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Hay is one of the primary constituents of ruminant feed, and rapid classification systems of nutritional value are essential. A reliable approach to evaluating hay quality is a combination of visual combined inspection by NIRS analysis. The analysis was carried out on 1,639 samples of hay collected from 2016 to 2021 in northern Italy. Discriminant analysis (DAPC) on five hay types (FOM, forage mixtures; APG, first alfalfa cutting with prevalence of graminaceous >50%; PRA, prevailing alfalfa >50%; PUA, purity alfalfa >95%; and PEM, permanent meadows) was performed by ex-ante visual inspection categorization and NIRS analysis. This study aimed to provide a complementary method to differentiate hay types and classify unknown samples. Two scenarios were used: i) all data were used for model training, and the discriminant functions were extracted based on all samples; ii) the assignment of each group was assessed without samples belonging to the training set group. DAPC model resulted in an overall assignment success rate of 66%; precisely, the success was 84, 79, 69, 37, and 27% for PUA, FOM, PRA, APG, and PEM, respectively. In the second scenario, three groups showed percentages of posterior assignment probability higher than 70% to only one group: PUA with PRA (~ 99%), PRA with PUA (~71%), and PEM with FOM (~75%). Discriminant analysis can be successfully used to differentiate hay types and could also be used to assess factors related to hay quality in addition to NIRS analysis.

The aim of this work was to study the yield and nutritional characteristics of winter wheat hay. A selection of cultivars recommended for three main purposes: grain, whole plant (biomass) and dual purpose (grain and biomass) production were cultivated and harvested from heading to grain dough stages. Yield dry weight (YDW), dry matter (DM) and undigested neutral detergent fiber (uNDF) increased with advancing maturity, ranging from 9 t ha−1, 20 and 11% of DM to 16 t ha−1, 43 and 17% of DM, respectively; while crude protein (CP) and neutral detergent fiber (NDF) decreased from 11 and 59% of DM to 6 and 54% of DM, respectively. Our study showed that dual purpose winter wheat cultivars displayed similar performance of CP, NDF and net energy for lactation, when harvested at heading or grain milk stages. In addition, winter wheat recommended to be harvested as whole plant showed similar values of YDW, sugar and starch contents, when harvested at grain dough and milk stages. These characteristics are strategic in hay production, allowing a more flexible harvesting strategy. These results might be useful to improve the hay production, given useful information on harvest time and improving agricultural sustainability covering the soil in autumn and winter.

The objective of the present work was to develop calibration equations for the prediction of chemical composition and forage digestibility from different populations of alfalfa hay harvested in Parmigiano- Reggiano cheese production area of Northern Italy. Due to annual climatic variations that affect soil and growing conditions and consequently cause high variability in chemical and physical composition, 319 hay samples from four years were used to build robust calibration. NIRS calibration equations were developed for the prediction of in vitro NDF digestibility (IVNDFd) and 20 chemical parameters (dry matter, starch, fat, sugar, fiber fractions, crude protein, nitrogen fractions and some minerals) of Italian hay. The results obtained show that NIRS equations greatly explain the variation in the composition existing in alfalfa hays grown in Northern Italy, except for a few parameters characterized by low variability range value. The equations obtained for the prediction of biological and chemical parameters explain the major part of the variation existing in the reference data, which open great prospects for the use of NIRS in planning feeding strategies of livestock, based on alfalfa forage.