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Articles containing the keyword 'initiation'

Category : Article

article id 5311, category Article
Timo Pukkala. (1987). Kuusen ja männyn siemensadon ennustemalli. Silva Fennica vol. 21 no. 2 article id 5311. https://doi.org/10.14214/sf.a15468
English title: Model for predicting the seed crop of Picea abies and Pinus sylvestris.
Original keywords: kuusi; mänty; luontainen uudistaminen; Lappi; siemensato; lämpötila; kukinnan aloitus; ennustemalli
English keywords: Pinus sylvestris; Norway spruce; Picea abies; natural regeneration; Scots pine; Finland; Lapland; predictive modelling; seed crop; flowering initiation; influence of temperature
Abstract | View details | Full text in PDF | Author Info

The seed crop of Norway spruce (Picea abies (L.) H. Karst.) and Scots pine (Pinus sylvestris L.) is predicted with the help of mean monthly temperatures during May–August one and two years before the flowering year. The prediction models were made separately for Lapland and for the rest of Finland. The models are based on 10-year periods of seed crop measurements and climatic data. The total number of time series was 59.

In Lapland, Norway spruce flowered abundantly and produced an abundant seed crop after warm July–August and two years after cool July–August. In other parts of Finland, warm June and July produced a good flowering year, especially if these months were cool two years before the flowering year.

In Lapland, Scots pine flowered abundantly if the whole previous growing season was warm. Elsewhere in Finland, a cool June preceded prolific flowering in the coming year if the rest of the growing season was considerably warmer than the average.

The prediction models explained 37–49 % of the variation in the size of the seed crop. The occurrence of good and poor seed years was usually predicted correctly. Using the presented models, the prediction of the seed crop is obtainable 1.5 year for Norway spruce and 2.5 year for Scots pine before the year of seed fall.

The PDF includes an abstract in English.

  • Pukkala, E-mail: tp@mm.unknown (email)

Category : Research article

article id 7772, category Research article
Curt Almqvist. (2018). Improving floral initiation in potted Picea abies by supplemental light treatment. Silva Fennica vol. 52 no. 2 article id 7772. https://doi.org/10.14214/sf.7772
Keywords: Norway spruce; seed production; flower stimulation; strobili initiation; indoor seed orchard
Highlights: Supplemental light treatment:
  • Increases the proportion of genotypes initiating reproductive buds.
  • Increases floral induction, especially of female floral buds.
  • Facilitates breeding programmes, and seed production of highly improved base material from new selections for vegetative production programmes, to be more efficient.
Abstract | Full text in HTML | Full text in PDF | Author Info

Light is an important environmental factor for all green plants. Its intensity, spectral composition and photoperiod can affect the regulatory pathways in plants that lead to floral initiation. In this report, results are presented from three experiments in which supplemental light with metal halide lamps (250 µmol m–2 s–1, 20 hours day–1, approx. 6 weeks) was tested as a complement to other flowering stimulation treatments (elevated temperature, treatment with gibberellin A4 and A 7 (GA4/7), restricted water supply) applied to potted Picea abies (L.) Karst. in the greenhouse. Flower stimulation in a greenhouse resulted in more floral initiation compared to flower stimulation outdoors. Supplemental light treatment increased floral initiation further, and to a larger extent in female than in male flowers. It also increased the proportion of trees and genotypes that induced reproductive buds. In a practical application of the supplemental light treatment to potted Picea abies breeding material, 90.6% of the clones produced either female or male flowers, or both. A subset of the same material kept outdoors, and thus subjected to natural light and temperatures, produced no flowers despite being treated with GA4/7 and receiving a restricted water supply. In conclusion, supplemental light treatment facilitates breeding programmes, and seed production of highly improved base material from new selections for vegetative production programmes, to be more efficient.

  • Almqvist, Skogforsk (The Forestry Research Institute of Sweden), Uppsala Science Park, 751 83 Uppsala, Sweden ORCID http://orcid.org/0000-0001-5739-4854 E-mail: curt.almqvist@skogforsk.se (email)
article id 212, category Research article
Sandhya Samarasinghe. (2009). Exploration of fracture dynamics properties and predicting fracture toughness of individual wood beams using neural networks. Silva Fennica vol. 43 no. 2 article id 212. https://doi.org/10.14214/sf.212
Keywords: Pinus radiata; wood properties; cracks; initiation; New Zealand; peak stress; speed; video imaging
Abstract | View details | Full text in PDF | Author Info
In this study, the time to crack initiation (Tinit), duration of crack propagation (Tfrac), crack initiation stress, peak stress as well as crack speed and fracture toughness were investigated for three Rates of Loading (ROL) and four sizes of notched wood beams using high-speed video imaging and neural networks. Tinit was consistent for all volumes and the average Tinit was nonlinearly related to volume and ROL. For the smallest ROL, there was a distinct volume effect on Tinit and the effect was negligble at the largest ROL. However, the stress at crack initiation was not consistent. Contrasting these, Tfrac for all volumes appeared to be highly variable but the peak stress carried prior to catastrophic failure was consistent. The crack propagation was a wave phenomenon with positive and negative (crack closure) speeds that varied with the ROL. As accurate estimation of crack initiation load (or stress) and its relationship to peak load (or stress) is important for determining fracture toughness, Artificial Neural Networks (ANN) models were developed for predicting them from volume, Young’s modulus, face and grain angles, density, moisture content and ROL. Models for crack initiation load and peak load showed much higher predictive power than those for the stresses with correlation coefficients of 0.85 and 0.97, respectively, between the actual and predicted loads. Neural networks were also developed for predicting fracture toughness of individual wood specimens and the best model produced a statistically significant correlation of 0.813 between the predicted and actual fracture toughness on a validation dataset. The inputs captured 62% of variability of fracture toughness. Volume and Young’s modulus were the top two contributing variables with others providing lesser contributions.
  • Samarasinghe, Centre for Advanced Computational Solutions (C-fACS), Lincoln University, Canterbury, New Zealand E-mail: sandhya.samarasinghe@lincoln.ac.nz (email)

Category : Research note

article id 608, category Research note
Jouni Partanen, Ilkka Leinonen, Tapani Repo. (2001). Effect of accumulated duration of the light period on bud burst in Norway spruce (Picea abies) of varying ages. Silva Fennica vol. 35 no. 1 article id 608. https://doi.org/10.14214/sf.608
Keywords: Norway spruce; phenology; growth initiation; photoperiod
Abstract | View details | Full text in PDF | Author Info
One-year-old seedlings (two sowing times), two-year-old seedlings and 14- and 18-year-old cuttings of Norway spruce (Picea abies (L.) Karst.) were exposed to shortening photoperiod (initially 16 h), lengthening photoperiod (initially 6 h) and constant short photoperiod (6 h) treatments with uniform temperature conditions in growth chambers. The timing of bud burst was examined. In all plants, shortening photoperiod treatment seemed to promote bud burst compared with other treatments. This effect was clearest in the oldest material. The results suggest that, in addition to temperature sum, the accumulated duration of the light period may promote bud burst of Norway spruce.
  • Partanen, Finnish Forest Research Institute, Punkaharju Research Station, Finlandiantie 18, FIN-58450 Punkaharju, Finland E-mail: jouni.partanen@metla.fi (email)
  • Leinonen, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: il@nn.fi
  • Repo, University of Joensuu, Faculty of Forestry, P.O. Box 111, FIN-80101 Joensuu, Finland E-mail: tr@nn.fi

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