Reforms of the Common Agricultural Policy and agriculture in Finland

Selostus: Euroopan unionin yhteisen maatalouspolitiikan uudistaminen ja Suomen maatalous

Analysis, modelling and classification of geospatial data using machine learning

The research considers the problem of spatial data classification using machine learning algorithms: probabilistic neural networks (PNN) and support vector machines (SVM). As a benchmark model simple k-nearest neighbor algorithm is considered. PNN is a neural network reformulation of well known nonparametric principles of probability density modeling using kernel density estimator and Bayesian optimal or maximum a posteriori decision rules. PNN is well suited to problems where not only predictions but also quantification of accuracy and integration of prior information are necessary. An important property of PNN is that they can be easily used in decision support systems dealing with problems of automatic classification. Support vector machine is an implementation of the principles of statistical learning theory for the classification tasks. Recently they were successfully applied for different environmental topics: classification of soil types and hydro-geological units, optimization of monitoring networks, susceptibility mapping of natural hazards. In the present paper both simulated and real data case studies (low and high dimensional) are considered. The main attention is paid to the detection and learning of spatial patterns by the algorithms applied.

Agricultural phosphorus and water quality : sources, transport and management

Selostus: Maatalous, fosfori ja veden laatu: alkuperä, kulkeutuminen ja vesistökuormituksen hallinta

Physical properties of dystrophic Red Latosol (Oxisol) under different agricultural uses

Obtaining information about soil properties under different agricultural uses to plan soil management is very important with a view to sustainability in the different agricultural systems. The aim of this study was to evaluate changes in certain indicators of the physical quality of a dystrophic Red Latosol (Oxisol) under different agricultural uses. The study was conducted in an agricultural area located in northern Paraná State. Dystrophic Red Latosol samples were taken from four sites featuring different types of land use typical of the region: pasture of Brachiaria decumbens (P); sugarcane (CN); annual crops under no-tillage (CAPD); and native forest (permanent conservation area) (control (C)). For each land use, 20 completely randomized, disturbed and undisturbed soil samples were collected from the 0-20 cm soil layer, to determine soil texture, volume of water-dispersible clay, soil flocculation (FD), particle density, quantity of organic matter (OM), soil bulk density (Ds), soil macroporosity (Ma) and microporosity (Mi), total soil porosity (TSP), mean geometric diameter of soil aggregates (MGD), and penetration resistance (PR). The results showed differences in OM, FD, MGD, Ds, PR, and Ma between the control (soil under forest) and the areas used for agriculture (P, CN and CAPD). The soils of the lowest physical quality were those used for CN and CAPD, although only the former presented a Ma level very close to that representing unfavorable conditions for plant growth. For the purposes of this study, the physical properties studied were found to perform well as indicators of soil quality.

Sewage sludge application to agricultural land as soil physical conditioner

Water resource quality is a concern of today's society and, as a consequence, low pollutant wastewaters and sludges are being increasingly treated, resulting in continuous production of sewage sludge. Sewage sludge (SS) can be used as soil physical conditioner of agricultural or degraded lands, due to its organic C component. The objective of this research was to evaluate the long-term SS effects on soil physical quality of properties such as bulk density, porosity, permeability and water retention of degraded soils treated with annual SS applications. The SS rates were calculated according to the crop N demand. The field experiment consisted of three treatments: mineral fertilization, 10 and 20 Mg ha-1 of SS (once and twice the SS quantity to meet the maize N demand, respectively), in annual applications to the surface layer of a eutroferric Red Latosol. SS reduced bulk density, increased macroporosity and decreased microporosity after the third application, but did not significantly alter the soil permeability and physical quality as measured by the S index in the surface layer.

Example-based support vector machine for drug concentration analysis

Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. In this paper, we focus on the prediction of drug concentrations using Support Vector Machines (S VM) and the analysis of the influence of each feature to the prediction results. Our study shows that SVM-based approaches achieve similar prediction results compared with pharmacokinetic model. The two proposed example-based SVM methods demonstrate that the individual features help to increase the accuracy in the predictions of drug concentration with a reduced library of training data.

Portable penetrometer for agricultural soil: sensitivity test to identify critical compaction depth

To express the negative effects of soil compaction, some researchers use critical values for soil mechanical strength that severely impair plant growth. The aim of this study was to identify this critical compaction depth, to test the functionality of a new, portable penetrometer developed from a spring dynamometer, and compare it to an electronic penetrometer traditionally used in compaction studies of agricultural soils. Three soils with distinct texture were conventionally tilled using a disk plow, and cultivated with different plant species. The critical soil resistance defined to establish critical compaction depth was equal to 1.5 MPa. The results of the new equipment were similar to the electronic penetrometer, indicating its viability as a tool for assessing the soil physical conditions for plant growth.

Physical properties of afforested former agricultural peat soils in western Finland

Tiivistelmä: Metsitettyjen turvepeltojen maan fysikaaliset ominaisuudet

Improvement of a testing apparatus for dynamometry: procedures for penetrometry and influence of strain rate to quantify the tensile strength of soil aggregates

Soil penetration resistance (PR) and the tensile strength of aggregates (TS) are commonly used to characterize the physical and structural conditions of agricultural soils. This study aimed to assess the functionality of a dynamometry apparatus by linear speed and position control automation of its mobile base to measure PR and TS. The proposed equipment was used for PR measurement in undisturbed samples of a clayey "Nitossolo Vermelho eutroférrico" (Kandiudalfic Eutrudox) under rubber trees sampled in two positions (within and between rows). These samples were also used to measure the volumetric soil water content and bulk density, and determine the soil resistance to penetration curve (SRPC). The TS was measured in a sandy loam "Latossolo Vermelho distrófico" (LVd) - Typic Haplustox - and in a very clayey "Nitossolo Vermelho distroférrico" (NVdf) - Typic Paleudalf - under different uses: LVd under "annual crops" and "native forest", NVdf under "annual crops" and "eucalyptus plantation" (> 30 years old). To measure TS, different strain rates were applied using two dynamometry testing devices: a reference machine (0.03 mm s-1), which has been widely used in other studies, and the proposed equipment (1.55 mm s-1). The determination coefficient values of the SRPC were high (R² > 0.9), regardless of the sampling position. Mean TS values in LVd and NVdf obtained with the proposed equipment did not differ (p > 0.05) from those of the reference testing apparatus, regardless of land use and soil type. Results indicate that PR and TS can be measured faster and accurately by the proposed procedure.

Audit report on the Iowa Agricultural Development Authority for the year ended June 30, 2011

Audit report on the Iowa Agricultural Development Authority for the year ended June 30, 2011