In vitro digestibility of dietary proteins and in vitro DIAAS analytical workflow based on the INFOGEST static protocol and its validation with in vivo data.

The FAO recommends the digestible indispensable amino acid score (DIAAS) to determine protein quality in foods, preferably tested in vivo. Here, the INFOGESTin vitrodigestion protocol was applied and supplemented with an analytical workflow allowing the assessment of protein digestibility and DIAAS calculation. The protocol was applied to selected samples WPI, zein, collagen, black beans, pigeon peas, All-Bran®, and peanuts. The total protein digestibility, digestibility of individual amino acids (AA), and DIAAS values were established and compared with in vivo data for the same substrates. Total protein digestibility (total Nitrogen, r = 0.7, P < 0.05; primary amines (OPA), r = 0.6, P < 0.02; total AA, r = 0.6, P < 0.02) and digestibility of individual AA (r = 0.6, P < 0.0001) were in good agreement, between in vitro and in vivo, with a mean difference of 1.2 %. In vitro DIAAS was highly correlated with DIAAS obtained from in vivo true ileal digestibility values (r = 0.96, R2 = 0.89, P < 0.0001) with a mean difference of 0.1 %.

No adverse dietary effect of a cisgenic fire blight resistant apple line on the non-target arthropods Drosophila melanogaster and Folsomia candida.

Genetic modification of apple cultivars through cisgenesis can introduce traits, such as disease resistance from wild relatives, quickly and without crossing. This approach was used to generate the cisgenic apple line C44.4.146, a 'Gala Galaxy' carrying the fire blight resistance gene FB_MR5. In contrast to traditionally bred apple cultivars, genetically modified (GM) plants need to undergo a regulatory risk assessment considering unintended effects before approval for commercial release. To determine potential unintended effects of C44.4.146, we assessed major leaf components and effects on the fitness of the decomposers Drosophila melanogaster (fruit fly) and Folsomia candida (collembolan), which were fed a diet amended with powdered apple leaf material. Leaf material of 'Gala Galaxy', several natural 'Gala' mutants, and the unrelated apple cultivar 'Ladina' were used for comparison. The genetic modification did not alter major leaf components and did not adversely affect survival, growth, or fecundity of the two decomposers. Consistent with previous studies with other GM crops, the differences between conventionally bred cultivars were greater than between the GM line and its non-GM wild type. These data provide a baseline for future risk assessments.

Estimation of dairy goat body composition: A direct calibration and comparison of eight methods.

The objective was to compare eight methods for estimation of dairy goat body composition, by calibrating against chemical composition (water, lipid, protein, mineral and energy) measured post-mortem. The methods tested on 20 Alpine goats were body condition score (BCS), 3-dimension imaging (3D) automatic assessment of BCS or whole body scan, ultrasound, computer tomography (CT), adipose cell diameter, deuterium oxide dilution space (D2OS) and bioelectrical impedance spectroscopy (BIS). Regressions were tested between predictive variates derived from the methods and empty body (EB) composition. The best equations for estimation of EB lipid mass included BW combined with i) perirenal adipose tissue mass and cell diameter (R2 = 0.95, residual standard deviation, rSD = 0.57 kg), ii) volume of fatty tissues measured by CT (R2 = 0.92, rSD = 0.76 kg), iii) D2OS (R2 = 0.91, rSD = 0.85 kg), and iv) resistance at infinite frequency from BIS (R2 = 0.87, rSD = 1.09 kg). The D2OS combined with BW provided the best equation for EB protein mass (R2 = 0.97, rSD = 0.17 kg), whereas BW alone provided a fair estimate (R2 = 0.92, rSD = 0.25 kg). Sternal BCS combined with BW provided good estimation of EB lipid and protein mass (R2 = 0.80 and 0.95, rSD = 1.27 and 0.22 kg, respectively). Compared to manual BCS, BCS by 3D slightly decreased the precision of the predictive equation for EB lipid (R2 = 0.74, rSD = 1.46 kg), and did not improve the estimation of EB protein compared with BW alone. Ultrasound measurements and whole body 3D imaging methods were not satisfactory estimators of body composition (R2 ≤ 0.40). Further developments in body composition techniques may contribute for high-throughput phenotyping of robustness.