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As recent findings supported new hypotheses regarding the origin and spreading of Podolian breeds, the objectives of the present study were to assess the current genetic diversity and the population structure of five Italian Podolian breeds, and to explore their genetic relationships with the Istrian Cattle (IST) population of Croatia, as Istria peninsula represents the passage between Italian and Balcanic Peninsulas. A total of 373 animals were analyzed using 20 microsatellite markers. The individuals were from seven different breeds: IST (n=113), Romagnola (ROM, n=53), Marchigiana (MAC, n=32), Chianina (CHI, n=30), Maremmana (MAM, n=51), Podolica (POD, n=38), and a reference breed, the Brown Swiss (BRO, n=56). The MAM breed showed the highest gene diversity over all loci (0.726), followed by the POD (0.719) and IST (0.659). The mean observed heterozygosity was 0.580 and it was lower than expected in all breeds. The IST breed appeared genetically very close to the Italian breeds, more similar to Podolian stereotype (POD and MAM; the genetic distances were 0.058 and 0.080, respectively) than to the geographically closer beef type breeds (CHI, MAC, and ROM), suggesting possible ancient trade of animals through the Adriatic Sea. Our results emphasize the importance of monitoring genetic variability in native populations both for conservation purposes and to maintain breed identity and genetic diversity.

Italy counts a large number of local chicken populations, some without a recognized genetic structure, such as Val Platani (VPL) and Cornuta (COS), which represent noteworthy local genetic resources. In this study, the genotype data of 34 COS and 42 VPL, obtained with the Affymetrix Axiom600KChicken Genotyping Array, were used with the aim to investigate the genetic diversity, the runs of homozygosity (ROH) pattern, as well as the population structure and relationship within the framework of other local Italian and commercial chickens. The genetic diversity indices, estimated using different approaches, displayed moderate levels of genetic diversity in both populations. The identified ROH hotspots harbored genes related to immune response and adaptation to local hot temperatures. The results on genetic relationship and population structure reported a clear clustering of the populations according to their geographic origin. The COS formed a nonoverlapping genomic cluster and clearly separated from the other populations, but showed evident proximity to the Siciliana breed (SIC). The VPL highlighted intermediate relationships between the COS-SIC group and the rest of the sample, but closer to the other Italian local chickens. Moreover, VPL showed a complex genomic structure, highlighting the presence of 2 subpopulations that match with the different source of the samples. The results obtained from the survey on genetic differentiation underline the hypothesis that Cornuta is a population with a defined genetic structure. The substructure that characterizes the Val Platani chicken is probably the consequence of the combined effects of genetic drift, small population size, reproductive isolation, and inbreeding. These findings contribute to the understanding of genetic diversity and population structure, and represent a starting point for designing programs to monitor and safeguard these local genetic resources, in order to define a possible official recognition program as breeds.

The aim of this study was to conduct a genome-wide comparative analysis of 8 local Italian chicken breeds (Ermellinata di Rovigo, Millefiori di Lonigo [PML], Polverara Bianca, Polverara Nera, Padovana, Pepoi [PPP], Robusta Lionata, and Robusta Maculata), all under a conservation plan, to understand their genetic diversity and population structure. A total of 152 animals were analyzed using the Affymetrix Axiom 600 K Chicken Genotyping Array. The levels of genetic diversity were highest and lowest in PML and PPP, respectively. The results of genomic inbreeding based on runs of homozygosity (ROH; FROH) showed marked differences among breeds and ranged from 0.161 (PML) to 0.478 (PPP). Furthermore, in all breeds, short ROH (

Background Assessment of genetic diversity and population structure provides important control metrics to avoid genetic erosion, inbreeding depression and crossbreeding between exotic and locally-adapted cattle breeds since these events can have deleterious consequences and eventually lead to extinction. Historically, the Alpine Arc represents an important pocket of cattle biodiversity with a large number of autochthonous breeds that provide a fundamental source of income for the entire regional economy. By using genotype data from medium-density single nucleotide polymorphism (SNP) arrays, we performed a genome-wide comparative study of 23 cattle populations from the Alpine Arc and three cosmopolitan breeds. Results After filtering, we obtained a final genotyping dataset consisting of 30,176 SNPs for 711 individuals. The local breeds showed high or intermediate values of genetic diversity compared to the highly selected cosmopolitan breeds. Patterns of genetic differentiation, multidimensional scaling, admixture analysis and the constructed phylogenetic tree showed convergence, which indicates the presence of gene flow among the breeds according to both geographic origin and historical background. Among the most differentiated breeds, we identified the modern Brown cattle. In spite of admixture events, several local breeds have preserved distinctive characteristics, which is probably due to differences in genetic origin and geographic location. Conclusions This study represents one of the most comprehensive genome-wide analysis of the Alpine cattle breeds to date. Using such a large dataset that includes the majority of the local breeds found in this region, allowed us to expand knowledge on the evaluation and status of Alpine cattle biodiversity. Our results indicate that although many of the analyzed local breeds are listed as endangered, they still harbor a large amount of genetic diversity, even when compared to some cosmopolitan breeds. This finding, together with the reconstruction of the phylogeny and the relationships between these Alpine Arc cattle breeds, provide crucial insights not only into the improvement of genetic stocks but also into the implementation of future conservation strategies.

This study aimed to estimate genetic parameters for 19 linear type traits related to frame, udder, and feet and legs, and for final score of 10,305 first-parity Jersey cows evaluated between 2004 and 2016. Since scoring of locomotion in Jersey breed started in 2009, a subset of 6853 animals was extracted from the original data and used to investigate sources of variation and heritability of locomotion score, and its associations with the other traits. Univariate animal models were used to estimate variance components of type traits and bivariate analyses were implemented to obtain genetic correlations between traits. Fixed effects were herd-year-classifier, season of evaluation, stage of lactation at scoring and age at calving, and the random effects were additive genetic animal and the residual. Herd-year-classifier was the major source of variation affecting the traits. Heritabilities were low with the only exception of a moderate heritability (0.32 ± 0.02) for stature. The lowest heritabilities were estimated for feet and legs traits with values between 0.04 ± 0.02 (rear leg set side view, rear leg set rear view and locomotion) and 0.07 ± 0.02 (foot angle). The final score had heritability of 0.20 ± 0.02. Genetic correlations were generally stronger than their phenotypic counterparts. Overall, frame traits were weakly correlated with feet and legs, and udder traits, except for rump width, which showed moderate correlations with almost all traits, and angularity which showed the greatest correlations with rear udder height (0.61 ± 0.10) and rear udder width (0.62 ± 0.11). Genetic correlations between locomotion and frame traits ranged from 0.08 ± 0.22 (angularity) to 0.32 ± 0.16 (stature). The strongest correlations were estimated between locomotion and other feet and legs traits, but also with front teat placement (0.97 ± 0.19) and with rear teat placement (0.88 ± 0.17). Results of the present study will be used to enhance genetic evaluation of linear type traits in Jersey cattle breed.

Milk mineral concentration is important from both the perspective of processing milk into dairy products and its nutritive value for human consumption. Precise estimates of genetic parameters for milk mineral concentration are lacking because of the considerable resources required to collect vast phenotypes quantities. The milk concentration of calcium (Ca), potassium (K), magnesium (Mg), sodium (Na) and phosphorus (P) in the present study was quantified from mid-IR spectroscopy on 12 223 testday records from 1717 Holstein-Friesian cows. (Co)variance components were estimated using random regressions to model both the additive genetic and within-lactation permanent environmental variances of each trait. The coefficient of genetic variation averaged across days-in-milk (DIM) was 6.93%, 3.46%, 6.55%, 5.20% and 6.68% for Ca, K, Mg, Na and P concentration, respectively; heritability estimates varied across lactation from 0.31 ± 0.05 (5 DIM) to 0.67 ± 0.04 (181 DIM) for Ca, from 0.18 ± 0.03 (60 DIM) to 0.24 ± 0.05 (305 DIM) for K, from 0.08 ± 0.03 (15 DIM) to 0.37 ± 0.03 (223 DIM) for Mg, from 0.16 ± 0.03 (30 DIM) to 0.37 ± 0.04 (305 DIM) for Na and from 0.21 ± 0.04 (12 DIM) to 0.57 ± 0.04 (211 DIM) for P. Genetic correlations within the same trait across different DIM were almost unity between adjacent DIM but weakened as the time interval between pairwise compared DIM lengthened; genetic correlations were weaker than 0.80 only when comparing both peripheries of the lactation. The analysis of the geometry of the additive genetic covariance matrix revealed that almost 90% of the additive genetic variation was accounted by the intercept term of the covariance functions for each trait. Milk protein concentration and mineral concentration were, in general, positively genetically correlated with each other across DIM, whereas milk fat concentration was positively genetically correlated throughout the entire lactation with Ca, K and Mg; the genetic correlation with fat concentration changed from negative to positive with Na and P at 243 DIM and 50 DIM, respectively. Genetic correlations between somatic cell score and Na ranged from 0.38 ± 0.21 (5 DIM) to 0.79 ± 0.18 (305 DIM). Exploitable genetic variation existed for all milk minerals, although many national breeding objectives are probably contributing to an indirect positive response to selection in milk mineral concentration.

Climate change has the potential to adversely affect the health of livestock, with consequences to animal welfare, greenhouse gas emissions, productivity, human health and livelihoods. Phenotypic plasticity is the ability of a genotype to produce different phenotypes, depending on environmental, biotic or abiotic conditions; it is a factor influencing and modifying the genes of animal and plant organisms, to adaptation to climate change. Among the various climate variables, heat stress has been reported to be the most detrimental factor to the economy of the livestock industry. There are a number of candidate genes that are associated with adaptation of ruminants, monogastric and poultry to heat stress. For instance, the genes encoding leptin, thyroid hormone receptor, insulin growth factor-1, growth hormone receptor, are associated with the impacts of heat stress on the physiological pathways of domestic animals such as dairy cows, beef cattle, buffaloes, poultry, pigs and horses. This review aims to highlight genes and traits that are involved with thermo-tolerance of domestic animals to sustain production and to cope with climate change. Selection and experimental evolution approaches have shown that plasticity is a trait that can evolve when under direct selection and has a correlated response to some specific traits. Therefore, new breeding goals should be defined for the potential of livestock species to acquire plasticity for adaptation to the current climate changing conditions.Highlights Heat stress compromises feed intake, growth, milk and meat quality and quantity, resulting in a significant financial burden to global livestock. Genetic selection and nutritional intervention are key strategies to consider in Animal Genetic Resources in hot environments. Information from gene expression or genome-wide association studies can be used to further improve the accuracy of selection.

Identifying genomic regions involved in the differences between breeds can provide information on genes that are under the influence of both artificial and natural selection. The aim of this study was to assess the genetic diversity and differentiation among four different Brown cattle populations (two original vs. two modern populations) and to characterize the distribution of runs of homozygosity (ROH) islands using the Illumina Bovine SNP50 BeadChip genotyping data. After quality control, 34735 SNPs and 106 animals were retained for the analyses. Larger heterogeneity was highlighted for the original populations. Patterns of genetic differentiation, multidimensional scaling, and the neighboring joining tree distinguished the modern from the original populations. The FST-outlier identified several genes putatively involved in the genetic differentiation between the two groups, such as stature and growth, behavior, and adaptability to local environments. The ROH islands within both the original and the modern populations overlapped with QTL associated with relevant traits. In modern Brown (Brown Swiss and Italian Brown), ROH islands harbored candidate genes associated with milk production traits, in evident agreement with the artificial selection conducted to improve this trait in these populations. In original Brown (Original Braunvieh and Braunvieh), we identified candidate genes related with fat deposition, confirming that breeding strategies for the original Brown populations aimed to produce dual-purpose animals. Our study highlighted the presence of several genomic regions that vary between Brown populations, in line with their different breeding histories.

Milk coagulation and acidity traits are important factors to inform the cheesemaking process. Those traits have been deeply studied in bovine milk, whereas scarce information is available for buffalo milk. However, the dairy industry is interested in a method to determine milk coagulation and acidity features quickly and in a cost-effective manner, which could be provided by Fourier-transform mid-infrared (FT-MIR) spectroscopy. The aim of this study was to evaluate the potential of FT-MIR to predict coagulation and acidity traits of Mediterranean buffalo milk. A total of 654 records from 36 herds located in central Italy with information on milk yield, somatic cell score, milk chemical composition, milk acidity [pH, titratable acidity (TA)], and milk coagulation properties (rennet coagulation time, curd firming time, and curd firmness) were available for statistical analysis. Reference measures of milk acidity and coagulation properties were matched with milk spectral information, and FT-MIR prediction models were built using partial least squares regression. The data set was divided into a calibration set (75%) and a validation set (25%). The capacity of FT-MIR spectroscopy to correctly classify milk samples based on their renneting ability was evaluated by a canonical discriminant analysis. Average values for milk coagulation traits were 13.32 min, 3.24 min, and 39.27 mm for rennet coagulation time, curd firming time, and curd firmness, respectively. Milk acidity traits averaged 6.66 (pH) and 7.22 Soxhlet-Henkel degrees/100 mL (TA). All milk coagulation and acidity traits, except for pH, had high variability (17 to 46%). Prediction models of coagulation traits were moderately to scarcely accurate, whereas the coefficients of determination of external validation were 0.76 and 0.66 for pH and TA, respectively. Canonical discriminant analysis indicated that information on milk coagulating ability is present in the MIR spectra, and the model correctly classified as noncoagulating the 91.57 and 67.86% of milk samples in the calibration and validation sets, respectively. In conclusion, our results can be relevant to the dairy industry to classify buffalo milk samples before processing.

This study aimed to investigate factors affecting protein fractions, namely &alpha, casein (&alpha, CN), &beta, casein (&beta, CN), &kappa, casein (&kappa, lactoglobulin (&beta, LG) and &alpha, lactalbumin (&alpha, LA) predicted from milk infrared spectra in milk of dairy and dual-purpose cattle breeds. The dataset comprised 735,328 observations from 49,049 cows in 1782 herds. Results highlighted significant differences of protein fractions in milk of the studied breeds. Significant variations of protein fractions were found also through parities and lactation, with the latter thoroughly influencing protein fractions percentage. Interesting correlations (r) were estimated between &beta, CN, &kappa, CN and &beta, LG, expressed as percentage of crude protein, and milk urea nitrogen (r = 0.31, &minus, 0.20 and &minus, 0.26, respectively) and between &alpha, LA and fat percentage (r = 0.41). The present study paves the way for future studies on the associations between protein fractions and milk technological properties, and for the estimation of genetic parameters of predicted protein composition.

The aim of the present study was to assess the relationships of lactose percentage (LP), lactose yield (LY), and freezing point (FRP) with minerals and coagulation properties predicted from mid-infrared spectra in bovine milk. To achieve this purpose, we analyzed 54,263 test-day records of 4,297 Holstein cows to compute (co)variance components with a linear repeatability animal model. Parity, stage of lactation, season of calving, and herd-test-date were included as fixed effects in the model, and additive genetic animal, within- and across-lactation permanent environment, and residual were included as random effects. Lactose percentage was more heritable (0.405 ± 0.027) than LY (0.121 ± 0.021) and FRP (0.132 ± 0.014). Heritabilities (± standard error) of predicted milk minerals varied from 0.375 ± 0.027 for Na to 0.531 ± 0.028 for P, and those of milk coagulation properties ranged from 0.348 ± 0.052 for rennet coagulation time to 0.430 ± 0.026 for curd firming time. Lactose percentage showed favorable (negative) genetic correlations with milk somatic cell score (SCS) and FRP, and it was almost uncorrelated with casein-related minerals (Ca and P) and coagulation properties. Moreover, LP was strongly correlated with Na (-0.783 ± 0.022), a mineral known to increase in the presence of intramammary infection (IMI) and high somatic cell count. Indeed, Na is the main osmotic replacer of lactose in mastitic milk when the blood-milk barrier is altered during IMI. Being strongly associated with milk yield, LY did not favorably correlate with coagulation properties, likely because of the negative correlation of this trait with protein and casein percentages. Milk FRP presented moderate and null genetic associations with Na and SCS, respectively. Results of the present study suggest that the moderate heritability of LP and its genetic correlations with IMI-related traits (Na and SCS) could be exploited for genetic selection against mastitis. Moreover, selection for LP would not impair milk coagulation characteristics or Ca and P content, which are important for cheesemaking.

The objective of the present study was to estimate the effect of breed on milk fatty acid (FA) composition of dairy (Brown Swiss, Holstein-Friesian, and Jersey) and dual-purpose cows (Simmental and Alpine Grey) in multi-breed herds. Information on individual milk samples was collected during routine cow milk testing between 2011 and 2014, and consisted of 285 606 observations from 17 445 cows in 617 herds. Fixed effects included in the mixed model were breed, parity, stage of lactation and the interaction between parity and stage of lactation, and random effects were cow, herd-test-date and residual. Contrast estimates for the studied traits were used to compare specific sets of breeds. Holstein-Friesian produced more milk than the other cattle breeds, with the greatest trans FA and C18:1 and the lowest C18:0 content. Comparison between the specialised dairy vs the dual-purpose breeds highlighted significant differences for all traits except for polyunsaturated FA and trans FA content. Specialised dairy breeds had greater milk saturated FA, short-chain FA, medium-chain FA, C14:0 and C16:0 content, and dual-purpose breeds produced milk with greater content of monounsaturated FA, long-chain FA, C18:0 and C18:1. Results demonstrated that, although specialised dairy produced more milk than dual-purpose breeds, milk FA profile of the latter was more favourable from a human nutrition point of view.

Milk minerals and coagulation properties are important for both consumers and processors, and they can aid in increasing milk added value. However, large-scale monitoring of these traits is hampered by expensive and time-consuming reference analyses. The objective of the present study was to develop prediction models for major mineral contents (Ca, K, Mg, Na, and P) and milk coagulation properties (MCP: rennet coagulation time, curd-firming time, and curd firmness) using mid-infrared spectroscopy. Individual milk samples (n = 923) of Holstein-Friesian, Brown Swiss, Alpine Grey, and Simmental cows were collected from single-breed herds between January and December 2014. Reference analysis for the determination of both mineral contents and MCP was undertaken with standardized methods. For each milk sample, the mid-infrared spectrum in the range from 900 to 5,000 cm−1 was stored. Prediction models were calibrated using partial least squares regression coupled with a wavenumber selection technique called uninformative variable elimination, to improve model accuracy, and validated both internally and externally. The average reduction of wavenumbers used in partial least squares regression was 80%, which was accompanied by an average increment of 20% of the explained variance in external validation. The proportion of explained variance in external validation was about 70% for P, K, Ca, and Mg, and it was lower (40%) for Na. Milk coagulation properties prediction models explained between 54% (rennet coagulation time) and 56% (curd-firming time) of the total variance in external validation. The ratio of standard deviation of each trait to the respective root mean square error of prediction, which is an indicator of the predictive ability of an equation, suggested that the developed models might be effective for screening and collection of milk minerals and coagulation properties at the population level. Although prediction equations were not accurate enough to be proposed for analytic purposes, mid-infrared spectroscopy predictions could be evaluated as phenotypic information to genetically improve milk minerals and MCP on a large scale.

Simple Summary In order to assess sources of variation related to Polverara breed plumage color (black vs. white), we carried out genome-wide analyses to identify the genomic regions involved in this trait. The present work has revealed new candidate genes involved in the phenotypic variability in local chicken populations. These results also contribute insights into the genetic basis for plumage color in poultry, and confirm the great complexity of the mechanisms that control this trait. Abstract Through the development of the high-throughput genotyping arrays, molecular markers and genes related to phenotypic traits have been identified in livestock species. In poultry, plumage color is an important qualitative trait that can be used as phenotypic marker for breed identification. In order to assess sources of genetic variation related to the Polverara chicken breed plumage colour (black vs. white), we carried out a genome-wide association study (GWAS) and a genome-wide fixation index (FST) scan to uncover the genomic regions involved. A total of 37 animals (17 white and 20 black) were genotyped with the Affymetrix 600 K Chicken single nucleotide polymorphism (SNP) Array. The combination of results from GWAS and FST revealed a total of 40 significant markers distributed on GGA 01, 03, 08, 12 and 21, and located within or near known genes. In addition to the well-known TYR, other candidate genes have been identified in this study, such as GRM5, RAB38 and NOTCH2. All these genes could explain the difference between the two Polverara breeds. Therefore, this study provides the basis for further investigation of the genetic mechanisms involved in plumage color in chicken.

Lactose percentage (LP) in milk is currently determined in most herd-testing schemes, and globally, it is usually routinely recorded in the framework of the official milk recording procedures. However, few studies have investigated the phenotypic and genetic variability of this component. Data used in the present paper consisted of 59 811 test-day records from 4355 Holstein cows in 266 herds. Heritabilities of LP and lactose yield (LY) were estimated through single-trait repeatability animal models, whereas genetic and phenotypic correlations of LP and LY with milk composition and production traits, somatic cell score and milk freezing point were estimated using bivariate models. Fixed effects included in the analyses were herd-test-date, season of calving, parity, stage of lactation and the interaction between parity and stage of lactation. Random effects were animal additive genetic, within and across lactation permanent environment and the residual. Lactation curves of LP and LY increased from parturition to the peak of lactation and decreased thereafter, mirroring the typical curve of milk yield. Lactose percentage was greater in first- than later-parity cows. Heritabilities of LP and LY were 0.43 ± 0.03 and 0.14 ± 0.02, respectively, and LP and protein percentage were the most repeatable traits. Genetic correlations (ra) of LP with somatic cell score, LY and milk freezing point were −0.22 ± 0.08, 0.28 ± 0.08 and −0.46 ± 0.05, respectively. Genetic relationships of LY with milk yield (ra = 0.97 ± 0.00), fat percentage (ra = −0.71 ± 0.06), protein percentage (ra = −0.57 ± 0.06) and protein yield (ra = 0.64 ± 0.06) were moderate to strong. Results suggest that milk LP could be considered in breeding strategies to accelerate the gain of correlated low heritable traits. Further research is needed to evaluate the feasibility of including LP in the selection index of Italian Holstein population to address country-specific needs and market demands.

The aim of the present study was to characterize alternative somatic cell count (SCC) traits that could be exploited in genetic selection for mastitis resistance. Data were from 66,407 first-parity Holsteins in 404 herds. Novel SCC traits included average somatic cell score (SCS, log-transformation of SCC) in early lactation (SCS_150), standard deviation of SCS of the entire lactation (SCS_SD), the presence of at least one test-day (TD) SCC >400,000 cells/mL in the lactation, and the ratio of number of TD SCC >400,000 cells/mL to total number of TD in the lactation. Novel traits and lactation-mean SCS (SCS_LM) were analyzed using linear mixed or logistic regression models, including month of calving, year of calving, number of TD, and milk yield as fixed effects, and herd and residual as random terms. A multitrait linear animal model was applied to a random subset of 152 herds (n = 22,695 cows) to assess heritability of and genetic correlations between SCC traits. Alternative SCC traits were affected by the environmental factors included in the model; in particular, results suggested a seasonal effect and a tendency toward an improvement of the udder health status in the last years. Association was also found between novel SCC traits and milk production. Alternative SCC traits exhibited coefficients of additive genetic variation that were similar to or larger than that of traditional SCS_LM. Heritability of novel SCC traits was smaller than heritability of SCS_LM (0.126 ± 0.014), ranging from 0.044 ± 0.008 (SCS_SD) to 0.087 ± 0.010 (SCS_150). Genetic correlations between SCC traits ranged from 0.217 ± 0.096 (SCS_150 and SCS_SD) to 0.969 ± 0.010 (SCS_LM and SCS_150). Alternative SCC traits exhibited additive genetic variation that is potentially exploitable in breeding programs of Italian Holstein population to improve resistance to mastitis.

Milk and dairy products are important sources of macro- and trace elements for human health. However, fresh cheeses usually have a lower mineral content than other cheeses, and this makes mineral prediction more difficult. Although mineral prediction in several food matrices using infrared spectroscopy has been reported in the literature, very little information is available for cheeses. The present study was aimed at developing near-infrared reflectance (NIR, 866-2,530 nm) and transmittance (NIT, 850-1,050 nm) spectroscopy models to predict the major mineral content of fresh cheeses. We analyzed samples of mozzarella (n = 130) and Stracchino (n = 118) using reference methods and NIR and NIT spectroscopy. We developed prediction models using partial least squares regression analysis, and subjected them to cross- and external validation. Average Na content was 0.15 and 0.22 g/100 g for mozzarella and Stracchino, respectively. The NIR and NIT spectroscopy performed similarly, with few exceptions. Nevertheless, none of the prediction models was accurate enough to replace the current reference analysis. The most accurate prediction model was for the Na content of mozzarella cheese using NIT spectroscopy (coefficient of determination of external validation = 0.75). We obtained the same accuracy of prediction for P in Stracchino cheese with both NIR and NIT spectroscopy. Our results confirmed that mineral content is difficult to predict using NIT and NIR spectroscopy.