This study was conducted through the seasons of 2013 and 2014 to determine the optimum bud loads/ vine for Autumn Royal seedless "grapevines. Three years old uniform vines were uniform chosen and pruned to four levels of bud load, namely (32, 42, 52 and 60 buds/ vine). With fruiting spur at 2, 3 and 4 buds per spurThe results showed that the percentage of bursted buds was decreased significantly by increasing bud load /vine in the two seasons of the study. Data also indicated that 42 buds/ vine were more suitable for Autumn Royal seedless grapevines to produce good yield and fruit quality. On the other hand, 32 buds/vine or 60 buds/vine were unfavorable science it produced rather clusters.In addition, pruning Autumn Royal seedless "grapevines to 42buds /vine by leaving 21 spur with 2 eyes/spur or leaving 14 spur with 3 eyes per spur resulted a high yield and good quality, reduced cluster compactness and reduced shoot berries %, gave the greatest cluster weight, berry firmness, adherence, T.S.S and anthocyanin content. Increasing bud load increased number of cluster/vine and yield but reduced cluster weight. Vines pruned to 32 buds / vine gave the greatest C/N ratio of the canes. Whereas vines pruned to 60 buds / vine showed higher percent of T.A than the other levels of bud load and cane length.
This investigation was carried out at Bahteem farm Genetic resources research department ,field crop research institute , Agricultural Research Center ,Giza , Egypt during two growing seasons 2018/19 and 2019/20. Twenty landraces with two faba bean check landraces were grown in Randomized Complete Block Design (RCBD) with 3 replications to determine the genetic variability, morphological diversity and relationships among these landraces for agro-morphological and biochemical characteristics. Analysis of variance revealed high variability among all measured genotypes with respect to all agronomic and protein characteristic studied traits. Principle Component Analysis (PCA) was performed; the first principal component had 54.40% and 37.90% of the total variation (PC1) and the second principle component (PC2) explained 14.30% and 24.90% of the total variation for morphological and biochemical traits, respectively . The cumulative ratio of the first six primary components explained all variations of total variation. The studied faba bean landraces were distribution among PC biplot and clustered indicated distribution of studied material (matched with measured checks) by cluster or heat-map analysis. The results clustered or distributed differently based on morphological and biochemical traits. Then, GT biplot used to clear the relationship among the studied faba bean traits and landraces, showing that number of seeds and pods were the most positive effective traits in faba bean seed yield, causing highest harvest index. Results revealed that landrace G16 and G19 with the highest check Giza716 recorded the highest values of seed yield, number of seeds, number of pods and harvest index. GT biplot graph is a good preferred alternative procedure for each of correlation and cluster analyses and considered an effective technique beside or instead of cluster analysis for facility the interpretations. From all results, this work has provided useful data for elaboration of strategies for the conservation and sustainable management of the better genetic source germplasm and for Vicia faba improvement genetically.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2025 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.