Replacement of alfalfa hay ( Medicago sativa ) with maralfalfa hay ( Pennisetum sp.) in diets of lactating dairy goats

Analysis of global Napier grass (Cenchrus purpureus) collections reveals high genetic diversity among genotypes with some redundancy between collections

Genetic diversity amongst genotypes of several Napier grass collections was analyzed and compared with the diversity in a set of open pollinated progeny plants. A total of 114,881 SNP and 46,293 SilicoDArT genome-wide markers were generated on 574 Napier grass genotypes. Of these, 86% of the SNP and 66% of the SilicoDArT markers were mapped onto the fourteen chromosomes of the Napier grass genome. For genetic diversity analysis, a subset of highly polymorphic and informative SNP markers was filtered using genomic position information, a maximum of 10% missing values, a minimum minor allele frequency of 5%, and a maximum linkage-disequilibrium value of 0.5. Extensive genetic variation, with an average Nei's genetic distance value of 0.23, was identified in the material. The genotypes clustered into three major and eleven sub-clusters with high levels of genetic variation contained both within (54%) and between (46%) clusters. However, we found that there was low to moderate genetic differentiation among the collections and that some overlap and redundancy occurred between collections. The progeny plants were genetically diverse and divergent from the germplasm collections, with an average FST value of 0.08. We also reported QTL regions associated with forage biomass yield based on field phenotype data measured on a subset of the Napier grass collections. The findings of this study offer useful information for Napier grass breeding strategies, enhancement of genetic diversity, and provide a guide for the management and conservation of the collections.

Development of a dynamic energy-partitioning model for enteric methane emissions and milk production in goats using energy balance data from indirect calorimetry studies

The main objective of this study was to develop a dynamic energy balance model for dairy goats to describe and quantify energy partitioning between energy used for work (milk) and that lost to the environment. Increasing worldwide concerns regarding livestock contribution to global warming underscore the importance of improving energy efficiency utilization in dairy goats by reducing energy losses in feces, urine and methane (CH4). A dynamic model of CH4 emissions from experimental energy balance data in goats is proposed and parameterized (n = 48 individual animal observations). The model includes DM intake, NDF and lipid content of the diet as explanatory variables for CH4 emissions. An additional data set (n = 122 individual animals) from eight energy balance experiments was used to evaluate the model. The model adequately (root MS prediction error, RMSPE) represented energy in milk (E-milk; RMSPE = 5.6%), heat production (HP; RMSPE = 4.3%) and CH4 emissions (E-CH4; RMSPE = 11.9%). Residual analysis indicated that most of the prediction errors were due to unexplained variations with small mean and slope bias. Some mean bias was detected for HP (1.12%) and E-CH4 (1.27%) but was around zero for E-milk (0.14%). The slope bias was zero for HP (0.01%) and close to zero for E-milk (0.10%) and E-CH4 (0.22%). Random bias was >98% for E-CH4, HP and E-milk, indicating non-systematic errors and that mechanisms in the model are properly represented. As predicted energy increased, the model tended to underpredict E-CH4 and E-milk. The model is a first step toward a mechanistic description of nutrient use by goats and is useful as a research tool for investigating energy partitioning during lactation. The model described in this study could be used as a tool for making enteric CH4 emission inventories for goats.

Development and evaluation of a mechanistic model of post-absorptive nitrogen partitioning in lactating goats

Context Goats contribute to global warming through emission of nitrous oxide from urine and faeces. To reduce nitrogen (N) excretion, improvements of N efficiency of goats is necessary. Aims The aim of the present study was to develop and evaluate a dynamic mechanistic research-oriented model that explicitly represents N partition into faeces, urine and milk in dairy goats fed total mixed rations. Methods Data from five N-balance dairy-goat experiments were used to develop a mechanistic dynamic model of post-absorptive N partition. Various representations considering either mass action or Michaelis–Menten kinetics of N usage for milk were proposed. Key results The data for faecal and urine N responses were best fit by a straight line; whereas, data for milk N responses were best fit by curvilinear saturating curve. The model with curvilinear saturating curve had more precise parameter estimates, with the predicted N excretion in faeces (15.6 g/day), urine (15.4 g/day) and milk N output (11.7 g/day) being very close to the observed values, namely, 15.31 g N/day in faeces, 18.78 g N/day in urine and 12.24 g N/day in milk. Independent datasets with 12 studies were used to evaluate the model. The model tended to under-predict faecal N outflow at a lower N intake level and urinary N outflow at a higher N intake level, with the lowest mean bias for milk N outflow. Conclusions The final chosen model was adequate to represent faecal, urinary and milk N outflows in dairy goats. Implications The model has provided a mechanistic description of N usage, which is useful to frame and test hypotheses of physiological regulation of N use by goats, and focus on a more efficient transfer of dietary N into milk, reducing the N excretion in faeces and urine.

Genotyping by sequencing provides new insights into the diversity of Napier grass (Cenchrus purpureus) and reveals variation in genome-wide LD patterns between collections

Napier grass is an important tropical forage-grass and of growing potential as an energy crop. One-hundred-five Napier grass accessions, encompassing two independent collections, were subjected to genotyping by sequencing which generated a set of high-density genome-wide markers together with short sequence reads. The reads, averaging 54 nucleotides, were mapped to the pearl millet genome and the closest genes and annotation information were used to select candidate genes linked to key forage traits. 980 highly polymorphic SNP markers, distributed across the genome, were used to assess population structure and diversity with seven-subgroups identified. A few representative accessions were selected with the objective of distributing subsets of a manageable size for further evaluation. Genome-wide linkage disequilibrium (LD) analyses revealed a fast LD-decay, on average 2.54 kbp, in the combined population with a slower LD-decay in the ILRI collection compared with the EMBRAPA collection, the significance of which is discussed. This initiative generated high-density markers with a good distribution across the genome. The diversity analysis revealed the existence of a substantial amount of variation in the ILRI collection and identified some unique materials from the EMBRAPA collection, demonstrating the potential of the overall population for further genetic and marker-trait-association studies.