P4-0072 — Annual report 2009
1.
Organisation of the Pine Wood Nematode Workshop

We organized a seminar on Bursaphelenchus xylophilus, which was attended by more than 50 participants from phytosanitary and forestry sector. 3 papers were presented.

F.18 Transfer of new know-how to direct users (seminars, fora, conferences)

COBISS.SI-ID: 3119976
2.
Cloning and expression of two Phaseolus vulgaris L. drought-responsive serine protease genes.

We developed a procedure, involving zymography with fluorescent substrates, which has revealed the heterogeneity of serine proteases and enabled us to detect and quantitate relative proteolytic activities in bean leaves. Levels of several serine proteases changed in different ways under water deficit. We isolated a serine protease (BSP) and a phenylalanyl aminopeptidase (FAP) involved in the response of P. vulgaris to drought and cloned bsp and fap genes. We studied the gene expression of BSP and FAP in leaf tissues of plants submitted to water deficit.

F.02 Acquisition of new scientific knowledge

COBISS.SI-ID: 3110760
3.
19th EUCARPIA Conference, Genetic Resources Section

We have organized 19th EUCARPIA Conference, Genetic Resources Section with participation of 150 researchers and proffessionals from Europe, Americas and Asia.

B.01 Organiser of a scientific meeting

COBISS.SI-ID: 245700608
4.
Biodiversity: agricultural crops. Environmental indexes in Slovenia

Monitoring of most important indexes that are describing biodiversity of agricultural crops in Slovenia and their inclusion in the European database.

F.18 Transfer of new know-how to direct users (seminars, fora, conferences)

COBISS.SI-ID: 2595432
5.
An attempt to predict pork drip loss from pH and colour measurements or near infrared spectra using artificial neural networks

The aim of the study was to verify if prediction of meat drip loss could be improved using NIR spectra and different chemometric approach (artificial neural networks). Study demonstrated similar prediction error for models based on spectral information or meat quality measurements. No major improvement was obtained using different chemometric approach (artificial neural network). Nevertheless the simplicity of data acquisition in case of NIRS, and less bias in case of artificial neural networks proves certain advantages.

F.02 Acquisition of new scientific knowledge

COBISS.SI-ID: 3025512