Browsing by Person "Petersen, Thies"

Now showing 1 - 2 of 2

Comparing meat and meat alternatives: An analysis of nutrient quality in five European countries
(2023) Petersen, Thies; Hirsch, Stefan
Objective: To assess and compare the (macro-)nutritional composition of red meat (RM) and poultry meat (PM) products with the emerging category of meat substitutes. Design: We use information on nutritional values per 100 g to estimate the differences in the nutritional composition between RM, PM, vegan meat substitute (VMS) and non-vegan meat substitute (NVMS) and derive six unique meat product clusters to enhance the comparability. Setting: Meat markets from five major European countries: France, Germany, UK, Italy and Spain. Participants/Data: Product innovation data for 19 941 products from Mintel’s Global New Product Database from 2010 to 2020. Results: Most of the innovations in the sample are RM products (55 %), followed by poultry (30 %), VMS (11 %) and NVMS (5 %). RM products exhibit a significantly higher energy content in kcal/100 g as well as fat, saturated fat, protein and salt all in g/100 g than the meatless alternatives, while the latter contain significantly more carbohydrates and fibre than either poultry or RM. However, results differ to a certain degree when products are grouped into more homogeneous clusters like sausages, cold cuts and burgers. This indicates that general conclusions regarding the health effects of substituting meat with plant-based alternatives should only be drawn in relation to comparable products. Conclusions: Meat substitutes, both vegan and non-vegan, are rated as ultra- processed foods. However, compared with RM products, they and also poultry products both can provide a diet that contains fewer nutrients-to-limit, like salt and saturated fats.
Shared digital agricultural technology on farms in Southern Germany-analysing farm and socio-demographic characteristics in an inter-farm context
(2025) Gscheidle, Michael; Petersen, Thies; Doluschitz, Reiner; Gscheidle, Michael; Department of Management in Agribusiness, University of Hohenheim, Schwerzstraße 46, 70599, Stuttgart, Germany; Petersen, Thies; Department of Management in Agribusiness, University of Hohenheim, Schwerzstraße 46, 70599, Stuttgart, Germany; Doluschitz, Reiner; Department of Management in Agribusiness, University of Hohenheim, Schwerzstraße 46, 70599, Stuttgart, Germany
Introduction: Up till now, digitalisation in agriculture has almost only been discussed in the context of large farms. However, sooner or later, ongoing digitalisation will reach the agricultural sector as a whole. Indeed, even smaller farms can also benefit from the opportunity and make profitable use of digital agricultural technology by adopting inter-farm organisational forms e.g. collaboration between farmers or contractor services. This article seeks to gain a better understanding of the digital transformation process and to validate relevant forecasts by analysing farm and socio-demographic characteristics that have a possible influence on the likelihood of inter-farm use of digital agricultural technology in general and regardless of the organisational form. Methodological approach: Univariate analysis approaches and bivariate analysis approaches were selected to describe the sample. A binary regression analysis was used to analyse the results of a written online survey of farmers from southern Germany. The characteristics listed in hypotheses H1 to H10 serve as a theory-based conceptual framework for the statistical analysis within the binary logistic regression model. Results: The results of this study are based on a survey sample of 165 farmers, 36.4 % (n=60) of whom use digital agricultural technology on an inter-farm basis. The sample covers n=89 farms from Baden-Württemberg and n=76 from Bavaria. Most of the farmers (87.3 %) considered themselves perfectly capable of using digital technologies confidently after it had been explained to them once (x̅=2.52, s=1.02, scale: 1=completely true to 6=not true at all), with 38.2 % of them using digital agricultural technology across farms, that means they use digital agricultural technology together. Certain factors which can influence the likelihood of inter-farm use of digital agricultural technology in small-scale regions were identified using the binary logistic regression model to analyse the relevant operational and socio-demographic characteristics. Using this methodological approach, eight predictors were identified, three of which have a positive influence on the likelihood of inter-farm use of digital agricultural technology: the availability of two external labourers, the farm's focus on “finishing” or on “other” activities such as taking horses at livery or fattening livestock. Farms that have less than 200 hectares, have no clear succession plan, or whose farm managers are under 30 years old are less likely to use inter-farm digital agricultural technology. Conclusions: In this study, several influencing factors were identified that can play a role in the shared use of digital agricultural technology, especially between farmers in small-scale regions in southern Germany. The empirical results obtained from the binary logistic regression show both positive and negative influences on the likelihood of inter-farm use of digital agricultural technology. Forms of cooperation between farmers play a central role in the establishment and use of capital-intensive digital agricultural systems on farms in southern Germany. The study therefore emphasises that the widespread and economical use of digital agricultural technology in small-scale regions can be achieved quickly, especially through established collaborations between farmers and other stakeholders such as machinery rings or agricultural contractors.