2.5.4. Recognising the age of larvae
When queen caging is not an option to obtain
larvae of known age, the age of worker larvae can be assessed visually or by
weighing. Visual recognition can be done based on Fig. 7. This however, only
allows for a rough estimate of age. Because the growth is exponential, visual
estimation of age is error prone. A more accurate way is to weigh the larvae
after having cleaned them from jelly residues and absorbed the excess water
from their surface. Table 5 gives equations that allow the calculation of larva
age for workers, queens and drones. Given the exponential growth of larvae,
Thrashyvoulou and Benton (1982) divided the larval development of honey bees of
Italian origin in several phases that could be described with regression
equations for workers, queens and drones (Tables 9 and 10). The high
coefficient of correlations obtained (between 92.3 and 99.7) shows that their
formulas are reliable for the population measured. An equation was also
produced to describe the complete development, but with lower precision and is
therefore not given here (coefficient of correlations between 81.7 and 90.6).
Despite the good fit of these equations, deviations might occur according to
variations between bee populations and subspecies and they should be
recalculated for different populations or subspecies.
Fig. 7. Development of a worker larva, starting from egglaying by the queen. A rough assessment of larva age can be obtained by observing the space occupied by the larva in the cell. Larval instars are represented by greyed areas. Photo: V Dietemann.
Table 9. Regression equations for weight categories of honey bee workers and queens. X designate age and Y the measured weight within the category given in the second column (after Thrashyvoulou and Benton, 1965).

Workers 
Queens 

Age (h) 
Weight (mg) 
Regression equation 
Weight (mg) 
Regression equation 
6 – 30 
0.20 – 0.80 
X = (Y  1.41) / 32.60 
0.12 – 0.69 
X = (Y – 4.79) / 51.40 
31 – 54 
0.81 – 7.00 
X = (Y – 31.90) / 2.71 
0.70 – 8.50 
X = (Y – 33.50) / 3.29 
55 – 90 
7.10 – 46.00 
X = (Y – 50.60) / 0.87 
8.60 – 37.90 
X = (Y – 48.80) / 1.12 
91 – 120 
46.10 – 140.00 
X = (Y – 73.30) / 1.69 
38.00 – 186.00 
X = (Y – 85.10) / 0.16 
Table 10. Regression
equations for weight categories of honey bee drones. X designate age in hours
and Y the measured weight in mg within the category given in the second column
(after Thrashyvoulou and Benton, 1965).
Age (h) 
weight (mg) 
regression equation 
9 – 54 
0.29 – 3.50 
X = (Y – 8.82) / 11.60 
55 – 98 
3.51 – 42.00 
X = (Y – 52.80) / 1.09 
99 – 120 
42.10 – 129.00 
X = (Y – 64.30) / 0.47 
121 – 163 
129.42 – 311.54 
X = (Y – 91.6) / 0.23 