Von J. v. Liebig bis E. A. Mitscherlich. Die Grundlage ressourceneffizienter Pflanzenernährung - Langfassung

We share the visions of the originator of the modern soil science VV Dokuchaev and the great innovators of agrochemistry J v. Liebig, EA Mitscherlich, DN Pryanishnikov, UU Uspanov and others. Their visions were to eliminate hunger and poverty of the population by stable crop yields based on innovative site-adapted soil management and farming

Soil Quality and Crop Yield Potential of Sites in North and Central Asian

Science and technology may help to find solutions for sustainable use of soils. The awareness about limited and degrading natural resources have fired the energy and creativity of responsible and innovative people to develop and install monitoring systems and countermeasures. However, the access to modern monitoring systems and agri-environmental technologies is different over regions of Eurasia. Some regions of Central Asia and Asian Russia require modern monitoring systems for their land and water resources in order to avoid their accelerating degradation and maintain their productivity function and ecosystem services for the populatio

Monitoring of Soil Fertility (Agroecological Monitoring) Langfassung

Monitoring the ecological status of agricultural land in trials with different inputs of fertilizers is focused on analyzing soil fertility indicators and their impact on productivity. Some of these experiments are long-term and part of international networks. Their results are of fundamental importance for monitoring, modeling, and controlling the status of soils. In a regular survey, we found tendencies toward decreasing soil fertility in some regions

Bodenbewertung und Ernteerträge: Analyse internationaler Datensätze

Das Muencheberger Soil Quality Rating (M-SQR) ist ein Verfahren zur skalenübergreifenden Bewertung der Produktivitätsfunktion von Böden. Die Kennziffern dieses für den globalen Maßstab konzipierten Bodenschätzungsverfahrens sollen eine Begutachtung von Ertragspotentialen anhand von standörtlichen Indikatoren ermöglichen. Im Hinblick auf die Objektivierung der Schätztabellen prüften wir die Beziehungen zwischen Standortfaktoren, Boden-Bonitierungsverfahren und Ertrag landwirtschaftlicher Kulturen auf einer Vielzahl von Agrarstandorten. Grundlage waren Felduntersuchungen an Bodenprofilen, mittlere monatliche Klimadaten und mittlere Ernteerträge benachbarter Parzellen. Die Daten wurden mit multivariaten statistischen Verfahren analysiert. Im Ergebnis konnten wir die standörtliche Trockenheit und das Thermalregime der Böden als maßgebliche ertragsbeeinflussende Faktoren identifizieren und quantifizieren. Auf dieser Grundlage wurden sowohl die Bewertungstabellen des M-SQR-Verfahrens präzisiert als auch Regressionsgleichungen für die Abschätzung von Erträgen aus den Bodenpunkten des M-SQR abgeleitet. Wir schlussfolgern, dass das M-SQR Verfahren als Welt-Bodenschätzung hinreichend präzise und praktikabel ist. Das beinhaltet sowohl die Feldmethodik als auch die Kartierung von Ertragspotentialen

Bodenhydrologische Untersuchungen in verschiedenen Skalen für eine nachhaltige Landwirtschaft (Langfassung)

Eine umfassende Analyse von interaktiven Prozessen zwischen Boden, Wasser, Pflanze, Tiere und Atmosphäre für eine nachhaltige Landwirtschaft erfordert Kenntnisse von hydrologischen Parametern und Prozessen in unterschiedlichen Skalen. Methoden und Ergebnisse aus bodenhydrologischen Studien in Nordostdeutschland werden vorgestellt. Die Untersuchungen erfolgten im Labor, Lysimeter, Feld und Einzugsgebiet

Modelling and Prediction of Organic Carbon Dynamics in Arable Soils Based on a 62-Year Field Experiment in the Voronezh Region, European Russia

Organic carbon (OC) accumulation in soil mitigates greenhouse gases emission and improves soil health. We aimed to quantify the dynamics of OC stock in soils and to justify technologies that allow annual increasing OC stock in the arable soil layer by 4‰. We based the study on a field experiment established in 1936 in the 9-field crop rotation with a fallow on Chernozem in European Russia. The RothC version 26.3 was used for the reproducing and forecasting OC dynamics. In all fertilizer applications at FYM background, there was a decrease in the OC stock with preferable loss of active OC, except the period 1964–1971 with 2–5‰ annual OC increase. The model estimated the annual C input necessary to maintain OC stock as 1900 kg·ha−1. For increasing OC stocks by 4‰ per year, one should raise input to 2400 kg·ha−1. The simulation was made for 2016–2090 using climate scenarios RCP4.5 and RCP8.5. Crop rotation without fallowing provided an initial increase of 3‰ and 6‰ of stocks in the RCP8.5 and RCP4.5 scenarios accordingly, followed by a loss in accumulated OC. Simulation demonstrates difficulties to increase OC concentration in Chernozems under intensive farming and potential capacity to rise OC stock through yield management

Estimating black carbon emissions from agricultural burning

High sensitivity of the Arctic region to short-lived climate forcers, including black carbon (BC), makes crop residue burning an important source of emissions. A high to moderate uncertainty in cropland burning emission estimates from remote sensing-based analyses currently exists and is problematic for establishing baseline estimates of black carbon emissions from global remote sensing products. Straw burning and possible BC emissions were estimated at the oblast level for Russia for years 2003 through 2010. A study was based on 1 km Moderate Resolution Spectroradiometer (MODIS) Active Fire Product, oblast level agricultural statistics, 1:25,000–1:50,000 scale GIS vector field maps and developing algorithms for calculating the size and intensity of fires as well as testing the accuracy of the predictions in areas with contrast land use. Both Active Fire Product and statistics methods demonstrated consistent results, including increasing fire activity in the years with additional straw surplus and the highest absolute values for vast territories with quite intensive grain production, mainly in European Russia. Straw burning can be a source of at least 1/3 total BC emissions from agriculture and grassland fires and does not appear to be the main source of total BC emissions for the Russian Federation. For regions with small number of cropland fires, the accuracy of existing remote sensing-based land cover products is insufficient for reliable classification of agricultural fires from satellite products. Incorrect classification of agricultural fires may exceed 25 %, increasing for the northern part of the country where forests are the predominant land cover. An improved method would be to calculate BC emissions from burned area using high resolution field masks and ground validation of fire sources in cropland areas