Weckesser, F.; Leßke, F.; Luthardt, M.; Hülsbergen, K. (2021): Conceptual Design of a Comprehensive Farm Nitrogen Management System. Agronomy 11, 2501 (12). DOI: 10.3390/agronomy11122501
Data that are required for nutrient management are becoming increasingly
available in digital format, leading to a high innovation potential for
digital nitrogen (N) management applications. However, it is currently
difficult for farmers to analyze, assess, and optimize N flows in their
farms using the existing software. To improve digital N management, this
study identified, evaluated, and systematized the requirements of
stakeholders. Furthermore, digital farm N management tools with varying
objectives in terms of system boundaries, data requirements, used
methods and algorithms, performance, and practicality were appraised and
categorized. According to the identified needs, the concept of a farm N
management system (FNMS) software is presented which includes the
following modules: (1) management of site and farm data, (2)
determination of fertilizer requirements, (3) N balancing and cycles,
(4) N turnover and losses, and (5) decision support. The aim of FNMS is
to support farmers in their farming practices for increasing N
efficiency and reducing environmentally harmful N surpluses. In this
study, the conceptual requirements from the agricultural and computer
science perspectives were determined as a basis for developing a
consistent, scientifically sound, and user-friendly FNMS, especially
applicable in European countries. This FNMS enables farmers and their
advisors to make knowledge-based decisions based on comprehensive and
integrated data.
Abstract
 Volltext
 
Open Access
Wahmann, R.; Moser, S.; Bieber, S.; Cruzeiro, C.; Schröder, P.; Gilg, A.; Leßke, F.; Letzel, T. (2021): Untargeted Analysis of Lemna minor Metabolites: Workflow and Prioritization Strategy Comparing Highly Confident Features between Different Mass Spectrometers. Metabolites 11, 832 (12). DOI: 10.3390/metabo11120832
Metabolomics approaches provide a vast array of analytical datasets,
which require a comprehensive analytical, statistical, and biochemical
workflow to reveal changes in metabolic profiles. The biological
interpretation of mass spectrometric metabolomics results is still
obstructed by the reliable identification of the metabolites as well as
annotation and/or classification. In this work, the whole Lemna minor
(common duckweed) was extracted using various solvents and analyzed
utilizing polarity-extended liquid chromatography (reversed-phase liquid
chromatography (RPLC)-hydrophilic interaction liquid chromatography
(HILIC)) connected to two time-of-flight (TOF) mass spectrometer types,
individually. This study (introduces and) discusses three relevant
topics for the untargeted workflow: (1) A comparison study of metabolome
samples was performed with an untargeted data handling workflow in two
different labs with two different mass spectrometers using the same
plant material type. (2) A statistical procedure was observed
prioritizing significant detected features (dependent and independent of
the mass spectrometer using the predictive methodology Orthogonal
Partial Least Squares-Discriminant Analysis (OPLS-DA). (3) Relevant
features were transferred to a prioritization tool (the FOR-IDENT
platform (FI)) and were compared with the implemented compound database
PLANT-IDENT (PI). This compound database is filled with relevant
compounds of the Lemnaceae, Poaceae, Brassicaceae, and Nymphaceae
families according to analytical criteria such as retention time
(polarity and LogD (pH 7)) and accurate mass (empirical formula). Thus,
an untargeted analysis was performed using the new tool as a
prioritization and identification source for a hidden-target screening
strategy. Consequently, forty-two compounds (amino acids, vitamins,
flavonoids) could be recognized and subsequently validated in Lemna
metabolic profile using reference standards. The class of flavonoids
includes free aglycons and their glycosides. Further, according to our
knowledge, the validated flavonoids robinetin and norwogonin were for
the first time identified in the Lemna minor extracts.
Abstract
 Volltext
 
Open Access
Krappmann, M.; Leßke, F.; Letzel, T.; Luthardt, M. (2015): The Software-Landscape in (Prote)Omic Research. Journal of Proteomics & Bioinformatics 8 (7), S. 164-175. DOI: 10.4172/jpb.1000365
Abstract
 Volltext
 
Open Access
Donauer, J.; Luthardt, M.; Leßke, F.; Hülsbergen, K. (2021): Development of a web-based farm-nutrient-management system: requirements and model structure, AGROSYM 2021: XII International Agriculture Symposium, Bosnien-Herzegovina.
Weckesser, F.; Hülsbergen, K.; Leßke, F. (2021): Integration of diverse data into a Farm-Nitrogen-Mangement System (FNMs). Mitteilungen der Gesellschaft für Pflanzenbauwissenschaften, 63- Jahrestagung der Gesellschaft für Pflanzenbauwissenschaften e.V., Closing the Cycle: Pflanze und Tier im Agrarsystem Band 32, S. 138.
Weckesser, F.; Hülsbergen, K.; Luthardt, M.; Leßke, F. (2021): Wissensbasierte Entscheidungsunterstützung zum Umbruch von Leguminosen-Gras Beständen. Tagung: Nährstoffmanagement im ökologischen Landbau, 26. und 27. August 2021, TUM School of Life Sciences - Weihenstephan.
Krappmann, M.; Leßke, F.; Letzel, T. (2013): Achroma - a software strategy for analysing (a-)typical mass spectrometric data. Anakon-Tagung, 4. bis 7. März 2013, Essen - Deutschland.
Luthardt, M.; Krappmann, M.; Leßke, F.; Letzel, T. (2012): openMASP – high performance software technology for analytical chemistry. Umweltsymposium, Leipzig - Deutschland.
Krappmann, M.; Luthardt, M.; Wenig, P.; Leßke, F.; Letzel, T. (2011): Cloudy Analytics – High Performance Software Technology for Analytical Chemistry. 8. Langenauer Wasserforum, 07.-08.11.2011, Langenau - Deutschland.
Fakultät Bioingenieurwissenschaften
Am Hofgarten 10
85354 Freising
T +49 8161 71-5780 frank.lesske[at]hswt.de