Browsing by Author "Sairasalo, Maria"

Research has shown that the temperature sum or the average of daily mean temperature, together with the photoperiod and genotype, determines the progress of faba bean towards flowering. However, other environmental factors such as photosynthetically active radiation (PAR) and humidity conditions (Sielianinow´s hydrothermal index K) have been found to have a secondary effect on the progress towards flowering. The timing of the development stages of faba bean growth is of great importance for its regional adaptation and the profitability of its cultivation in new and changing environments. Progress towards flowering and the environmental conditions during flowering strongly affect the yield of different cultivars. Identifying the environmental factors affecting initiation and induction of flowering enables the breeding of new, more sustainable cultivars of faba bean. Negative effects of stress factors to yield can be avoided using earlier flowering cultivars in cultivation. Changing climatic conditions are leading to long periods of dry and warm weather in Finland, the effect of which is particularly pronounced during flowering. The stage of flowering has been found to be the most sensitive stage of the development of faba bean, during which the amount and quality of the crop yield is determined. The aim of this study was to validate the functionality and suitability of the improved model for predicting the progress towards flowering in field conditions. The significance of PAR, K-index, the temperature mean and photoperiod was tested in the model predicting flowering, were the observations of flowering were from two growing seasons, 2016 and 2017, using 20 cultivars of faba bean. The impacts of these environmental factors on the model were also tested with broader observation data from six growing seasons: 2009 to 2012 together with 2016 to 2017. The best model was obtained with the combination of all parameters with the highest value of R2 (R2v2=0.999, R6v2= 0.964). In the model containing only photoperiod and temperature mean, values for R2 were too low. The parameters of PAR and K-index significantly (R2>0.90) increased the value of R2. When tested alone, PAR explained over 90 % of the flowering. However, the photoperiod and the temperature mean played an important role in the development and flowering and they are known to be critical for the induction of flowering of certain cultivars. With six years of observations, the coefficients for temperature mean in the model were negligible (p >0.05). Significant parameters were photoperiod, K-index and PAR. The cultivar ‘Kontu’ started to flower earlier than other cultivars and it had greatest variation between predicted and observed value in the model. Therefore, adding it to the function as extra parameter was important to bring its values closer to regression line and to improve the overall value of R2. The conditions in greenhouse are usually adjusted to the optimum for the plant, when normally varying humidity conditions are ignored. Effects of photoperiod and PAR on the development of faba bean cannot be distinguished in controlled light conditions. Field experiments lasting several growing seasons are required to be able to distinguish their effects. The model for predicting the progress towards flowering could be used to identify different qualities of various cultivars. The parameters in this model worked well in prediction of flower induction of faba bean in Finland.