Analysis of variance in soil research: let the analysis fit the design

Sound design for experiments on soil is based on two fundamental principles: replication and randomization. Replication enables investigators to detect and measure contrasts between treatments against the backdrop of natural variation. Random allocation of experimental treatments to units enables effects to be estimated without bias and hypotheses to be tested. For inferential tests of effects to be valid an analysis of variance (anova) of the experimental data must match exactly the experimental design. Completely randomized designs are usually inefficient. Blocking will usually increase precision, and its role must be recognized as a unique entry in an anova table. Factorial designs enable questions on two or more factors and their interactions to be answered simultaneously, and split-plot designs may enable investigators to combine factors that require disparate amounts of land for each treatment. Each such design has its unique correct anova; no other anova will do. One outcome of an anova is a test of significance. If it turns out to be positive then the investigator may examine the contrasts between treatments to discover which themselves are significant. Those contrasts should have been ones in which the investigator was interested at the outset and which the experiment was designed to test. Post-hoc testing of all possible contrasts is deprecated as unsound, although the procedures may guide an investigator to further experimentation. Examples of the designs with simulated data and programs in GenStat and R for the analyses of variance are provided as File S1

Preparation of single cell detritus from Laminaria sacchat¡rina as a hatchery diet for bivlabe mollucs.

A high-yield technique is described for the elaboration of single cell detritus (SCD) from Laminaria saccharina, based on the sequential action of C1H, enzymes (endoglucanases and cellulases) and 2 bacteria showing a high degree of cellobiotic, proteolytic, and alginolytic activity (CECT 5255 and CECT 5256). Over 85% of dried particles of L. saccharina were transformed into a suspension of free cell and bacterial and detrital particles after 24 hours of bacterial activity with this technique. These particles were less than 20 μm in diameter, constituting a suitable diet for bivalve mollusks. After 72 hours 99% of the total particulate volume consisted of particles less than 20 μm in diameter. Tests of hatchery diets for the seed of clam Ruditapes decussatus revealed increases of 54% and 68% for live weight and length, respectively, when SCD from L. saccharina was used as the sole dietary component compared with a live phytoplankton diet. However, SCD from L. saccharina is not a suitable food for the larvae of R. decussatus.Postprint

A proposed methodology for the correction of the Leaf Area Index measured with a ceptometer for pinus and eucalyptus forests = Proposta de uma methodologia para a correcao do indice de area foliar medido pelo ceptometro em provoamentos de pinus e eucalyptus

Leaf area index (LAI) is an important parameter controlling many biological and physiological processes associated with vegetation on the Earth's surface, such as photosynthesis, respiration, transpiration, carbon and nutrient cycle and rainfall interception. LAI can be measured indirectly by sunfleck ceptometers in an easy and non-destructive way but this practical methodology tends to underestimated when measured by these instruments. Trying to correct this underestimation, some previous studies heave proposed the multiplication of the observed LAI value by a constant correction factor. The assumption of this work is LAI obtained from the allometric equations are not so problematic and can be used as a reference LAI to develop a new methodology to correct the ceptometer one. This new methodology indicates that the bias (the difference between the ceptometer and the reference LAI) is estimated as a function of the basal area per unit ground area and that bias is summed to the measured value. This study has proved that while the measured Pinus LAI needs a correction, there is no need for that correction for the Eucalyptus LAI. However, even for this last specie the proposed methodology gives closer estimations to the real LAI values

A Hierarchical Approach to Multimodal Classification

Abstract. Data models that are induced in classifier construction often consists of multiple parts, each of which explains part of the data. Classi-fication methods for such models are called the multimodal classification methods. The model parts may overlap or have insufficient coverage. How to deal best with the problems of overlapping and insufficient cov-erage? In this paper we propose hierarchical or layered approach to this problem. Rather than seeking a single model, we consider a series of models under gradually relaxing conditions, which form a hierarchical structure. To demonstrate the effectiveness of this approach we imple-mented it in two classifiers that construct multi-part models: one based on the so-called lattice machine and the other one based on rough set rule induction. This leads to hierarchical versions of the classifiers. The classification performance of these two hierarchical classifiers is compared with C4.5, Support Vector Machine (SVM), rule based classifiers (with the optimisation of rule shortening) implemented in Rough Set Explo-ration System (RSES), and a method combining k-nn with rough set rule induction (RIONA in RSES). The results of the experiments show that this hierarchical approach leads to improved multimodal classifiers