The aim of this study was to investigate normal intraocular pressure (IOP) values of cattle, sheep, and goats with a rebound tonometer [TonoVet (TV)] and an applanation tonometer [Tono-Pen AVIA (TPA)] and to determine correction functions for the 2 devices. A total of 60 healthy cattle, sheep, and goats (20 of each) underwent slit-lamp biomicroscopy. Intraocular pressure (IOP) readings were taken from both eyes with the 2 different tonometers and statistically analyzed. For calibration purposes, the IOP was preset on each instrument at 5 to 60 mmHg using 5 mmHg increments in 10 bovine, 8 ovine, and 6 caprine freshly enucleated eyes. Readings were taken with both tonometers at each interval and compared to the manometrically controlled IOP (Mann-Whitney U-test, P ≤ 0.05; Bland-Altman plot, and regression analysis). The median IOP measurements (min to max) obtained with the TV were 23 mmHg (12 to 40 mmHg), 11 mmHg (7 to 20 mmHg), and 23 mmHg (9 to 37 mmHg) for cattle, sheep, and goats, respectively. Using the TPA, the median IOP measurements were 16 mmHg (8 to 27 mmHg), 10 mmHg (5 to 18 mmHg), and 13 mmHg (4 to 25 mmHg) for cattle, sheep, and goats, respectively. There were statistically significant differences between the readings taken with the TV and the TPA in all species (Wilcoxon-test, P ≤ 0.05). All measurements obtained with the TV and the TPA during the calibration procedure differed statistically significantly from the manometrically controlled IOP measurements (Mann-Whitney U-test, P ≤ 0.05). For both instruments, regression formulas were calculated to correct the measurements. Both tonometers can be used effectively to assess intraocular pressure in ruminants, using the specific regression formulas.

The rapid method for predicting palm kernel cake quality with near infrared reflectance spectroscopy was investigated. Chemical tests for moisture, ash, crude protein, crude fat, crude fibre, total digestible nutrients (TDN), nitrogen free extract (NFE), metabolisable energy (ME), calcium and phosphorous were time
consuming and involve high cost. This technology can save considerable time by testing all the parameters simultaneously;
however accurate calibration of the equipment is essential. Near infrared (NIR) partial least square (PLS) regression models for determination of several palm kernel cake quality parameters were
developed from NIRFlex Model N-500 (Buchi). In general, reliable prediction results were obtained for the TDN (SEP = 0.85 r2 = 0.99), NFE (SEP = 0.42 r2 = 0.97) and crude protein (SEP = 0.57 r2 = 0.98)
PLS regression models.