Oats are known for their nutritional value and also for their beneficial properties on human health, such as the reduction of cholesterol levels and risk of coronary heart disease; they are an important export product for Chile. During the last decade (2010-2022) over 90% of the oat cultivated area in Chile has been covered with Avena sativa L. cv. Supernova INIA. This lack of genetic diversity in a context of climate change could limit the long-term possibility of growing oats in Chile. The present study is a phenotypic and genetic analysis of 132 oat cultivars and pure lines of diverse origin that can be considered as potential breeding material. The germplasm was evaluated for 28 traits and analyzed with 14 SSR markers. The effects of genotypes on phenotype were significant over all traits (P ≤ 0.05). Most traits exhibited moderate to high broad-sense heritability with exceptions such as yield (H2 = 0.27) and hulls staining (H2 = 0.32). Significant undesirable correlations between traits were generally of small biological importance, which is auspicious for achieving breeding objectives. Some of the heritability data and correlations provided here have not been previously reported. The overall phenotypic diversity was high (H’ = 0.68 ± 0.18). The germplasm was grouped into three phenotypic clusters, differing in their qualities for breeding. Twenty-six genotypes outperforming Supernova INIA were identified for breeding of conventional food-oats. The genetic diversity of the germplasm was moderate on average (He = 0.58 ± 0.03), varying between 0.32 (AM22) and 0.77 (AME178). Two genetic subpopulations supported by the Structure algorithm exhibited a genetic distance of 0.24, showing low divergence of the germplasm. The diversity and phenotypic values found in this collection of oat genotypes are promising with respect to obtaining genetic gain in the short term in breeding programs. However, the similar genetic diversity, higher phenotypic diversity, and better phenotypic performance of the germplasm created in Chile compared to foreign germplasm suggest that germplasm harboring new genetic diversity will be key to favor yield and quality in new oat cultivars in the long term.

The chemical composition and quality of honey depend on the floral and geographical origin, extraction techniques, and storage, resulting in a unique product for each area. Currently, consumers are not only concerned about the chemical composition, quality, and food safety of honey, but also about its origin. The objective of this study was to characterize honeys produced in Chile's central-southern region from a mineral and botanical perspective, thus adding value through differentiation by origin. Two hundred honey samples were used and underwent analysis such as melissopalynological composition, nutritional composition, and color. Forty-seven melliferous floral species were identified, out of which 24 correspond to exotic species and 23 to native species. Fifty-six percent were classified as monofloral honeys, 2% as bifloral, and 42% as multifloral. Moisture mean values (17.88%), diastase activity (15.53 DN), hydroxymethylfurfural (2.58 mg/kg), protein (0.35%), and ash (0.25%) comply with the ranges established by both the national and the international legislation; standing out as honeys of great nutritional value, fresh, harvested under optimal maturity conditions, and absence fermentation. Regarding color, light amber was prevalent in most territories. The territory where honey was produced, denoted relevant differences in all the parameters studied.

Este boletin fue editado por el Centro Regional de Investigaciones INIA Remehue, Instituto de Investigaciones Agropecuarias. Ministerio de Agricultura, como parte del proyecto “Capacitacion para la valorizacion Sello de Origen Productos Silvoagropecuarios”, BIP: 30341173. Financiado por el Gobierno Regional de Los Lagos y ejecutado por INIA en conjunto a la Seremia de Agricultura.

Increases in cereals grain yield in the last decades have increased the accumulation of straw on the soil after harvest. Farmers typically open burn the straw to prepare the soil for the next crop, resulting in pollution, emission of greenhouse gases, erosion, loss of soil organic matter, and wildfires. An alternative is feeding straw to ruminants, but straw nutritive value is limited by its high content of lignocellulose and low content of protein. Cereal breeding programs have focused on improving grain yield and quality and agronomic traits, but little attention has been paid to straw nutritive value. We screened straw from 49 genotypes of oats and 24 genotypes of wheat from three cereal breeding trials conducted in Chile for in vitro gas production kinetics. We found moderate effects of the genotype on gas production at 8, 24, and 40 h of incubation, and on the maximum extent and rate of gas production. Gas production was negatively associated with lignin and cellulose contents and not negatively associated with grain yield and resistance to diseases and lodging. Effects observed in vitro need to be confirmed in animal experiments before gas production kinetics can be adopted to identify cereal genotypes with more digestible straw.

The quantification of nutrient concentration in soils is important for the implementation of adequate fertilization strategies, and also to improve agricultural productivity. In recent decades, new instrumental methods have been developed, including the use of near infrared spectroscopy (NIRS). Although its potential has been recognized by soil scientists for a few decades, the use of NIRS for routine soil analysis has been, to the best of our knowledge, poorly developed in Chile. Calibration models were developed by partial least squares regression (PLSR). The objective of this study was to assess the use of NIRS for the determination of concentrations of Calcium, Magnesium, Phosphorus, Potassium, pH (water), organic matter, Sodium, exchangeable aluminum, ammonium and nitrate in volcanic soils of southern Chile. The coefficient of determination in the calibration obtained ranged from 0.79 to 0.95 and 0.79 to 0.89 in Andisols and Ultisols, respectively. The residual prediction deviation (RPD) values varied between 2.1 and 4.4 in Andisols, and between 2.2 and 3.1 in Ultisols. It was not possible to generate robust calibration models for Al Exch, Na and NH4+ in Andisols and Al Exch, Mg, NO3- and Na in Ultisols. Although some of the models developed presented high R-2, this methodology requires further validation, including a greater number of samples from a wider spatial distribution, covering a variety of climatic and agricultural conditions.

Improving nitrogen (N) utilization efficiency (NUtE (kg dry matter (DM) kg(-1) N uptake)) is one of the challenges of modern grassland systems in order to improve nitrogen use efficiency. The NUtE is highly variable in response to climate and N supply. Therefore, NUtE must be assessed in relation to the N nutrition index (NNI) and forage yield in pastures growing under different N supplies and environments. The aim of this study was to assess NUtE and NNI in response to different ryegrass genotypes, N supplies and harvest times. Two experiments were conducted in southern Chile for this purpose. In each experiment, treatments were the factorial combination of two hybrid ryegrass cultivars (Shogun and Trojan) and seven N fertilization rates (0, 50, 100, 200, 350, 525 and 700 kg N ha(-1) yr(-1)). A wide range in N uptake, NUtE and NNI were observed (N uptake: 4 - 134 kg N ha(-1); NUtE: 20 - 71 kg DM kg(-1) N uptake; NNI: 0.23 - 1.43) across experiments. The main sources of variation of the above-mentioned variables were N rates and harvest times. Across experiments, the NUtE was described by a negative power function (R-2 = 0.77, P < 0.01) in relation to the NNI and the remaining variability in NUtE was well explained by the forage yield, demonstrating that NUtE depends on the N nutritional status and forage yield. A reference NUtE of 29 +/- 5.1 kg DM kg(-1) is proposed for grasslands growing at optimal N status (NNI = 1). Therefore, both the NNI and forage yield must be taken into account when interpreting how NUtE responds to genotypes cultivated under different N availabilities and growing conditions.

High levels of animal performance and health depend on high-quality nutrition. Determining forage quality both reliably and quickly is essential for improving animal production. The present study describes the use of near infrared reflectance spectroscopy (NIRS) for the quantification of nutritional quality (dry matter (DM), water-soluble carbohydrates (WSC), crude protein (CP), in vitro dry matter digestibility (DMD), organic matter digestibility (OMD), neutral detergent fiber (NDF) and the WSC/CP ratio) in samples from fresh pastures in southern Chile (39° to 40° S). Calibration models were developed with wet chemistry and NIRS spectral data using partial least squares regression (PLSR). The coefficients of determination in the validation set ranged between 0.69 and 0.93, and the error of prediction varied from 0.064 to 2.89. The evaluation of the model confirmed the high predictive ability of NIRS for DM and CP and its low predictive ability for DMD, OMD, NDF and the WSC/CP ratio. It was not possible to obtain a model for WSC because it would have required an increased number of samples to improve the spectral variability and the R2 value (> 80%).

One of the challenges of modern grassland systems is to minimize nitrogen (N) fertilization without negatively affecting the forage yield. Therefore, critical N dilution curves (Nc = a(c) W-b) have been developed in different species to improve N fertilization management. The aim of this study was to validate a critical N dilution curve for hybrid ryegrasses. Two field experiments were conducted in southern Chile. Treatments were the factorial combination of two hybrid ryegrasses (Shogun and Trojan cultivars) and seven N fertilization rates (0, 50, 100, 200, 350, 525 and 700 kg N/ha). Factors were arranged in a split-plot design, where forage species were assigned to main plots and N rates to subplots that were randomized into four blocks. A wide range in forage yield and plant N concentration was observed (yield: 0.16 and 3.9 Mg DM/ha and N: 1.6% and 5.1%). The variations in these traits were principally explained by the N levels and harvest times. Relative yield responses of both cultivars were significantly (p , R-2 = 0.81-0.87) related to the nitrogen nutrition index (NNI) calculated with different critical N dilution curves. However, the NNI calculated with N dilution curves from annual ryegrass best described the relative yield response of hybrid ryegrass. Therefore, this validated critical N dilution curve (%N-c = 4.1W(-0.38)) will serve as a useful diagnosis tool for improving the N fertilization management of grazing systems for hybrid ryegrasses.

In temperate climates, cold stress constrains productivity of white clover (Trifolium repens L.), the most important perennial forage legume in intensive grazing systems for ruminants. Metabolism of water sugar carbohydrate (WSC) has been proposed as an important trait conferring cold tolerance to white clover. Conventional methodologies for WSC determination are considered high-cost and time-consuming. Near-infrared (NIR) spectroscopy is a robust, reliable, and high-throughput methodology to estimate chemical composition of forage species. The objectives of this work were to determine the accuracy of NIR spectroscopy for predicting WSC in stolon samples of white clover, and to evaluate the genetic relationship between WSC and cold tolerance. A white clover association mapping (WCAM) population was stablished in three location that represent a winter low temperature gradient associated with altitude. Dry matter production and some morphological traits were evaluated during three growing seasons. Samples for WSC determination were collected three time during a winter period. Samples were scanned with a NIR system, and a prediction model for WSC was fitted using partial least squares (PLS) regression. The adjusted prediction model achieved suitable predictive ability (R2 > 0.85). The WSC per se did not show significant genetic relationship with morphological and agronomically important traits. However, the WSC degradation rate (WSCdr) across the winter period showed significant genetic correlation with DM production during spring (rg = 0.64), which is the result of genetic/physiological mechanism expressed during the cold period. The NIR spectroscopy is a reliable and high-throughput methodology to predict WSC in stolon samples of white clover. The metabolism of WSC, evaluated as WSCdr, is involved in the cold tolerance of the WCAM population. The methodology implemented in this work is suitable to be applied in a plant breeding program routine.

In pasture systems of southern Chile, nitrogen (N) fertilization is mostly carried out without considering soil N supply, while seasonal N plant uptake is partially accounted for. These aspects are fundamental to correctly decide N fertilization. The aim of this work was to determine soil N contribution to grasslands yield in southern Chile and its implication for N use efficiency. Three treatments were distributed in a completely randomized block design with four replicates. A negative control treatment without N application and a positive control without N deficiency (450 kg N ha(-1)) were considered. An optimized treatment was also used, so that the total amount of mineral N applied as fertilizer was only that necessary to account for the arithmetic difference among plant uptake and N soil supply, resulting in the application of 171 kg N ha(-1) only. Soil mineralization was high (241-934 kg N ha(-1)) and strongly affected by soil available N (VIP > 0.8). The 450 kg N ha-1 treatment produced 1,726 kg DM more than the 171 kg N ha(-1) treatment. Nevertheless, this increase was associated to the application of an extra 279 kg N ha(-1), so that the extra yield was produced at a 6 kg DM kg(-1) N efficiency. This value was one third of that showed by the optimized treatment, which was 1.8 times more efficient in the use of N than the 450 kg N ha(-1) treatment, on average. Results suggest that it is possible to adjust pasture's N fertilization considering soil N contribution via mineralization, and that this improves resources efficiency while maintaining pasture productivity.