Experience of Ring Rot Caused by Corynebacterium sepedonicum(Spieck. et Kotth.) Skapt. et Burkh. in Sweden. Particularly Detection of the Disease in its Latent Form)1

As it is difficult to detect ring rot in its latent form as well as in badly decayed tubers and in potato haulm, a diagnostic technique has been developed. With the help of a Turmix blender and a little water, a suspension is made of the suspected material. The suspension is inoculated into eggplants. Gram-staining of bacteria in sap from petioles of leaves showing symptoms is used to confirm the diagnosis. Some results obtained with this method applied on potatoes and potato haulm are described.     

Experience of Brown Rot Caused by Pseudomonas solanacearum (Smith) Smith in Sweden1

Brown rot (Pseudomonas solanacearum [Smith] Smith) infection of 5% or less was found in potatoes from some fields in Southern Sweden at about 56° N in the years 1972 and 1973²⁾. The fields were irrigated with water from small streams. The pathogen has been isolated from a wild host, Solanum dulcamara, growing at the water's edge in one of the streams. The wild host is perennial and bacteria can overwinter in this host. Overwintering also occurred in artificially infected S. dulcamara at 59° N. No overwintering in soil has hitherto been demonstrated, in spite of experiments with artificially infested soil. Infections have probably originated from imported potatoes.     

Variation among stallions in sperm quality after single layer centrifugation

Although single layer centrifugation (SLC) selects robust spermatozoa from stallion semen, the effect of individual variation has not been studied in detail. The objective of this study was to determine the variation among stallions in the effects of SLC on sperm quality during cooled storage for up to 48 hr. Semen samples from seven stallions (18 ejaculates) were split, with one portion being used for SLC and the other serving as a control (CON). Sperm quality (kinematics, reactive oxygen species (ROS) production, membrane integrity (MI) and chromatin integrity) were analysed at 0, 24 and 48 hr using computer-assisted sperm analysis and flow cytometry. Sperm quality was better in SLC than in CON at all timepoints, especially chromatin integrity and MI (p < .0001 for both), and some categories of ROS production (e.g. proportion of live hydrogen peroxide negative spermatozoa, p < .0001), but the degree of improvement varied among stallions and type of ROS (p < .05–p < .0001). Total and progressive motility were also better in SLC samples than in CON at 24 and 48 hr (p < .0001), although the effect on sperm kinematics varied. The interaction of treatment, time and stallion was not significant. In conclusion, sperm quality was better in SLC samples than in CON, although there was considerable individual variation among stallions. The improvement in sperm quality, particularly in chromatin integrity, was clearly beneficial, and therefore the use of this technique would be warranted for all stallion semen samples.     

Customer adapted grading of Scots pine sawn timber using a multivariate method

To define new grading rules, or to customize the ones in use in a rule-based automatic grading (RBAG) system of boards, is a time-consuming job for a sawmill engineer. This has the effect that changes are rarely made. The objective of this study was to continue the development of a method that replaces the calibration of grading rule settings by a holistic-subjective automatic grading, using multivariate models. The objective was also to investigate if this approach can improve sawmill profitability and at the same time have a satisfied customer. For the study, 323 Scots pine (Pinus sylvestris L.) boards were manually graded according to the preferences of an important customer. That is, a customer that regularly purchases significant volumes of sawn timber. This manual grading was seen as reference grading in this work. The same boards were also scanned and graded by a RBAG system, calibrated for the same customer. Multivariate models for prediction of board grade based on aggregated knot variables, obtained from the scanning, were calibrated using partial least squares regression. The results show that prediction of board grades by the multivariate models were more correct, with respect to the manual grading, than the grading by the RBAG system. The prediction of board grades based on multivariate models resulted in 76–87% of the boards graded correctly, according to the manual grading, while the corresponding number was 63% for the RBAG system.