The wavelet transform, time-frequency localization and signal analysis
IEEE Transactions on Information Theory
Computers and Electronics in Agriculture
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The aim of the present study was to clarify whether wavelet analysis could identify water intake variation due to health problems and to differentiate between healthy and treated sows. A total of 85 sows (Large White, German Landrace and their crossbreeds) in parities 1-6 were observed. Data were measured in the farrowing unit, beginning at the day of farrowing until the day 10 of lactation. During the week of farrowing the body temperature was measured rectally. If a sow had a body temperature higher than 39.5^oC, the animal was treated. The individual water intake was recorded on a daily basis. The present study used the wavelet analysis to investigate individual water intake of lactating sows. After evaluation of the best wavelet transform, daily water intake of each sow was decomposed into coefficients of approximation and details. The analysis calculated five coefficients of approximation. The differences between the second and first (C"2"1), between the third and second (C"3"2), between fourth and third (C"4"3) and between the fifth and fourth coefficients (C"5"4) were calculated. The smallest value of C"2"1 and C"3"2 was the minimal difference of coefficients (MDC1) of decision criterion one and the smallest value of C"2"1, C"3"2, C"4"3 and C"5"4 decision criterion two (MDC2). These criteria were used to differentiate between healthy and treated sows. The mean MDC1 of healthy sows was significantly higher than the mean MDC1 of treated sows. No distinction could be derived between healthy and treated sows using the mean MDC2. The classification parameters sensitivity, specificity and error rate were calculated depending on different thresholds. Sensitivity ranged from 34% to 83% and specificity from 32% to 92%. In conclusion wavelet analysis in combination with criteria MDC1 could be used to analyse water intake of treated and healthy lactating sows.