Chilling Heat Requirement

A total of 30 jojoba clones, among them six already commercial clones and 24 newly selected ones were characterized in terms of yield parameters, chilling requirements and morphological traits. The aim was to supply farmers (from Israel and abroad) better yielding clones. Considerable variability was found among the clones in all the parameters. Some clones exhibited excellent vegetative traits related to yield potential, such as a high survival rate, rapid growth, extensive branching, high node density, while others exhibited outstanding reproductive traits, such as earliness, high flower density, high percentage of fruit set, high seed weight, and high wax content in the seed. The clones also differed in their wax composition. Plants began to yield 2 years after planting in the field, some having commercial yields as early as their third year. The best clones with respect to wax yield were Hazerim, Negev, BGU, Forti, and Gvati, all new clones not yet planted in commercial plantations. An attempt to relate yield parameters at the third year to wax yield at their sixth year was made. The height in the third year and the flower index, relative fruit set and seed weight were related to yield. The flowering pattern of all clones was followed up during the season 1993/94, which was characterized by a combination of cool night temperatures with warm days. This weather enabled the clones that broke dormancy to flower during the winter instead of spring. We were thus able to identify clones with different chilling requirement. In conclusion some very promising clones with high yields can be added to our commercial clones. Owing to the new information gathered on depth of dormancy and flowering pattern, clones can also be allocated to environments differing in climatic conditions.

Winter chill, which temperate trees require in order to overcome dormancy, is expected to decrease substantially in the future in most deciduous fruit tree growing areas. Several mathematical models have been developed in different regions to quantify chill requirements of tree species and cultivars. The Dynamic model has emerged as the most plausible and reliable model, yet all chill models have been found inadequate in at least some growing regions. Accurate models are crucial for the development of quantitatively appropriate climate change adaptation strategies for temperate orchards. To demonstrate the importance of model choice we compared the outputs from 13 agricultural and forest chill models using past and projected future weather data for nine sites in Chile, Tunisia and Germany. To evaluate chill risk, we used a weather generator calibrated with 45 years of temperature data to generate 100 years of synthetic temperature records per scenario for multiple climate scenarios. Chill was computed for 10 past scenarios and projected for 60 future scenarios (for 2050 and 2085 according to greenhouse gas concentration scenarios RCP4.5 and RCP8.5, using projections from 15 climate models). Results show that estimations differ substantially across chill models, even for the same sites and scenarios. The "Chilling Hours" model and the "Chilling Rate" function showed high sensitivity across regions in future scenarios. The "North Carolina", "Utah", "Modified Utah" and "Low Chill" models all suggest negative chill levels for past and future scenarios in Tunisia (despite the thriving fruit tree industry there). Only two models projected chill decreases in all sites. In Mediterranean climate areas (central Chile and Tunisia) the "Dynamic" and "Positive Utah" models forecasted similar chill reductions for future scenarios, whereas in temperate locations (Germany) the "Dynamic" model forecasted lower chill increase compared with the "Utah" and "Positive Utah" models. Despite the "Dynamic" and the "Positive Utah" models showing similar performance among climates, the "Dynamic" model appears to be the best current option, due its more physiologically credible structure. However, further research is needed to develop or identify models that are valid across wide climatic gradients. Our results show that a major source of variation and inaccuracy in chilling assessments is the choice of the chill model used to make the assessment.

Winter chill, which temperate trees require to overcome dormancy, is expected to decrea- se substantially in the future in most deciduous fruit tree growing areas. Several mathema- tical models have been applied in different regions around the world to quantify this chill requirement. While the ‘Dynamic’ model has emerged as the most plausible and reliable model, chill models are still widely reported to be inadequate for some areas. We compared the outputs from 13 agricultural and forest chill models using past and projected weather data for nine sites in Chile, Tunisia and Germany. We used a weather generator calibrated with 45 years of temperature data to produce chill distributions for 100 synthetic years for multiple climate scenarios. Chill was computed for 10 past scenarios and projected for future scenarios (for 2050 and 2085 according to greenhouse gas concentration scenarios RCP4.5 and RCP8.5). Results show that models’ estimations differ substantially for the same site and scenario. The ‘North Carolina’, ‘Utah’, ‘Modified Utah’ and ‘Low Chill’ mo- dels indicated negative chill levels for past and future scenarios in Tunisia. These models, together with the ‘Positive Utah’ model, projected the greatest chill increases for locati- ons in Germany. The ‘Chilling Hours’ model and the ‘Chilling Rate’ function showed high sensitivity across regions in future scenarios. Just two models projected chill decreases in all sites. In Mediterranean climate areas (central Chile and Tunisia) the ‘Dynamic’ model and ‘Positive Utah’ model forecasted similar chill reductions in both year and RCP sce- narios, whereas in temperate locations (Germany) the ‘Dynamic’ model forecasted lower chill increase compared with ‘Utah’ and ‘Positive Utah’ models. Despite the ‘Dynamic’ model and the ‘Positive Utah’ model showing similar performance among climates, the ‘Dynamic’ model appears to be the best current option, due its more physiologically cre- dible approach. However, further research is needed to develop or identify models that are valid across wide climatic gradients. Such models are crucial for the development of quantitatively appropriate climate change adaptation strategies for temperate orchards.