Yield gap analysis in dairy production systems using the mechanistic model LiGAPS-Dairy

The difference between the theoretical maximum (potential) production and the actual production realized by farmers is referred to as the yield gap. The objectives of this study are to develop a mechanistic model for dairy cows that allows yield gap analysis in dairy production systems and to evaluate model performance. We extended and adapted an existing model for beef cattle to dairy cattle, and the new model was named Livestock simulator for Generic analysis of Animal Production Systems—Dairy cattle (LiGAPS-Dairy). Milk production and growth of an individual cow over its entire lifespan were described as a function of the animal's genotype, the ambient climate, feed quality, and available feed quantity. The model was parameterized for Holstein-Friesian cows. After calibration, we evaluated model performance by comparing simulated results and measured results from experimental farms in the Netherlands, which were not used for model calibration. Cows were permanently housed in stables, where the diet consisted of predetermined amounts of concentrates and ad libitum high-quality roughage. The mean absolute error (MAE) for simulated milk production per lactation was 12% of the measured milk production, whereas the MAE for simulated daily milk yields was 19%. The MAE for simulated feed intake per lactation was 10% of the measured feed intake, whereas the MAE for simulated daily feed intake was 19%. The average yield gap for dairy cows was 11% of the potential milk production (Y_P). Yield gap analysis indicated that for experimental farms in the Netherlands, the difference between Y_P and feed quality limited milk production (Y_L) of 1,009 kg fat- and protein-corrected milk was mainly explained by feed intake capacity (33%), protein deficiency (25%), cow weight at the start of experiments (23%), and heat stress (19%). The LiGAPS-Dairy model also indicated the periods during lactation in which these factors affected milk production. In our opinion, the overall model performance is acceptable for permanently housed cows under Dutch conditions. The model needs to be evaluated further for other production systems, countries and breeds. Thereafter, LiGAPS-Dairy can be used for yield gap analysis and exploration of options to increase resource use efficiency in dairy production.     

Perspectives to breed for improved baking quality wheat varieties adapted to organic growing conditions

Northwestern European consumers like their bread to be voluminous and easy to chew. These attributes require a raw material that is rich in protein with, among other characteristics, a suitable ratio between gliadins and glutenins. Achieving this is a challenge for organic growers, because they lack cultivars that can realise high protein concentrations under the relatively low and variable availability of nitrogen during the grain-filling phase common in organic farming. Relatively low protein content in wheat grains thus needs to be compensated by a high proportion of high-quality protein. Organic farming therefore needs cultivars with genes encoding for optimal levels of glutenins and gliadins, a maximum ability for nitrogen uptake, a large storage capacity of nitrogen in the biomass, an adequate balance between vegetative and reproductive growth, a high nitrogen translocation efficiency for the vegetative parts into the grains during grain filling and an efficient conversion of nitrogen into high-quality proteins. In this perspective paper the options to breed and grow such varieties are discussed.     

A vision of 14 T MR for fundamental and clinical science

Objective

We outline our vision for a 14 Tesla MR system. This comprises a novel whole-body magnet design utilizing high temperature superconductor; a console and associated electronic equipment; an optimized radiofrequency coil setup for proton measurement in the brain, which also has a local shim capability; and a high-performance gradient set.

Research fields

The 14 Tesla system can be considered a ‘mesocope’: a device capable of measuring on biologically relevant scales. In neuroscience the increased spatial resolution will anatomically resolve all layers of the cortex, cerebellum, subcortical structures, and inner nuclei. Spectroscopic imaging will simultaneously measure excitatory and inhibitory activity, characterizing the excitation/inhibition balance of neural circuits. In medical research (including brain disorders) we will visualize fine-grained patterns of structural abnormalities and relate these changes to functional and molecular changes. The significantly increased spectral resolution will make it possible to detect (dynamic changes in) individual metabolites associated with pathological pathways including molecular interactions and dynamic disease processes.

Conclusions

The 14 Tesla system will offer new perspectives in neuroscience and fundamental research. We anticipate that this initiative will usher in a new era of ultra-high-field MR.