A non-destructive and novel in situ acoustic sensor approach based on the sound absorption spectra was developed for identifying and classifying different seed types. The absorption coefficient spectra were determined by using the impedance tube measurement method. Subsequently, a multivariate statistical analysis, i.e., principal component analysis (PCA), was performed as a way to generate a classification of the seeds based on the soft independent modelling of class analogy (SIMCA) method. The results show that the sound absorption coefficient spectra of different seed types present characteristic patterns which are highly dependent on seed size and shape. In general, seed particle size and sphericity were inversely related with the absorption coefficient. PCA presented reliable grouping capabilities within the diverse seed types, since the 95% of the total spectral variance was described by the first two principal components. Furthermore, the SIMCA classification model based on the absorption spectra achieved optimal results as 100% of the evaluation samples were correctly classified. This study contains the initial structuring of an innovative method that will present new possibilities in agriculture and industry for classifying and determining physical properties of seeds and other materials.

One of the main parameters affecting forage management and quality is density. Existing methods used for measuring physical properties of forage involve costly destructive analysis. A frequent and appropriate control of the forage density is required for optimizing the management of silage, hay and straw production; therefore, there is a need to develop a new measurement method. The sound insulation properties of a material are governed by its physical structure. Based on this, an inexpensive, non-destructive acoustic measurement method using sound insulation properties was developed to determine forage density. The method has been used to analyse the correlation of the density with the sound insulation spectra produced by smallscale models of hay, silage and straw. Results show that the sound insulation spectra of forage have a high correlation with the density and a significant congruence with the physical structure of the targeted forage types. The findings are highly relevant for innovative applications in agriculture, animal nutrition and bioenergy production in terms of material properties monitoring, materials classification and quality determination.

This PhD thesis is the outcome of three intensive but stimulating years of research. These pages will present the "end product", but will fall short in describing the personal and professional development triggered by this remarkable journey. These pages hide a myriad of experiences, lessons and wisdom from colleagues, interviewees and friends, which make me still wonder why I am the only author on the front page. I would like to wholeheartedly thank my supervisors Claus Aage Grøn Sørensen and Frank Willem Oudshoorn for their valuable guidance, mentorship, and encouragement, which have been the essential ingredients allowing the completion of this remarkable journey. You have greatly steered my progress and have always provided me with the space required for expanding my scientific curiosity. I am also tremendously grateful to my "adopted" supervisor Henrik Moller from the University of Otago, whose wisdom, love for rigorous science and will to share, have definitely shaped me as a scientist. I am also very thankful for all knowledge exchanges and discussions with my various co-authors, including Andrew Barber, Evelien de Olde, and Hans Henrik Pedersen. I would like to express my sincere gratitude to the farmers and other stakeholders that generously participated in sharing their data, experiences and views. Without you, this research would not have been possible. I would like to thank Niels Clement Justesen and the Sønderjysk advisory service for sharing their knowledge. I also would like to thank Sustainable Wine-growing New Zealand for sharing their precious database. Furthermore, I would like to thank Ole Green for supporting the start-up of this project and believing in me, the Centre for Sustainability of the University of Otago and Jon Manhire from the Agribusiness Group for providing me a very warm and productive stay in New Zealand, and Soren Moller and Florence Bedoin for their assistance during the writing process. Finally, the sweetest of my thanks goes to my family and beloved friends for encouraging me and sharing with me all their unconditional love in this life journey.