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Cover crops are grown between two main crops to reduce periods of bare fallow. In highly diverse crop rotations, the lengths of break periods between two main crops vary highly over time and consequently the cover cropping management differs from year to year. Long-term field trials are thus of limited use because the same cover cropping approach only appears once in several years. This increases the need to better determine the immediate effects of different cover cropping strategies on soil properties. This study evaluated two cover cropping strategies and monitored the temporal development of several soil properties on six fields in Eastern Switzerland in the 9 months period between harvest of winter wheat and sowing of spring crops. The two tested strategies were (a) double cover cropping (DCC) where two cover crops mixtures were grown subsequently and shallowly (3 cm) incorporated into the topsoil and (b) permanent soil cover (PSC) with one grass-clover mixture, which was harvested and thus not incorporated into the soil. Soil samples at three different soil depths (0–5, 5–10 and 10–20 cm) were sampled four times in high spatial resolution and analysed using a combined approach of visible near infrared spectroscopy and conventional lab methods. Differences between the sampling times and field sites were stronger than effects of different treatments. For soil organic carbon (SOC), no significant difference was measured between treatments in 0–20 cm soil depth. Only when analysed per depth segment, the PSC treatment showed significantly higher SOC increase in 5–10 cm soil depth than the DCC treatment. This could be due to the longer soil cover and thereby associated longer root growth period in the PSC treatment, leading to higher below ground C inputs than in the DCC treatment. On the other hand, the DCC treatment showed generally higher increases in permanganate oxidizable carbon stocks (0–5 cm), microbial C (0–10 cm), microbial N (0–10 cm) and mineral N (0–10

Vor nicht allzu langer Zeit galt Pflanzenkohle lediglich als Nebenprodukt der Holzverarbeitung. Doch heute ist sie ein Schlüsselelement in der Diskussion um nachhaltige Landwirtschaft und Klimaschutz. In den letzten Jahren hat die Popularität von Pflanzenkohle zur Bodenverbesserung und als CO2-Speicher stark zugenommen. In unserer aktuellen Podcast-Episode beleuchten wir ihre vielfältigen Anwendungsmöglichkeiten und die bisher gewonnenen wissenschaftlichen Erkenntnisse.

Conventional laboratory analysis of soil properties is often expensive and requires much time if various soil properties are to be measured. Visual and near-infrared (vis–NIR) spectroscopy offers a complementary and cost-efficient way to gain a wide variety of soil information at high spatial and temporal resolutions. Yet, applying vis–NIR spectroscopy requires confidence in the prediction accuracy of the infrared models. In this study, we used soil data from six agricultural fields in eastern Switzerland and calibrated (i) field-specific (local) models and (ii) general models (combining all fields) for soil organic carbon (SOC), permanganate oxidizable carbon (POXC), total nitrogen (N), total carbon (C) and pH using partial least-squares regression. The 30 local models showed a ratio of performance to deviation (RPD) between 1.14 and 5.27, and the root mean square errors (RMSE) were between 1.07 and 2.43 g kg−1 for SOC, between 0.03 and 0.07 g kg−1 for POXC, between 0.09 and 0.14 g kg−1 for total N, between 1.29 and 2.63 g kg−1 for total C, and between 0.04 and 0.19 for pH. Two fields with high carbonate content and poor correlation between the target properties were responsible for six local models with a low performance (RPD < 2). Analysis of variable importance in projection, as well as of correlations between spectral variables and target soil properties, confirmed that high carbonate content masked absorption features for SOC. Field sites with low carbonate content can be combined with general models with only a limited loss in prediction accuracy compared to the field-specific models. On the other hand, for fields with high carbonate contents, the prediction accuracy substantially decreased in general models. Whether the combination of soils with high carbonate contents in one prediction model leads to satisfying prediction accuracies needs further investigation.

Soil carbon sequestration is an indicator for the climate change mitigation performance of agricultural land management. Already in the SECO-funded programme ‘Higher Value-Added Trade from the Organic and the Dairy Sector in Ukraine (Quality FOOD Trade Program)’, which started in 2020, soil carbon sequestration has been chosen as an impact indicator. The same applies for the SECO-funded project Organic Trade for Development (OT4D), which started in September 2019. Based on the statistics of certified organic farmland and a rough formula, FiBL calculated the net soil carbon sequestration effect under certified organic management for the period from 2011 to 2021. Given the focus on crop production on these areas and the large areas concerned, FiBL suggests to use an average soil carbon sequestration value from the literature to get a gross picture on the sequestration potential without incurring huge measurement costs. This value is taken from a meta-analysis from 2012 mainly covering temperate zones, thus largely being adequate for the climatic situation in Eastern Europe.

The application of visual and near infrared soil spectroscopy (vis–NIR) is an easy and cost-efficient way to gain a wide variety of soil information to cover high spatial and temporal resolution in large-scale soil surveys and in local field-scale studies. However, unlike for conventional methods, the prediction accuracy of vis–NIR spectral models cannot yet be estimated before the data collection, which hampers its application at the local scale where often a high precision is required (e.g., field experiments). In this study we used soil data from six agricultural fields in Eastern Switzerland and calibrated i) field-specific (local) models and ii) general models (combining all fields) for organic carbon, total carbon, total nitrogen, permanganate oxidizable carbon and pH using partial least squares regression. 24 out of 30 local models showed an accurate or even excellent performance (ratio of performance to deviation (RPD) > 2) and the root mean square errors (RMSE) of prediction were, except for pH, maximum five times higher than the lab measurement error. The variability of a specific soil property and the mean carbonate concentration in the dataset were the two factors influencing the performance of the local models. We found a significant relationship between the coefficient of variation in the dataset and the metrics for model performance (R2, percental RMSE and RPD). Starting from a tolerable prediction error for the spectral measurements, the regressions can be used to develop a sampling design that matches the corresponding target variability. The five inaccurately performing local models with RPD < 2 were on the two fields with highest carbonate content raising the question if local vis–NIR models are suitable for soils with high carbonate concentration. General models combining the datasets from all six fields showed an accurate overall performance but the RMSE on the field level were higher compared to the local models.

Der Klimawandel ist eine der zentralen Herausforderungen unserer Zeit und alle Bereiche der Wirtschaft und Gesellschaft müssen zu dessen Minderung beitragen. Dies betrifft auch die Landwirtschaft und der Biolandbau mit seinem Fokus auf nachhaltigem Wirtschaften kann hier eine Pionierrolle einnehmen. Der vorliegende Artikel präsentiert die Ergebnisse einer Studie aus dem Jahr 2022, die beispielhaft darlegt, wie der Biolandbau in der Schweiz bis 2040 klimaneutral werden könnte. Dies zu erreichen ist möglich, aber sehr herausfordernd. Tatsächliche Emissionsreduktionen sind dabei sekundär, weil der Großteil der Klimaneutralität über Kompensationen (Bodenkohlenstoffbindung, Agroforst, Agri-Photovoltaik) und grundlegende Konsum- und Produktionssystemveränderungen (weniger tierische Produkte, also auch weniger Tiere) erreicht werden müsste.

Methoden der nachhaltigen Landwirtschaft und klimagerechten Lebensmittelproduktion können die Bildung von Humus und damit die Speicherung von Kohlenstoff im Boden fördern. Steigende Temperaturen, kleinere Tierbestände und ein reduzierter Einsatz von Mineraldünger bergen aber das Risiko, die Biomasseproduktion und den Humus eher zu reduzieren.

Agriculture feeds a growing world population, but is also one of the main causes of the global environmental crisis. The sustainable use of soil as a resource is the key challenge for the agricultural sector. Using the example of the 45-year-old DOK trial near Basel, the opportunities for organic farming to provide important ecosystem services in the long term will be demonstrated. The lecture will focus on the effects of conventional and organic land use systems on soil quality indicators such as soil carbon, soil biology and greenhouse gas emissions. In addition, the limitations of organic land use systems will be discussed and further food for thought on sustainable land use will be provided.

Der Klimawandel stellt Böden und die landwirtschaftliche Produktion vor Herausforderungen. Der Einsatz von Pflanzenkohle (PK) in landwirtschaftlich genutzten Böden soll sich positiv auf die organische Substanz des Bodens, mikrobielle Prozesse, das Wasserhaltevermögen sowie Nähr- und Schadstoffe auswirken. Aufgrund seiner hohen Stabilität kann PK auch zur Sequestrierung von Kohlenstoff (C) verwendet werden und Kohlenstoffzertifikate generieren. Für eine grossflächige Anwendung von PK müssen die langfristigen Auswirkungen unter Praxisbedingungen untersucht werden. Zu diesem Zweck untersuchen das FiBL und die Universität Bern in dem von Grün Stadt Zürich angelegten Langzeitversuch "Black goes green" die Auswirkungen von PK im Boden auf chemische, physikalische und biologische Parameter sowie die Erträge.

In Österreich sind die Klimaziele hochgesteckt. Bis 2040 soll Klimaneutralität auf nationaler Ebene erreicht werden. So müssen auch in der Landwirtschaft Veränderungen stattfinden. Der Bio-Landbau hat hier einige Vorteile zu bieten. Zur Erreichung der Klimaziele sind in der Landwirtschaft unterschiedliche Maßnahmen notwendig. Es ist zwischen Maßnahmen, die Emissionen auf dem eigenen Betrieb vermeiden oder reduzieren, und solchen, die Emissionen kompensieren, zu unterscheiden. Eine Gülleabdeckung reduziert zum Beispiel die Emissionen aus der Hofdüngerlagerung. Der Ausgleich von Emissionen kann unter anderem durch die vermehrte Speicherung von Kohlenstoff gefördert werden. So speichern humusaufbauende Maßnahmen und lebende Biomasse wie Bäume und Hecken Kohlenstoff.

This factsheet takes a closer look at the multifaceted role of agriculture in climate change. Various scientific findings are presented that show the potential of organic farming to mitigate climate change.

Soil organic carbon (SOC) originates from a complex mixture of organic materials, and to better understand its role in soil functions, one must characterise its chemical composition. However, current methods, such as solid-state 13C nuclear magnetic resonance (NMR) spectroscopy, are time-consuming and expensive. Diffuse reflectance spectroscopy in the visible and infrared regions (vis–NIR: 350–2500 nm; mid-IR: 4000–400 cm-1) can also be used to characterise SOC chemistry; however, it is difficult to know the frequencies where the information occurs. Thus, we correlated the C functional groups from the 13C NMR to the frequencies in the vis–NIR and mid-IR spectra using two methods: 1) 2-dimensional correlations of 13C NMR spectra and the diffuse reflectance spectra, and 2) modelling the NMR functional C groups with the reflectance spectra using support vector machines (validated using 5 times repeated 10-fold cross-validation). For the study, we used 99 mineral soils from the agricultural regions of Sweden. The results show clear correlations between organic functional C groups measured with NMR and specific frequencies in the vis–NIR and mid-IR spectra. While the 2D correlations showed general relationships (mainly related to the total SOC content), analysing the importance of the wavelengths in the SVM models revealed more detail. Generally, models using mid-IR spectra produced slightly better estimates than the vis–NIR. The best estimates were for the alkyl C group (R2 = 0.83 and 0.85, vis–NIR and mid-IR, respectively), and the O/N-alkyl C group was the most difficult to estimate (R2 = 0.34 and 0.38, vis–NIR and mid-IR, respectively). Combining 13CNMR with the cost effective diffuse reflectance methods could potentially increase the number of measured samples and improve the spatial and temporal characterisation of SOC. However, more studies with a wider range of soil types and land management systems are needed to further evaluate the conditions under which these

This fact sheet takes a closer look at the multifaceted role of agriculture in climate change. Various scientific findings are presented that show the potential of organic farming to mitigate climate change.

Der Mensch bewirtschaftet den Boden zur Nahrungsproduktion seit rund 12 000 Jahren – seit der industriellen Revolution und der raschen Zunahme der Weltbevölkerung zudem immer intensiver. Dass der Boden, insbesondere seine organische Substanz, dadurch Schaden nimmt, ist bekannt. Bieten die Methoden des Ökolandbaus eine Lösung des Problems?