Vergleichende ökonomisch-ökologische Analyse von biologisch und konventionell wirtschaftenden Betrieben in Luxemburg („öko-öko“)

International gibt es zahlreiche vergleichende Untersuchungen von ökonomischen oder ökologischen Leistungen von biologisch und konventionell wirtschaftenden Betrieben (Baumgartner et al., 2010; Offermann and Nieberg, 2000; Olesen et al., 2006). Dabei werden meist aber entweder ökonomische oder ökologische Wirkungen untersucht. Studien, die beide Aspekte zu einer übergreifenden Sichtweise vereinen, sind rar (Schader, 2009). Dabei sind gerade solche integrierte Studien aus agrarpolitscher Sicht höchst relevant. Denn bei der Gestaltung der Gemeinsamen Agrarpolitik (GAP) auf Mitgliedsstaatenebene spielt die Frage der Ausrichtung der Maßnahmen eine zentrale Rolle. Die Pläne zur ländlichen Entwicklung und die darin beinhalteten Agrarumweltprogramme bilden die 2. Säule der GAP, die während der letzten Jahre im Vergleich zur ersten Säule finanziell an Bedeutung gewann. Eine dieser Maßnahmen ist die Flächen- und Umstellungsförderung des biologischen Landbaus, welche in allen Mitgliedsstaaten implementiert wird. Während die Effektivität der Maßnahme in der Erbringung von Umweltleistungen wenig umstritten ist, streiten sich Ökonomen, ob der biologische Landbau diese Umweltleistungen auch kostengünstig erbringen kann (Dabbert, 2002). Kürzlich zeigte Schader (2009), dass hier keine grundsätzlichen Vorbehalte vorgebracht werden müssen, die Effizienz aber regions- und länderspezifisch evaluiert werden sollte. In der Politikevaluation spricht man hier von sogenannten „targeting and tailoring“ (OECD, 2007) der Maßnahmen. Auch in Luxemburg, einem Land in dem die Entwicklung des biologischen Landbaus bisher vergleichsweise schleppend voranging, ist diese Frage von agrarpolitischer Relevanz. Gerade im Zusammenhang des 2009 ins Leben gerufenen „Aktionsplan für biologische Landwirtschaft Luxemburg“ stellt sich die Frage, zu welchen Kosten die biologisch wirtschaftenden Betriebe Umweltleistungen erfüllen und ob diese Zahlungen angemessen sind. Eine derartige Evaluationsstudie ist bisher in Luxemburg nicht durchgeführt worden. Die vorliegende Studie versucht diese Wissenslücke zu schließen. Dabei wird das Ziel verfolgt, die ökologischen Leistungen und monetären Kosten der biologisch wirtschaftenden Betriebe in Luxemburg vergleichbaren konventionellen Betrieben gegenüberzustellen. Daraus sollen Aussagen über die ökologische Effektivität und die ökonomische Effizienz der biologischen Wirtschaftsweise in Luxemburg abgeleitet werden. In dem Projekt „öko-öko“ werden ökologische Wirkungen von Biobetrieben und konventionellen Betrieben in Luxemburg verglichen. Zusätzlich wird die betriebswirtschaftliche Situation und die Förderung der verschiedenen Betriebe beleuchtet. Daraufhin werden die ökonomischen und ökologischen Größen miteinander in Beziehung gesetzt, um Erkenntnisse für eine Optimierung der Effektivität und Effizienz der Förderung der Biobetriebe in Luxemburg zu gewinnen. Dazu wird zunächst eine Übersicht über die vorhandene Literatur gegeben (Kapitel 2). In Kapitel 3 wird der methodische Zugang erläutert, der für diese Studie gewählt wurde und die Datengrundlage wird kurz beschrieben. Dies beinhaltet auch eine kurze Analyse der Betriebsstruktur der Stichprobe der analysierten Betriebe. Danach werden die ökologischen (Kapitel 4) und ökonomischen (Kapitel 5) Parameter analysiert und diskutiert. Kapitel 6 analysiert die Kosteneffizienz der Zahlungen an biologisch wirtschaftende Betriebe. In Kapitel 7 werden Schlussfolgerungen aus den Ergebnissen der Studie für die Wissenschaft und Agrarpolitik abgeleitet

Il Futuro della Cybersecurity in Italia: Ambiti Progettuali Strategici

Il presente volume nasce come continuazione del precedente, con l’obiettivo di delineare un insieme di ambiti progettuali e di azioni che la comunità nazionale della ricerca ritiene essenziali a complemento e a supporto di quelli previsti nel DPCM Gentiloni in materia di sicurezza cibernetica, pubblicato nel febbraio del 2017. La lettura non richiede particolari conoscenze tecniche; il testo è fruibile da chiunque utilizzi strumenti informatici o navighi in rete. Nel volume vengono considerati molteplici aspetti della cybersecurity, che vanno dalla definizione di infrastrutture e centri necessari a organizzare la difesa alle azioni e alle tecnologie da sviluppare per essere protetti al meglio, dall’individuazione delle principali tecnologie da difendere alla proposta di un insieme di azioni orizzontali per la formazione, la sensibilizzazione e la gestione dei rischi. Gli ambiti progettuali e le azioni, che noi speriamo possano svilupparsi nei prossimi anni in Italia, sono poi accompagnate da una serie di raccomandazioni agli organi preposti per affrontare al meglio, e da Paese consapevole, la sfida della trasformazione digitale. Le raccomandazioni non intendono essere esaustive, ma vanno a toccare dei punti che riteniamo essenziali per una corretta implementazione di una politica di sicurezza cibernetica a livello nazionale. Politica che, per sua natura, dovrà necessariamente essere dinamica e in continua evoluzione in base ai cambiamenti tecnologici, normativi, sociali e geopolitici. All’interno del volume, sono riportati dei riquadri con sfondo violetto o grigio; i primi sono usati nel capitolo introduttivo e nelle conclusioni per mettere in evidenza alcuni concetti ritenuti importanti, i secondi sono usati negli altri capitoli per spiegare il significato di alcuni termini tecnici comunemente utilizzati dagli addetti ai lavori. In conclusione, ringraziamo tutti i colleghi che hanno contribuito a questo volume: un gruppo di oltre 120 ricercatori, provenienti da circa 40 tra Enti di Ricerca e Università, unico per numerosità ed eccellenza, che rappresenta il meglio della ricerca in Italia nel settore della cybersecurity. Un grazie speciale va a Gabriella Caramagno e ad Angela Miola che hanno contribuito a tutte le fasi di produzione del libro. Tra i ringraziamenti ci fa piacere aggiungere il supporto ottenuto dai partecipanti al progetto FILIERASICURA

Monitoring soil organic carbon in croplands using imaging spectroscopy (MOCA project)

The detection of changes in soil organic carbon (SOC) concentration is essential in both the assessment of SOC sequestration and soil quality. Within the EU soil thematic strategy the depletion of organic matter is mentioned as one of the major threats to the soil resource. As one of the first countries Luxemburg has taken the initiative to monitor the SOC concentration of individual fields to allow for eventual CO2 credits and as an indicator for good agro-ecological conditions (GAEC). The aim of this project is to develop an efficient and operational methodology to detect SOC changes in croplands using Imaging Spectroscopy and to map the SOC contents of croplands with high resolution and minimal calibration

Monitoring soil organic carbon in cropland using VIS-NIR imaging spectroscopy

Conventional soil sampling techniques are often too expensive and time consuming to meet the amount of quantitative data required in soil monitoring or modelling studies. The emergence of portable and flexible spectrometer operating in the visible and near infrared range of the electro-magnetic spectrum could provide the large amount of spatial data needed. To this regard, the ability of airborne imaging spectroscopy to cover large surfaces in a single flight campaign and study the spatial distribution of soil properties with a high spatial resolution represents an opportunity for improving the monitoring of soils. The potential of quantitative spectral analysis has been repeatedly demonstrated in soil science either in the laboratory or with remote sensors. However, imaging spectroscopy for soil applications has been generally applied over small areas or homogeneous soil types and surface conditions. Here, five hyperspectral images acquired with the AHS-160 sensor were analysed to predict Soil Organic Carbon (SOC) in an area (350 km2) in Luxembourg characterized by different soil types and a large variation in SOC contents. Reflectance data were related to surface SOC contents of bare cropland by means of 3 different multivariate calibration techniques: Partial Least Square Regression (PLSR), Penalized-spline Signal Regression (PSR) and Least Square Support Vector Machine (LS-SVM). The stability of the methods across different agropedological zones, soil types or soil surface conditions were tested by comparing their performance under different combinations of calibration/validation sets (global and local calibrations). A lack of fit at high SOC content was observed under global calibrations, yielding a relatively high Root Mean Square Error in the Predictions (RMSEP) of 4.7-6.2 g C kg-1. PSR showed a greater ability to handle noisy spectral features, resulting in more robust calibrations than PLSR. Local calibrations based on soil types and agro-geological regions appeared to be more efficient than global calibrations, due to the correlation of these strata with important chromophores like soil moisture or ferrous oxide content. Specifically, these calibrations allowed increasing the prediction accuracy up to two fold. The main difference between the SVMR models and the PLSR/PSR related approaches is that the former perform better for the global data set. On the other hand, SVMR validation results are of minor quality for the soil and region related sub-models compared to the PLSR/PSR models. The analysis of field-scale SOC maps revealed strong spatial patterns of SOC related to topographic and management variables, which confirm the importance of both inter- and intra-field variability in the assessment of SOC contents at larger scale.Monitoring soil organic carbon in cropland using VIS-NIR Imaging Spectroscopy (MOCA

Pratiques de pâturage, perceptions et attentes des éleveurs laitiers Wallons

peer reviewedThe role of grasslands as a C sink is generally accepted. It is considered that permanent grasslands allow annual C storage rates between 22 and 44 g C/m2/y (Soussana et al., 2010) thereby contributing to the mitigation of greenhouse gas (GHG) emissions. Grassland preservation has several other advantages including a decrease in feeding costs (Dillon et al., 2005), a positive effect on cows’ health (e.g.a decrease in lameness) (Burow et al., 2011) and the provision of a positive image to consumers. Despite these arguments, grazing is decreasing in Europe and grasslands are disappearing. A better understanding of grazing practices and of farmers’ expectations could suggest ways of improving these practices and limiting grassland disappearance. As a result, Walloon dairy farmers were surveyed in December 2015 and the preliminary results are presented below.Life Dairycli

Monitoring soil organic carbon in croplands using imaging spectroscopy

Conventional soil sampling techniques are often too expensive and time consuming to meet the amount of quantitative data required in soil monitoring or modelling studies. The emergence of portable and flexible spectrometer operating in the visible and near infrared range of the electro-magnetic spectrum could provide the large amount of spatial data needed. To this regard, the ability of airborne imaging spectroscopy to cover large surfaces in a single flight campaign and study the spatial distribution of soil properties with a high spatial resolution represents an opportunity for improving the monitoring of soils. The potential of quantitative spectral analysis has been repeatedly demonstrated in soil science either in the laboratory or with remote sensors. However, imaging spectroscopy for soil applications has been generally applied over small areas or homogeneous soil types and surface conditions. Here, five hyperspectral images acquired with the AHS-160 sensor were analysed to predict Soil Organic Carbon (SOC) in an area (350 km2) in Luxembourg characterized by different soil types and a large variation in SOC contents. Reflectance data were related to surface SOC contents of bare cropland by means of 3 different multivariate calibration techniques: Partial Least Square Regression (PLSR), Penalized-spline Signal Regression (PSR) and Least Square Support Vector Machine (LS-SVM). The stability of the methods across different agropedological zones, soil types or soil surface conditions were tested by comparing their performance under different combinations of calibration/validation sets (global and local calibrations). A lack of fit at high SOC content was observed under global calibrations, yielding a relatively high Root Mean Square Error in the Predictions (RMSEP) of 4.7-6.2 g C kg-1. PSR showed a greater ability to handle noisy spectral features, resulting in more robust calibrations than PLSR. Local calibrations based on soil types and agro-geological regions appeared to be more efficient than global calibrations, due to the correlation of these strata with important chromophores like soil moisture or ferrous oxide content. Specifically, these calibrations allowed increasing the prediction accuracy up to two fold. The main difference between the SVMR models and the PLSR/PSR related approaches is that the former perform better for the global data set. On the other hand, SVMR validation results are of minor quality for the soil and region related sub-models compared to the PLSR/PSR models. The analysis of field-scale SOC maps revealed strong spatial patterns of SOC related to topographic and management variables, which confirm the importance of both inter- and intra-field variability in the assessment of SOC contents at larger scale.Monitoring soil organic carbon in croplands using imaging spectroscopy (MOCA project

Suivi du carbone organique des sols agricoles par télédétection hyperspectrale

Executive summary Conventional sampling technique are often too expensive and time consuming to meet the amount of quantitative data required in soil monitoring or modelling studies. The emergence of portable and flexible VNIR sensors could provide the large amount of spatial data needed. In particular, the ability of imaging spectroscopy to cover large surfaces in a single campaign and study the spatial distribution of soil properties with a high spatial resolution represents an opportunity for improving the monitoring of soils. However, some challenges still remain to be solved concerning disturbing factors and the accuracy of the SOC analysis. Disturbing factors, especially soil roughness and moisture content, must be taken into account to produce good calibration models. These factors induce a spectral variability not related to the studied property (here, SOC) and degrade the accuracy of the image-based predictions. The use of hyperspectral remote sensing as a fast analysis of SOC stocks could lead to a loss of precision, which should be evaluated because it may be incompatible with the accuracy needed by end-users in the evaluation of the impact of agricultural practice on SOC stocks. Until now, imaging spectroscopy has been generally applied over small areas or homogeneous soil types and surface conditions. During the MOCA project: · Five hyperspectral images acquired with the AHS-160 sensor were analysed to predict Soil Organic Carbon (SOC) in an area in Luxembourg characterized by different soil types and a large variation in SOC contents. · The effect of soil Relative Shadow (RS, the percentage of shadowed soil of the surface studied) on SOC prediction from spectral data under field conditions was quantified. First, the impact of RS on reflectance and SOCp is briefly described. Then, a methodology to measure RS and correct its impact on field reflectance measured with an ASD FieldSpec Pro spectrometer and the AHS-160 sensor is proposed. Finally, SOC content is predicted with uncorrected and corrected reflectance values to evaluate the enhancement in SOC prediction accuracy. · The results of the investigations both in the laboratory (wet chemical SOC analysis (CONVIS), LECO CN analyzer (calibration and validation dataset) and with remote sensing via airplane were compared Reflectance data were related to surface SOC contents of bare croplands by means of 3 different multivariate calibration techniques: Partial Least Square Regression (PLSR), Penalizedspline Signal Regression (PSR) and Least Square Support Vector Machine (LS-SVM). The performance of the methods was tested under different combinations of calibration/validation sets (global and local calibrations stratified according to agro-geological zones, soil types and image number). The results demonstrated that PSR and LS-SVM performed better than PLSR using global calibrations. The Root Mean Square Error in the Predictions reached 5.6-6.2 g C kg- 1. Under local calibrations, this error was reduced by a factor 1.3 to 1.9, depending on the stratification scheme adopted. Pixels of two agricultural fields were extracted from the data cube and predicted for SOC with the best models. Intra- and inter-field variability of SOC contents were observed related to topography and land management. In the future, the mapping of SOC over the entire study area will constitute a database used as input in digital soil mapping and SOC monitoring. Tests under laboratory conditions showed that the prediction of SOC decreases when the relative shadow increases. A methodology for correcting the effect of relative shadow on reflectance spectra measured with ASD or AHS during field campaign was elaborated and tested. Results show that the methodology enables to significantly enhance SOC prediction in all cases studied. Correction always improves the prediction of SOC (and increase of 25 % in RMSEP for raw reflectance) when using non pre-processed reflectance. The best prediction of SOC is always achieved with corrected pre-processed reflectance. From the point of view of an agricultural extension organization in the field of fertilization planning as well as of maintaining and improving soil fertility such as the CONVIS s.c., the results presented above have to be considered positive and the investigations of the MOCA project a successful experiment. The results and the related calibration models appear to be able to deliver in most cases values of SOC which are precise enough to be used in agricultural extension. In order to optimize the calibration models of the remote sensing investigation, traditional chemical analysis of other fields of the investigated air corridor should be made and the results compared with the SOC values derived from imaging spectroscopy value. This could deliver more information about the strong points and the limitations of the applied method.BELSPO SR/00/110Monitoring soil organic carbon in croplands using imaging spectroscopy (MOCA project

Life-Dairyclim, projet de recherche visant à réduire les émissions de méthane et l'empreinte carbone du lait des vaches laitières

peer reviewedHow can dairy farming contribute to reduce the climate change without compromising food security and farm economy? This is the question the project Life-Dairyclim wants to answer. The project gathers partners from research groups, association of advisory services to farmers and feed industry in collaboration with private farmers in three countries (Belgium, Luxembourg and Denmark). It focuses on production of feed, including utilisation of grassland and feeding of dairy cows in order to implement strategies that can contribute to a sustainable development of the dairy sector. Feeding experiments to decrease methane from dairy cows will be assessed at the University of Liège (Belgium) with cows milked by an automatic milking system. Methane production will be analysed individually by a device (Guardian®) inserted in the feeding bin as well as by mid infrared spectrum analysis of milk. The effect of concentrate composition on methane production during grazing in combination with optimization of grazing practices will be studied in collaboration with the industrial partner, Dumoulin (Belgium). The carbon footprint of produced milk will be determined using lifecycle assessment methods based on input from the experiments in combination with effect of feed production on especially carbon sequestration from different type of crop and utilization by Aarhus University (Denmark) and Convis, association of advisory services to farmers (Luxembourg). An important part of the project is dissemination based on pilot farms in all three countries documenting the impact of mitigation strategies adopted during the projectLife-2014 CCB_BE_001187 Dairycli