Optimizing the procedure of grain nutrient predictions in barley via hyperspectral imaging

Hyperspectral imaging enables researchers and plant breeders to analyze various traits of interest like nutritional value in high throughput. In order to achieve this, the optimal design of a reliable calibration model, linking the measured spectra with the investigated traits, is necessary. In the present study we investigated the impact of different regression models, calibration set sizes and calibration set compositions on prediction performance. For this purpose, we analyzed concentrations of six globally relevant grain nutrients of the wild barley population HEB-YIELD as case study. The data comprised 1,593 plots, grown in 2015 and 2016 at the locations Dundee and Halle, which have been entirely analyzed through traditional laboratory methods and hyperspectral imaging. The results indicated that a linear regression model based on partial least squares outperformed neural networks in this particular data modelling task. There existed a positive relationship between the number of samples in a calibration model and prediction performance, with a local optimum at a calibration set size of ~40% of the total data. The inclusion of samples from several years and locations could clearly improve the predictions of the investigated nutrient traits at small calibration set sizes. It should be stated that the expansion of calibration models with additional samples is only useful as long as they are able to increase trait variability. Models obtained in a certain environment were only to a limited extent transferable to other environments. They should therefore be successively upgraded with new calibration data to enable a reliable prediction of the desired traits. The presented results will assist the design and conceptualization of future hyperspectral imaging projects in order to achieve reliable predictions. It will in general help to establish practical applications of hyperspectral imaging systems, for instance in plant breeding concepts

Preference-based algorithms for predicting herbivore diet composition

International audienc

Effects of High Stocking Grazing Density of Diverse Swards on Forage Production, Animal Performance and Soil Organic Matter: A Case Study

Mob grazing is regarded as a grazing management practice to increase soil organic matter, pasture productivity and nutrient cycling. There are different perspectives in the literature regarding the definition of mob grazing, but it is generally accepted that mob grazing is characterised by high stocking densities of livestock which are moved frequently from paddock to paddock (e.g. with the aid of electric fences), trampling forage into the soil as they graze. It has also been recognised that biodiverse pastures have the potential to build up carbon levels in the soil much more effectively than conventional (usually monocultures) or less diverse pastures; in turn all can enhance animal productivity and maintain good herd health. This paper reviews the concept of mob grazing and the benefits of diverse swards and provides evidence whether high stocking density as a grazing strategy can increase soil organic matter and enhance overall animal performance, based on observations on one farm. The grazing rotation applied in the farm during the study year was rather short to fulfil the expectations of a mob-grazing system, but stocking density was high (115 t LW ha−1). The results show that high stocking grazing density of biodiverse pastures has a remarkable effect on the build-up of the soil organic matter and that biodiverse pastures can serve as a viable alternative to conventional pastures as they can maintain animal productivity at high levels

Diet selection of the southern vizcacha (Lagidium viscacia): A rock specialist in north western Patagonian steppe, Argentina

The southern vizcacha (Lagidium viscacia) is a rock specialist that inhabits small colonies in isolated rocky outcrops of northwestern Patagonia. This study analyzes its diet selection in relation to food availability, establishes the degree of dietary specialization, and discusses the potential competition with exotic herbivores. Diet composition and food availability were determined in summer and winter in eight rocky outcrops by microhistological analysis of fecal pellets, and food availability was estimated by the Braun Blanquet cover abundance scale. Vegetation cover differences were detected by using a random analysis of variance (ANOVA) factorial block design, and dietary preferences were determined by the confidence interval of Bonferroni. The southern vizcacha showed a specialized feeding behavior despite the consumption of a wide variety of items. Their diet was concentrated on a few types of food, mainly grasses, and the trophic niche was narrow and without seasonal variations. In winter, when food was scarce and of lower quality than summer, diet was dominated by Stipa speciosa, suggesting a selection according to the selective quality hypothesis. Our results (narrow trophic niche, restricted activity near rocky outcrops, and a diet with high proportions of low-quality grasses) showed that the vizcacha is an obligatory dietary specialist, and these characteristics made it highly vulnerable to changes in food availability. In this scenario, overgrazing caused by alien species with similar diets, as the European hare and livestock, could negatively affect their colonies.Fil: Galende, Gladys I.. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Departamento de Zoología; ArgentinaFil: Raffaele, Estela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte. Instituto de Investigaciones en Biodiversidad y Medioambiente. Universidad Nacional del Comahue. Centro Regional Universidad Bariloche. Instituto de Investigaciones en Biodiversidad y Medioambiente; Argentina. Universidad Nacional del Comahue. Centro Regional Universitario Bariloche. Laboratorio de Ecotono; Argentin