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This study aimed to evaluate the predictive ability of NIRS for the estimation of the chemical composition and organic matter digestibility (OMD) of total mixed rations (TMR) for dairy cows. Moreover, herein, empirical equations based on chemical parameters were developed for calculating the OMD. Samples were collected from Galician dairy farms and were scanned in duplicate a Foss NIRSystem 6500 monochromator (1100-2500 nm). The predictive ability of NIRS models was evaluated according to the coefficient of determination in external validation ($r$2). High $r$2 (equal to or higher than 0.90) was shown in predicting chemical composition, however, the estimation of OMD was acceptable ($r$2 = 0.83). The ability of the NIRS models for estimating the chemical composition was considered excellent, with the ratio performance deviation of external validation ($RPD$) higher than 3.0, allowing for quantitative predictions. The estimation of the OMD value by NIRS was considered acceptable ($RPD$ = 2.5), and led to reduction in the standard error of external validation, in comparison of the best empirical model based on the chemical composition of samples (from ± 2.06% to ± 1.89%). Therefore, this study demonstrated that the NIRS is an effective technology for the rapid and precise nutritional evaluation of TMR in Galicia.

In the present work it is studied the predictive ability of NIRS for the estimation of chemical composition (n=171) and organic matter digestibility (n=71) of whole plants forage sorghum and morphological components, being developed empirical equations based on chemical parameters to estimate the organic matter digestibility (OMD) values and compared the predictive ability of empirical models vs. NIRS equations. The predictive ability of NIRS models for estimating the OMD and chemical composition showed high reliability, according to the coefficient of determination in external validation (r²≥0.90), whilst the ratio of the standard deviation of the original data to standard error of external validation (RPD) values were higher than 3.0 for all parameters studied. Applying NIRS models to the prediction of OMD of whole plants and morphological components of forage sorghum led to the reduction in the standard error of external validation, in comparison of the best empirical model based on the chemical composition of samples (from ±3.9 to ±1.9%). It is concluded that the NIRS equations developed in the present work are valuable tools for the fast and accurate assessment of the nutritive value of the whole plant and components of forage sorghum.

The soil-borne fungus Dactylonectria torresensis is the most common causal agent of black-foot disease in Europe. However, there is a lack of understanding on how this fungus can provoke plant symptoms. In this study, we sequenced, annotated and analyzed the genomes of three isolates of D. torresensis collected from asymptomatic vine, weed and soil. Sequenced genomes were further compared to those of 27 fungal species including root and aerial pathogens, white rot degraders, indoor biodeterioration agents, saprotrophs, dark septate endophytes and mycorrhiza. Strains of D. torresensis present genomes with between 64 and 65 Mbp and with up to 18,548 predicted genes for each strain. Average Nucleotide Identity (ANI) shows that strains are different according to genome contents. Clusters of orthologous groups were compared, and clusters of genes related to necroses were particularly detected in all strains of D. torresensis (necrosis inducing peptides and proteins, and ethylene inducing peptides) as well as several genes involved in resistance against fungicides frequently used in viticulture such as copper. Interestingly, an expanded high number of genes related to carbohydrate-active enzymes were detected in each Dactylonectria strain, especially those related to glycoside hydrolases that could be involved in penetration of plant tissues or pathogenicity. An increased number of candidate genes for CAZyme classes AA9 and AA3-1 supports the ability of strains to efficiently degrade plant material. High numbers of genes of D. torresensis related to secretome and small secreted proteins were further characterized. Moreover, the presence of several gene clusters such as fujikurin-like genes was detected and were normally found in Fusariumfujikuroi, that have been linked to fungal pathogenicity. The phenotypes of the three strains investigated showed further difference in light response. We found that Dactylonectria strains have an increased number of photoreceptor encoding genes and we showed sequence alterations. Altogether, the results highlight several gene clusters present in D. torresensis strains that could be linked to endophytic lifestyle, pathogenicity, plant maceration and degradation of plant tissues as well as adaptation to soil contaminated with metals and metalloids and light response.