on Food Utilization Efficiency of Tenebrio molitor (Coleoptera: Tenebrionidae) Author(s): Juan A. Morales-Ramos and M. Guadalupe Rojas Source: Journal of Economic Entomology, 108(5):2259-2267. Published By: Entomological Society of America URL: http://www.bioone.org/doi/full/10.1093/jee/tov208 BioOne (www.bioone.org) is a nonprofit, online aggregation of core research in the biological, ecological, and environmental sciences. BioOne provides a sustainable online platform for over 170 journals and books published by nonprofit societies, associations, museums, institutions, and presses. Your use of this PDF, the BioOne Web site, and all posted and associated content indicates your acceptance of BioOne’s Terms of Use, available at www.bioone.org/page/ terms_of_use. Usage of BioOne content is strictly limited to personal, educational, and non-commercial use. Commercial inquiries or rights and permissions requests should be directed to the individual publisher as copyright holder. BioOne sees sustainable scholarly publishing as an inherently collaborative enterprise connecting authors, nonprofit publishers, academic institutions, research libraries, and research funders in the common goal of maximizing access to critical research. ECOLOGY AND BEHAVIOR Effect of Larval Density on Food Utilization Efficiency of Tenebrio molitor (Coleoptera: Tenebrionidae) JUAN A. MORALES-RAMOS1 AND M. GUADALUPE ROJAS USDA-ARS National Biological Control Laboratory, Biological Control of Pests Research Unit, Stoneville, MS 38776. J. Econ. Entomol. 108(5): 2259–2267 (2015); DOI: 10.1093/jee/tov208 ABSTRACT Crowding conditions of larvae may have a significant impact on commercial production efficiency of some insects, such as Tenebrio molitor L. (Coleoptera: Tenebrionidae). Although larval densities are known to affect developmental time and growth in T. molitor, no reports were found on the effects of crowding on food utilization. The effect of larval density on food utilization efficiency of T. molitor larvae was studied by measuring efficiency of ingested food conversion (ECI), efficiency of digested food conversion (EDC), and mg of larval weight gain per gram of food consumed (LWGpFC) at increasing larval densities (12, 24, 36, 48, 50, 62, 74, and 96 larvae per dm2) over four consecutive 3-wk periods. Individual larval weight gain and food consumption were negatively impacted by larval density. Similarly, ECI, ECD, and LWGpFC were negatively impacted by larval density. Larval ageing, measured as four consecutive 3-wk periods, significantly and independently impacted ECI, ECD, and LWGpFC in a negative way. General linear model analysis showed that age had a higher impact than density on food utilization parameters of T. molitor larvae. Larval growth was determined to be responsible for the age effects, as measurements of larval mass density (in grams of larvae per dm2) had a significant impact on food utilization parameters across ages and density treatments (in number of larvae per dm2). The importance of mass versus numbers per unit of area as measurements of larval density and the implications of negative effects of density on food utilization for insect biomass production are discussed. KEY WORDS yellow mealworm, food conversion, rearing, biomass production, insects for food The yellow mealworm, Tenebrio molitor L. (Coleoptera: Tenebrionidae), is produced in large numbers and sold in the United States for a variety of purposes. The larvae of T. molitor are one of the most common foods for captive mammals, birds, reptiles, and amphibians because they are easy to propagate, harvest, and feed (Martin et al. 1976, Barker et al. 1998, Finke 2002). The existence of this type of world-wide industry has inspired organizations like FAO to propose insects as a potential source of food and feed (van Huis et al. 2013). T. molitor has been proposed as a candidate to produce insect biomass as a source for animal feed (Ramos-Elorduy et al. 2002, van Huis et al. 2013, Makkar et al. 2014, Sánchez-Muros et al. 2014), for aquaculture (Ng et al. 2001, Riddick 2014, Barroso et al. 2014), and for human consumption (DeFoliart 1992, 1999; Ramos-Elorduy 1997, 2009; Gahukar 2011; van Huis et al. 2013; Shockley and Dossey 2014). Insects are a promising source of high-quality animal protein with a substantially lower ecological footprint than vertebrate livestock (Finke 2002, 2013; Oonincx et al. 2010; Oonincx and de Boer 2012; van Huis et al. 2013; Shockley and Dossey 2014). The topic of the potential for insects to contribute to sustainable human food security has received the attention of several 1 Corresponding author, e-mail address: Juan.moralesramos@ars .usda.gov. organizations. The UN Food and Agricultural Organization (UN FAO) have proposed a program of feeding people with alternative food sources including insects (Gahukar 2011). Commercial availability of insect biomass (e.g. T. molitor) also provides an opportunity for developing new technologies for mass production of biological control agents. The potential of T. molitor as factitious prey for insect predators has been explored (Saint-Cyr and Cloutier 1996, De Clercq et al. 1998, Grundy et al. 2000, Costello et al. 2002, Lemos et al. 2003, Pappas et al. 2007, De Bortoli 2011). Another application is as a host for in vivo mass production of entomopathogenic nematodes (Shapiro-Ilan et al. 2002, 2008, 2012). The low level of technology required for T. molitor production makes it ideal for the small biological control industry. In addition, T. molitor extracts could be used to supplement artificial diets for entomophagous arthropods (Morales-Ramos et al. 2014). The use of commercially produced T. molitor to produce insect biomass for food and to aid the production of biological control agents will depend on lowering the costs of its production. Research efforts to reduce the cost of producing T. molitor have focused on optimizing reproduction and reducing labor (Morales-Ramos et al. 2011a), improving adult rearing conditions (MoralesRamos et al. 2012), and improving diets (MoralesRamos et al. 2010, 2011b, 2013). However, rearing conditions of immature insects, particularly the density Published by Oxford University Press on behalf of Entomological Society of America 2015. This work is written by US Government employees and is in the public domain in the US. 2260 JOURNAL OF ECONOMIC ENTOMOLOGY of larvae, may also have a significant impact on production efficiency. Increased larval densities delayed or inhibited pupation in many tenebrionid species including T. molitor (Tschinkel and Willson 1971). Weaver and McFarlane (1990) reported a significant and negative impact of larval density on pupal mass in T. molitor, suggesting reduction in growth rates at increasing densities. Increasing larval densities in Gnatocerus cornutus (F.) (Coleoptera: Tenebrionidae) significantly delayed development and increased mortality and cannibalism (Savvidou and Bell 1994). Similarly, development time increased and pupal weight was reduced as larval densities increased in Alphitobius diaperinus Panzer (Coleoptera: Tenebrionidae) (Parween and Begum 2001). Larval crowding arrested pupation in Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae) (Botella and Ménsua 1986). A similar phenomenon was observed in T. freemani (Hinton), which failed to pupate for more than 6 months under crowded conditions (Nakakita 1982). Hirashima et al. (1995) also observed a delay in the release of ecdysone in T. freemani larvae under crowded conditions. Although larval densities affected developmental time and growth in some tenebrionids, no reports were found on the effects of crowding on food utilization. Negative effects of crowding on food conversion efficiency would impact productivity in a commercial colony of T. molitor. Existing production methods tend to favor high larval densities in T. molitor commercial production facilities in order to reduce space demands (J. A. M.-R. unpublished data). The objective of this study was to determine if increasing larval densities have negative effects on the food utilization parameters and therefore biomass production of T. molitor. Materials and Methods Colony Maintenance. The T. molitor colony used in this study was originally established in 2005 from stock donated by Southeastern Insectaries Inc. (Perry, GA), and it has been continuously grown at the National Biological Control Laboratory (Stoneville, MS) for the past 9 yr. The rearing methods were as described by Morales-Ramos et al. (2012) using stacked fiberglass trays (MFG Tray Co., Linesville, PA) with screened bottoms (500-mm pore size) to grow the larvae, boxes with screened bottoms (850-mm pore size) to hold the adults, and collection of first instars in a second tray at the bottom. The colony was fed mostly with wheat bran (>90%) and supplemented with 5–10% dry potato squares once a week. Adults were misted with water twice a week with a spray bottle. Because larvae of T. molitor have the ability to take up water dissolved in subsaturated air (Dunbar and Winston 1975) the relative humidity in the rearing room was maintained at 70% or higher. The room was kept under dark conditions at 26 C. Experimental Design. To create different larval density conditions, increasing numbers of larvae were placed into modified stacked Petri dishes (20 by 60 mm diam.) separated by a nylon screen standard number 45 (350-mm openings) as described by Vol. 108, no. 5 Morales-Ramos et al. (2013). The screen allowed frass particles to fall to the second dish at the bottom while keeping the larvae and food in place. Larval densities were measured as number of larvae per square decimeter (dm2) as described by Morales-Ramos et al. (2012). The experimental dishes had a bottom area of 2733.97 mm2 equivalent to 0.2734 dm2. Eight treatments consisting of 12, 24, 36, 48, 60, 72, 84, and 96 larvae per dish were created, which corresponded to densities of 44, 88, 132, 176, 220, 263, 307, and 351 larvae per dm2, respectively (Table 1). Four-week-old larvae from the stock colony were separated according to sizes by using a series of sieves from standard number 20 to number 35. Larvae passing through sieve number 30 (600 mm) and remaining with sieve number 35 (500 mm) were selected for the experiment. This portion included larvae from the fourth to the sixth instar based on their head capsule measurements (Morales-Ramos et al. 2014). Larvae sorted by this method were used to create 10 groups of larvae for each of the eight density treatments consisting of the appropriate number of larvae for each of the treatments. Each group of larvae was weighed at the beginning of the experiment, and their initial weight was recorded. Groups were transferred to dishes as described above and were provided with food consisting of 80% wheat bran and 20% of a supplement composed of 17:2:1 parts of dry potato, dry egg whites, and soy protein, respectively. The quantity of the food provided varied according to the larval density and was equivalent to 34 mg of food per larvae per dish (Table 1). All dishes were transferred to an environmental chamber where they were maintained at 27 C, 75% RH, and under darkness for a 3-wk period. At the end of the 3 wk, larvae from each dish were separated from the food and weighed as a group. Remaining food and frass were dried in a vacuum oven at 50 C and negative pressure of 1,000 hPa for 24 h and weighed. Live weight gain (LWG) was determined by subtracting the initial larval weight from the accumulated weight of live larvae from each dish. Dry weight gained (DWG) was calculated by multiplying LWG by the dry weight proportion of T. molitor larvae (0.38) as reported by Finke (2002). Food consumed (FC) was calculated by subtracting the weight of the remaining food from the weight of the food provided. Food consumption and weight gained data were used to calculate food utilization parameters as described by Waldbauer (1968). Food assimilated (FA) was Table 1. Density treatments for groups of T. molitor larvae Treatment number 1 2 3 4 5 6 7 8 Larvae per dish Larvae per dm2 Initial food (mg) 12 24 36 48 60 72 84 96 44 88 132 176 220 263 307 351 400 800 1200 1600 2000 2400 2800 3200 October 2015 MORALES-RAMOS AND ROJAS: EFFECT OF LARVAL DENSITY IN T. molitor calculated by subtracting the frass weight from the weight of the food consumed (FA ¼ FC – frass). Weight of food converted was equal to the dry weight gain (DWG). Efficiency of ingested food conversion (ECI) was calculated as ECI ¼ DWG * 100 / FC and efficiency of digested food conversion (ECD) was calculated as ECD ¼ DWG * 100 / FA (Waldbauer 1968). Additionally, live weight (in mg) gained per gram of food consumed (LWGpFC) was calculated as LWG / (FC * 0.001). After data had been recorded for the first 3-wk period, larvae were returned to their corresponding dishes, provided with additional food mix (84 mg per larvae), and returned to the environmental chambers for another 3-wk period. At the end of the second 3-wk period, larvae groups were processed as described above and data was recorded. This process was repeated for another 2, 3-wk periods completing a total of 4, 3-wk periods of data collection. Food provided per larvae increased every 3-wk period as larvae food consumption increased with age. Dishes were monitored daily for food consumption to prevent larvae from running out of food. If food was totally consumed, new food was dried, weighed, added, and recorded. Food utilization parameters were also calculated for the full 12-wk experimental period. Data Analysis. Food utilization parameters at each of the 4, 3-wk periods and the full 12-wk period were analyzed using ANOVA; means were compared among treatments and control by Tukey–Kramer’s HSD test (SAS Institute 2013a). The parameters ECD and ECI, expressed as percentages, were arcsine converted for analysis (Zar 1999). Linear regression was used to analyze the impact of larval density on the values of food utilization parameters. General linear model was used to analyze and compare the impact of larval density and 3-wk period (larval age) and their interaction on food utilization parameters (SAS Institute 2013b). Density was also calculated as larval mass per dm2. The mean larval mass per dm2 during a given 3-wk period was calculated as (initial weight þ ending weight)/2 for each of the observations. Linear regression was used to analyze the impact of larval mass density on food utilization parameters. A multiple linear regression model was used to analyze the relative impact of both types of measurements of density (larval numbers and larval mass per unit of area) on the food utilization parameters. Results Analyses of the whole 12-wk data showed that larval density had a significant impact on individual larval weight gain (F ¼ 71.91, df1 ¼ 7, df2 ¼ 72, P < 0.0001), food consumed per larvae (F ¼ 15.55, df1 ¼ 7, df2 ¼ 72, P < 0.0001), live weight gained per food consumed (LWGpFC; F ¼ 79.57, df1 ¼ 7, df2 ¼ 72, P < 0.0001), efficiency of digested food conversion (ECD; F ¼ 49.15, df1 ¼ 7, df2 ¼ 72, P < 0.0001), and efficiency of ingested food conversion (ECI; F ¼ 76.63, df1 ¼ 7, df2 ¼ 72, P < 0.0001; Table 2). All the food utilization parameters showed a significant linear correlation with 2261 larval density. Individual larval live weight gain and food consumed per larvae were negatively impacted by larval density (b ¼ 0.144. R2 ¼ 0.86, F ¼ 498.27, df ¼ 78, P < 0.0001 and b ¼ 0.305, R2 ¼ 0.52, F ¼84.23, df ¼ 78, P < 0.0001, respectively; Fig. 1). The parameter based on live weight LWGpFC was impacted negatively (b ¼ 0.147, R2 ¼ 0.84, F ¼ 404.19, df ¼ 78, P < 0.0001) by larval density, respectively (Fig. 2A). The parameters ECD and ECI were both impacted negatively by larval density (b ¼ 0.03, R2 ¼ 0.799, df ¼ 78, P < 0.0001 and b ¼ 0.015, R2 ¼ 0.84, df ¼ 78, P < 0.0001, respectively; Fig. 2B and C). Comparison of food utilization parameters among different 3-wk periods revealed significant impact of larval age on food utilization efficiency. Not surprisingly, larval weight gain and food consumption per larvae increased significantly and progressively from one 3-wk period to the next (b ¼ 4.78, R2 ¼ 0.887, F ¼ 2497.7, df ¼ 318, P < 0.001, and b ¼ 27.32, R2 ¼ 0.969, F ¼ 9815.56, df ¼ 318, P < 0.0001, respectively). As larvae grew, food consumption and weight gain were expected to increase proportionally. More surprising was the negative effect of larval growth on the rest of the food utilization parameters (Tables 3–5). Larval biomass produced per g of food (LWGpFC) and ECI were negatively impacted by larval aging (b ¼ 8.3, R2 ¼ 0.643, F ¼ 572.27, df ¼ 318, P < 0.0001 and b ¼ 0.0032, R2 ¼ 0.63, F ¼ 542.5, df ¼ 318, P < 0.001, respectively). The impact of larval aging on ECD was significant (F ¼ 83.2, df1 ¼ 3, df2 ¼ 316, P < 0.0001), but it was nonlinear and the highest value was observed during the second 3-wk period (Table 4). A general linear model analysis on the impact of larval density treatment and the 3-wk period (larval age) on food utilization parameters revealed that larval aging had a greater impact than the density treatments on these parameters (Table 6). Although density in larvae per dm2 remained constant within treatment and 3wk period, density measured as larval mass per dm2 increased within density treatments as larvae aged and grew, and the relative space available to larvae diminished. Linear regression analyses on food utilization parameters of mixed ages and treatments (all pooled data) versus larval mass density expressed in g/dm2 showed a significant linear fit for LWGpFC (R2 ¼ 0.692, F ¼ 713.84, df ¼ 318, P < 0.0001), dryweight ECD (R2 ¼ 0.474, F ¼ 286.71, df ¼ 318, P < 0.0001), and dry-weight ECI (R2 ¼ 0.71, F ¼ 777.81, df ¼ 318, P < 0.0001; Fig. 3). Similar analyses of pooled data using number of larvae per dm2 as the independent variable did not show significant linear fit, with a lack of fit for F ¼ 3.05, 4.05, and 3.33 for LWGpFC, ECD, and ECI, respectively; and lack of fit for P values smaller than 0.0001. This indicates that larval mass is more relevant than the number of larvae as a measure of density and food utilization parameters were more affected by larval mass density than by the number of larvae per area unit. However, multiple linear regression analysis of a model including both measurements of density (as number of larvae and as mass) as independent variables 2262 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 108, no. 5 Table 2. Food utilization parameters of T. molitor larvae at eight different larval densities during a 12-wk period Treatment 1 2 3 4 5 6 7 8 LWG (mg) DWG (mg) FC (mg) LWGpFC (mg) ECD (%) ECI (%) 136.2 6 6.5a 132.1 6 5.0ab 126.0 6 6.2b 117.5 6 6.6c 111.7 6 2.4cd 103.8 6 5.2de 97.5 6 6.6e 96.4 6 6.2e 51.8 6 2.5a 50.2 6 1.9ab 47.9 6 2.3b 44.6 6 2.5c 42.5 6 0.9cd 39.4 6 2.0de 37.0 6 2.5e 36.6 6 2.4e 601.3 6 42.0a 619.4 6 28.3a 616.2 6 28.9a 583.3 6 26.6ab 583.3 6 14.5ab 554.1 6 22.4bc 534.5 6 30.7c 530.1 6 22.3c 227.0 6 9.3a 213.3 6 4.7b 204.6 6 6.5c 201.3 6 3.2c 191.6 6 2.5d 187.3 6 4.7de 182.3 6 6.0e 181.7 6 5.8e 20.29 6 0.50a 19.44 6 0.39b 18.84 6 0.78bc 18.28 6 0.68cd 17.94 6 0.29de 17.50 6 0.44ef 16.95 6 0.40f 17.03 6 0.55f 9.39 6 0.37a 8.82 6 0.20b 8.49 6 0.27c 8.35 6 0.12c 7.97 6 0.10d 7.79 6 0.19de 7.58 6 0.25e 7.56 6 0.24e Individual Larval Weight Gained (mg) LWG, live larvae weight gain; DWG, dry weight gain of larvae; FC, food consumed; LWGpFC, live larvae weight gained per g of food consumed; ECD, dry weight efficiency of digested food conversion; ECI, dry weight efficiency of ingested food conversion. Mean 6 SD. Means with the same letter within columns are not significantly different after Tukey–Kramer HSD test at a ¼ 0.05. 150 A 140 130 120 110 100 90 80 70 0 50 100 150 200 250 300 350 400 Food Consumed per Larva (mg) 700 B 650 600 550 500 450 0 50 100 150 200 250 300 350 400 Larval Density per dm2 Fig. 1. Effect of larval density expressed as larvae per dm2 on live weight gained of individual larvae (A) and food consumed per larvae (B) within 12-wk period. Dots represent observations and lines represent linear regression models. (A) Model: Y ¼ 143.23 – 0.144X, R2 ¼ 0.865, F ¼ 498.27. (B) Model: Y ¼ 637.27 – 0.305X, R2 ¼ 0.519, F ¼ 84.23. October 2015 MORALES-RAMOS AND ROJAS: EFFECT OF LARVAL DENSITY IN T. molitor 2263 260 A LWGpFC (mg) 240 220 200 180 160 B ECD (%) 22 20 18 16 14 C 10 ECI (%) 9 8 7 6 0 50 100 150 200 250 300 350 400 2 Larval Density per dm Fig. 2. Effect of larval density expressed as larvae per dm2 on live weight gained per gram of food consumed (LWGpFC) (A), efficiency of digested food conversion (dry-weight ECD) (B), and efficiency of ingested food conversion (dry-weight ECI) (C) within 12-wk period. Dots represent observations and lines represent linear regression models. (A) Model: Y ¼ 227.22 – 0.147X, R2 ¼ 0.838, F ¼ 404.19. (B) Model: Y ¼ 54.539 – 0.0304X, R2 ¼ 0.799, F ¼ 309.71. (C) Model: Y ¼ 22.722 – 0.0147X, R2 ¼ 0.838, F ¼ 404.19. 2264 JOURNAL OF ECONOMIC ENTOMOLOGY Vol. 108, no. 5 Table 3. Live weight (biomass) gained per g of food (wet weight) consumed in mg (LWGpFC) of T. molitor larvae at eight different densities obtained during 4, 3-wk periods Density treatment Three-week period First 1 2 3 4 5 6 7 8 299.5 6 19.3a 276.4 6 11.6a 247.9 6 20.4a 255.8 6 20.3a 247.1 6 10.7a 243.7 6 8.7a 241.2 6 16.3a 227.1 6 16.2a Second Third Fourth 248.1 6 18.5b 233.6 6 11.2b 235.6 6 6.0a 233.9 6 14.7b 225.9 6 10.4b 221.4 6 10.5b 207.9 6 16.9b 217.8 6 14.6a 227.4 6 7.3c 217.4 6 9.3c 216.3 6 5.4b 204.1 6 16.2c 191.6 6 8.1c 191.0 6 8.3c 188.5 6 8.8c 178.5 6 8.2b 214.8 6 13.8c 197.3 6 9.6d 180.3 6 12.7c 184.3 6 11.1d 171.8 6 8.0d 167.0 6 8.9d 161.6 6 13.0d 167.3 6 10.3b Mean 6 SD. Means with the same letter within rows are not significantly different after Tukey–Kramer HSD test at a ¼ 0.05. Table 4. Percent efficiency of digested food conversion (ECD) of T. molitor larvae at eight different densities obtained during 4, 3-wk periods Density treatment Three-week period First 1 2 3 4 5 6 7 8 20.22 6 1.18b 20.15 6 0.64b 19.83 6 0.74b 17.93 6 1.93b 19.05 6 0.47b 17.81 6 0.47b 17.63 6 0.73b 17.47 6 0.73b Second Third Fourth 21.91 6 0.480a 21.70 6 0.42a 21.38 6 0.20a 20.84 6 0.11a 20.19 6 0.31a 19.96 6 0.42a 18.93 6 0.64a 19.03 6 0.62a 20.53 6 0.32b 20.21 6 0.43b 19.90 6 0.46b 18.59 6 2.13b 18.44 6 0.35c 18.09 6 0.58b 17.52 6 0.37b 17.15 6 0.49b 19.60 6 0.98b 17.98 6 0.80c 16.98 6 1.38c 17.31 6 0.77b 16.43 6 0.61d 16.06 6 0.71c 15.56 6 0.81c 16.12 6 0.86c Mean 6 SD. Means with the same letter within rows are not significantly different after Tukey–Kramer HSD test at a ¼ 0.05. Table 5. Percent efficiency of ingested food conversion (ECI) of T. molitor larvae at eight different densities obtained during 4, 3-wk periods Density treatment Three-week period First 1 2 3 4 5 6 7 8 12.00 6 0.67a 11.22 6 0.37a 10.13 6 0.82a 10.31 6 0.74a 10.12 6 0.38a 9.85 6 0.29a 9.73 6 0.64a 9.19 6 0.65a Second Third Fourth 10.26 6 0.71b 9.71 6 0.42b 9.76 6 0.20a 9.71 6 0.55a 9.34 6 0.38b 9.22 6 0.42b 8.66 6 0.65b 9.05 6 0.55a 9.44 6 0.27c 9.05 6 0.37c 9.00 6 0.22b 8.49 6 0.65b 8.02 6 0.30c 7.96 6 0.34c 7.85 6 0.34c 7.45 6 0.32b 8.89 6 0.59c 8.11 6 0.41d 7.49 6 0.52c 7.65 6 0.45c 7.14 6 0.32d 6.95 6 0.36d 6.73 6 0.54d 6.97 6 0.42b Mean 6 SD. Means with the same letter within rows are not significantly different after Tukey–Kramer HSD test at a ¼ 0.05. Table 6. General linear model (GLM) analysis results of larval density treatment, 3-wk period, and their interaction effect on food utilization parameters Parameter R2 F Larval density F ratio 3-Wk period F ratio Interaction F ratio LWGpFC ECD ECI 0.866 0.825 0.867 67.52 43.73 67.9 70.41 82.08 75.65 511.63 241.84 503.59 3.12 2.64 3.07 Models df1 ¼ 31, df2 ¼ 288, P < 0.0001. All partial effects were significant with P < 0.0002. LWGpFC, live larvae weight gained per g of food consumed; ECD, dry weight efficiency of digested food conversion; ECI, dry weight efficiency of ingested food conversion. showed significant impact of both measurements on dependent variables LWGpFC, ECD, and ECI. The t values for parameter null hypothesis of independent variable “number of larvae per dm2” were 2.55, 8.29, and 3.1, with P ¼ 0.011, P < 0.0001, and P ¼ 0.0021 for LWGpFC, ECD, and ECI, respectively. The t values for parameter null hypothesis of independent variable “larvae mass in g/dm2” were 23.29, 13.33, and 24.24, for dependent variables LWGpFC, ECD, and ECI, respectively, with P < 0.0001 in all cases. Discussion Food utilization parameters of T. molitor were significantly and negatively impacted by increasing larval densities. However, regression analyses showed a stronger impact of larval age than larval densities on food utilization parameters of T. molitor. The density of larval mass increases with age even if larval numbers per unit of area remained constant. This was confirmed by the significant effect of larval mass density October 2015 MORALES-RAMOS AND ROJAS: EFFECT OF LARVAL DENSITY IN T. molitor 2265 350 A LWGpFC (mg) 300 250 200 150 100 24 B ECD (%) 22 20 18 16 14 12 C 14 ECI (%) 12 10 8 6 4 0 5 10 15 20 25 30 Larval Mass Density in g / dm2 Fig. 3. Regression analyses of all 4, 3-wk periods showing the effect of larval mass density expressed as grams of larvae per dm2 on live weight gained per gram of food consumed (LWGpFC) (A), efficiency of digested food conversion (dry-weight ECD) (B), and efficiency of ingested food conversion (dry-weight ECI) (C) within 3-wk period. Circles represent observations and lines represent linear regression models. (A) Model: Y ¼ 246.167 – 3.904X, R2 ¼ 0.692, F ¼ 713.84. (B) Model: Y ¼ 0.201 – 0.00173X, R2 ¼ 0.474, F ¼ 286.71. (C) Model: Y ¼ 0.041 – 0.00153X, R2 ¼ 0.71, F ¼ 777.81. (in mg/dm2) on food utilization parameters across ages and treatments (Fig. 3). This implies that the space available between larvae is the factor that determines larval density effects and therefore larval densities increase as larvae grow in a space of constant dimensions. Tschinkel and Willson (1971) determined that the negative effects of larval crowding in some tenebrionids are due to physical contact (mechanical 2266 JOURNAL OF ECONOMIC ENTOMOLOGY stimulation) among larvae. Although mechanical stimulation effects were relatively weak in T. molitor, pupation was delayed significantly by physically stimulating larvae (by rubbing them with chains) and applying vibration at low larval densities (Tschinkel and Willson 1971). However, multiple regression analysis of our data showed significant impact of both, number of larvae per area unit and mass of larvae per area unit, on LWGpFC, ECD, and ECI parameters. This may mean that the effects of density are not just caused by mechanical contact, but by other factors related to number of individuals, which could be chemical in nature. Weaver and McFarlane (1990) hypothesized that reduction of growth due to increased larval density in T. molitor was due to reduced feeding opportunity induced by conspecific competition. Our study shows that individual food consumption was significantly reduced as larval density increased. Although this seems to support Weaver and McFarlane (1990) hypothesis, it is more likely that reduction in growth was due to the combination of reduced ingestion and the observed reduction in ECD and ECI in response to increased larval density. This effect may be a behavioral response to the frequency of conspecific contacts as Tschinkel and Willson (1971) demonstrated. However, our results could not rule out the sublethal effects of high temperatures due to metabolic heat production as a potential factor in reducing food utilization efficiency. Metabolic heat has been reported as a major problem in insect colonies where rearing conditions often result in extremely high larval densities (Howell and Clift 1972, Tanaka et al. 1972). Larval aggregations of some dipterans, such as Calliphora vomitoria (L.), can produce from 5 to 27 C temperature elevations from ambient temperature (Turner and Howard 1992). High larval densities of late instars of T. molitor can increase temperature by 5 to 10 C inside rearing trays depending of the level of density (J. A. M.-R. unpublished data). Separating the effects of high larval densities from metabolic induced high temperature effects is a difficult task and will be the focus of future research. Results of this study may have important implications for improving T. molitor rearing conditions and for increasing T. molitor biomass production. 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