scholarly journals Comparing Stability Indices for Ripening Date and Yield in Blueberry

1996 ◽  
Vol 121 (2) ◽  
pp. 204-209 ◽  
Author(s):  
Creighton Gupton ◽  
John Clark ◽  
David Creech ◽  
Arlie Powell ◽  
Susan Rooks

To determine if any of the available techniques for estimating stability in different environments are useful in blueberry (Vaccinium ashei Reade and V. corymbosum L.), 14 clones were evaluated in nine environments for ripening date and yield. Type 1 and 2 stability statistics, plots for each genotype mean versus its coefficient of variation (cv) across environments (genotype grouping), environmental index regression, and cluster analyses were compared. The highest yielding rabbiteye and southern highbush clones across locations were not deemed stable by Type 1 and Type 2 stability statistics, genotype grouping, or environmental regression technique. No evidence of curvilinear response was found. The nonparametric cluster analysis with known cultivars included appears to be most useful compared to other methods of estimating stability used in this study.

2015 ◽  
Vol 70 (7-8) ◽  
pp. 191-195 ◽  
Author(s):  
Jose Isagani B. Janairo ◽  
Frumencio Co ◽  
Jose Santos Carandang ◽  
Divina M. Amalin

Abstract A reliable and statistically valid classification of biomineralization peptides is herein presented. 27 biomineralization peptides (BMPep) were randomly selected as representative samples to establish the classification system using k-means method. These biomineralization peptides were either discovered through isolation from various organisms or via phage display. Our findings show that there are two types of biomineralization peptides based on their length, molecular weight, heterogeneity, and aliphatic residues. Type-1 BMPeps are more commonly found and exhibit higher values for these significant clustering variables. In contrast are the type-2 BMPeps, which have lower values for these parameters and are less common. Through our clustering analysis, a more efficient and systematic approach in BMPep selection is possible since previous methods of BMPep classification are unreliable.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1414-1414
Author(s):  
S. Toyama ◽  
R. Oda ◽  
D. Tokunaga ◽  
S. Tsuchida ◽  
N. Hishikawa ◽  
...  

Background:The treatment of rheumatoid hand, which is characterized by thumb deformity, finger deformities, and ulnar drift (UD), is challenging. Its pathophysiology is complex, and a comprehensive understanding of the optimal intervention for this condition requires high technical skill and extensive clinical experience. Moreover, the natural course of rheumatoid hand itself remains unclear.Objectives:This study was performed to comprehensively evaluate rheumatoid hand through the specific parameters of each deformity.Methods:A rheumatoid hand cohort was established in 2004. In total, 134 hands of 67 patients were registered and underwent clinical evaluations. All hands surgically treated during follow-up were excluded from the study, but the contralateral hands were assessed. Evaluations were repeated in 2009 (100 hands of 52 patients) and in 2015 (63 hands of 37 patients) among all available patients. Therefore, among the data obtained from the 3 study endpoints, 297 hands were available for the cross-sectional analysis and 43 hands were available for the longitudinal analysis.Thumb deformities and finger deformities (swan-neck and boutonnière) were semi-quantitated by the Nalebuff classification score, and UD was quantified using a metacarpophalangeal joint condition scoring method1). A two-step cluster analysis was performed with entered parameters, and the distribution of each parameter was considered to clarify the characteristics of each cluster. The hands with different clusters at each endpoint were recruited for the following longitudinal analysis. The natural course of rheumatoid hand was considered based on the cluster change.Results:Seven clusters were used in this study to emphasize the impact of thumb deformity on function. The characteristics of each cluster were as follows. Cluster 1: mild finger deformities and various severities of UD; Cluster 2: type 1 thumb deformity and various severities of UD; Cluster 3: type 2 thumb deformity and severe UD; Cluster 4: type 3 or 4 thumb deformity, low or moderate level of swan-neck deformity, and various severities of UD; Cluster 5: various types of thumb deformity, severe boutonnière deformity, and various severities of UD; Cluster 6: type 1 thumb deformity, severe swan-neck deformity, and various severities of UD; and Cluster 7: type 6 thumb deformity.The longitudinal analysis showed that Cluster 1 mainly changed to Cluster 2 or 4, indicating progression of thumb deformity. Cluster 2 changed to Cluster 3, indicating that thumb type 1 progressed to type 2 (Figure 1). When the affected period was shorter than 10 years, the incidence of severe hand deformity (including two or more affected joint areas and low hand function) was <10%. In contrast, when the affected period was longer than 10 years, the incidence of severe hand deformity was >30% (Figure 2).Figure 1.Figure 2.Conclusion:This study suggests the presence of seven patterns of deformity enabling a comprehensive understanding of rheumatoid hand. Furthermore, the results of the longitudinal analysis suggest a natural course of rheumatoid hand progression. Therefore, from the distribution of parameters of each deformity and its severity, rheumatologists can easily classify rheumatoid hand and determine its pathophysiology to choose the most effective intervention.References:[1]Toyama S, Oda R, Tokunaga D et al. A new assessment tool for ulnar drift in patients with rheumatoid arthritis using pathophysiological parameters of the metacarpophalangeal joint. Modern rheumatology 2019, 29: 113-8.Acknowledgments:This work was supported by JSPS KAKENHI Grant Numbers JP19K19914.Disclosure of Interests:None declared


2022 ◽  
Vol 58 (1) ◽  
pp. 125-129
Author(s):  
K. J. Raghavendra ◽  
L. R. Meena ◽  
A. L. Meena ◽  
Debashis Dutta ◽  
Nirmal k ◽  
...  

The farming systems having diverse characteristics need to be understand for tailoredtechnological interventions. Farm typology designates the heterogeneous farmers’characteristics in to homogenous groups to understand the factual situation in the region.The multivariate analysis viz. PCA and Cluster analysis performed to minimize data andgroup them into homogenous characteristics by various farm variables. A cross sectionsurvey of 120 farmers in WPZ of Uttar Pradesh was carried out and identified 9 significantvariables and generated 4 PCs from PCA. Hierarchical clustering of PCs leads to groupingfarms into homogenous class. The predominant farm types based are type-1 (22.5%)livestock based intensive farms, type-2 (23.3%) are resource endowed large farms, type-3(10.8%) are crop based marginal farms and type-4 (43.3%) are small farmers with highprofit margin. Large farms are integrated with crop and animal components earning higherincome. The results show that the diversified farms with both livestock and crop sectorsare reaping better income and technology adoption capacities.


2008 ◽  
Vol 38 (15) ◽  
pp. 18
Author(s):  
SHERRY BOSCHERT
Keyword(s):  

2010 ◽  
Vol 30 (S 01) ◽  
pp. S150-S152
Author(s):  
G. Jiménez-Cruz ◽  
M. Mendez ◽  
P. Chaverri ◽  
P. Alvarado ◽  
W. Schröder ◽  
...  

SummaryHaemophilia A (HA) is X-chromosome linked bleeding disorders caused by deficiency of the coagulation factor VIII (FVIII). It is caused by FVIII gene intron 22 inversion (Inv22) in approximately 45% and by intron 1 inversion (Inv1) in 5% of the patients. Both inversions occur as a result of intrachromosomal recombination between homologous regions, in intron 1 or 22 and their extragenic copy located telomeric to the FVIII gene. The aim of this study was to analyze the presence of these mutations in 25 HA Costa Rican families. Patients, methods: We studied 34 HA patients and 110 unrelated obligate members and possible carriers for the presence of Inv22or Inv1. Standard analyses of the factor VIII gene were used incl. Southern blot and long-range polymerase chain reaction for inversion analysis. Results: We found altered Inv22 restriction profiles in 21 patients and 37 carriers. It was found type 1 and type 2 of the inversion of Inv22. During the screening for Inv1 among the HA patient, who were Inv22 negative, we did not found this mutation. Discussion: Our data highlight the importance of the analysis of Inv22 for their association with development of inhibitors in the HA patients and we are continuous searching of Inv1 mutation. This knowledge represents a step for genetic counseling and prevention of the inhibitor development.


1994 ◽  
Vol 71 (06) ◽  
pp. 731-736 ◽  
Author(s):  
M W Mansfield ◽  
M H Stickland ◽  
A M Carter ◽  
P J Grant

SummaryTo identify whether genotype contributes to the difference in PAI-1 levels in type 1 and type 2 diabetic subjects and whether genotype relates to the development of retinopathy, a Hind III restriction fragment length polymorphism and two dinucleotide repeat polymorphisms were studied. In 519 Caucasian diabetic subjects (192 type 1, 327 type 2) and 123 Caucasian control subjects there were no differences in the frequency of the Hind III restriction alleles (type 1 vs type 2 vs control: allele 1 0.397 vs 0.420 vs 0.448; allele 2 0.603 vs 0.580 vs 0.552) nor in the allelic frequency at either dinucleotide repeat sequence. In 86 subjects with no retinopathy at 15 years or more from diagnosis of diabetes and 190 subjects with diabetic retinopathy there was no difference in the frequency of Hind III restriction alleles (retinopathy present vs retinopathy absent: allele 1 0.400 vs 0.467; allele 2 0.600 vs 0.533) nor in the allelic frequencies at either dinucleotide repeat sequence. The results indicate that there is no or minimal influence of the PAI-1 gene on either PAI-1 levels or the development of diabetic retinopathy in patients with diabetes mellitus.


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