ICP-OES analysis of total As and Cd in Columbian Oryza sativa L. rice.

Arsenic (As) and cadmium (Cd) are considered toxic elements, even at trace levels. Their accurate quantification in crops can be complex at low levels and due to interference with other elements. The aim of this work was to develop and validate an analytical method for As and Cd quantification in rice stem and grains from the production systems "Irrigated Rice Ecosystems" (IRE) and "Rainfed Rice Ecosystems" (RRE) in Colombia. Mineralisation was carried out by acid digestion using an open system with a heating plate. Metal detection was performed by inductively coupled plasma optical emission spectrometry (ICP-OES). Method adjustment, calibration, and validation were performed in accordance with AOAC standards, considering sensitivity, precision, accuracy, and selectivity parameters. The obtained method was applied to quantify levels in 259 rice stem and 443 grain samples from IRE and RRE.

Use of near-infrared reflectance spectroscopy on feces to estimate digestibility and dry matter intake of dietary nutritional characteristics under grazing conditions in Colombian creole steers.

Digestibility and intake are parameters difficult and expensive to estimate under grazing conditions; therefore, the aim of this study was to develop near-infrared reflectance spectroscopy (NIRS) calibrations applied to feces (F-NIRS) and evaluate their accuracy to predict dry matter digestibility (DMD) and dry matter intake (DMI) of Colombian creole cattle. Five digestibility trials using creole steers were conducted; indigestible neutral detergent fiber (iNDF) was used as internal marker and Cr2O3 and TiO2 as external markers. A total of 249 forage and 396 fecal samples from individual animals were collected, dried, and grinded for conventional chemical analysis. For spectral analysis, fecal samples were pooled across collection periods (77 samples). Chemometric analysis was performed using WinISI V4.10 software applying the modified partial least squares method. Cross-validation was performed to avoid overfitting the models. The goodness-of-fit statistics considered were the coefficient of determination in cross-validation and prediction sets (R2cv and r2, respectively) and the ratio performance deviation (RPD). Fecal NIRS calibrations developed for forage and supplement DMD showed a satisfactory fit (R2cv =0.87 and RPD=2.77 and R2cv=0.92 and RPD=3.50, respectively). The accuracy of fecal output equations using chromium (Cr) and titanium (Ti) was similar in terms of R2cv (0.92) and RPD (3.63 vs. 3.57). Total DMI equations using Ti performed better compared to Cr (R2cv = 0.82 vs. 0.78; RPD=2.41 vs. 2.17, respectively). The F-NIRS models were validated using a completely independent set of fecal samples showing a moderate fit (r2>0.8 and RPD>2.0). This study showed that F-NIRS is a feasible tool to predict DMD and DMI of creole steers under grazing conditions. However, previous to socialization, this requires an improvement in accuracy of the calibrated equations related to grazing animals in different production contexts.