Electronic characterization of the phenological stages of grapevine using a LIDAR sensor

Canopy characteristics and their variation at all growth stages, together with the spatial distribution of plants in the field need to be considered in determining the application volume rate in fruit crops. Spray volume calculation in a vineyard needs to take into account concepts such as tree row volume (TRV), leaf wall area (LWA) and leaf area index (LAI). The objective of this work was to develop one protocol to characterize the canopy geometry of grapevine to determine BBCH stages using data sets measured manually and with LIDAR scanning. With this aim, a package called PROcess TO LIdar Data v.0.1 (PROTOLIDAR) was created in R environment to process the LIDAR scan information. Results showed a significant correlation between LIDAR impacts and LAI at each growth stage. The relationship between the estimated values of TRV or LWA, and the growth stage of the vine was statistically significant (R2 = 0.99 and R2 = 0.95, respectively). Finally, the geometry characterizations of the plants were represented in 2 or 3D maps in GRASS-GIS.Postprint (published version

Electronic characterization of the phenological stages of grapevine using a LIDAR sensor

Canopy characteristics and their variation at all growth stages, together with the spatial distribution of plants in the field need to be considered in determining the application volume rate in fruit crops. Spray volume calculation in a vineyard needs to take into account concepts such as tree row volume (TRV), leaf wall area (LWA) and leaf area index (LAI). The objective of this work was to develop one protocol to characterize the canopy geometry of grapevine to determine BBCH stages using data sets measured manually and with LIDAR scanning. With this aim, a package called PROcess TO LIdar Data v.0.1 (PROTOLIDAR) was created in R environment to process the LIDAR scan information. Results showed a significant correlation between LIDAR impacts and LAI at each growth stage. The relationship between the estimated values of TRV or LWA, and the growth stage of the vine was statistically significant (R2 = 0.99 and R2 = 0.95, respectively). Finally, the geometry characterizations of the plants were represented in 2 or 3D maps in GRASS-GIS

Clinical manifestations of intermediate allele carriers in Huntington disease

Objective: There is controversy about the clinical consequences of intermediate alleles (IAs) in Huntington disease (HD). The main objective of this study was to establish the clinical manifestations of IA carriers for a prospective, international, European HD registry. Methods: We assessed a cohort of participants at risk with <36 CAG repeats of the huntingtin (HTT) gene. Outcome measures were the Unified Huntington's Disease Rating Scale (UHDRS) motor, cognitive, and behavior domains, Total Functional Capacity (TFC), and quality of life (Short Form-36 [SF-36]). This cohort was subdivided into IA carriers (27-35 CAG) and controls (<27 CAG) and younger vs older participants. IA carriers and controls were compared for sociodemographic, environmental, and outcome measures. We used regression analysis to estimate the association of age and CAG repeats on the UHDRS scores. Results: Of 12,190 participants, 657 (5.38%) with <36 CAG repeats were identified: 76 IA carriers (11.56%) and 581 controls (88.44%). After correcting for multiple comparisons, at baseline, we found no significant differences between IA carriers and controls for total UHDRS motor, SF-36, behavioral, cognitive, or TFC scores. However, older participants with IAs had higher chorea scores compared to controls (p 0.001). Linear regression analysis showed that aging was the most contributing factor to increased UHDRS motor scores (p 0.002). On the other hand, 1-year follow-up data analysis showed IA carriers had greater cognitive decline compared to controls (p 0.002). Conclusions: Although aging worsened the UHDRS scores independently of the genetic status, IAs might confer a late-onset abnormal motor and cognitive phenotype. These results might have important implications for genetic counseling. ClinicalTrials.gov identifier: NCT01590589

Clinical and genetic characteristics of late-onset Huntington's disease

Background: The frequency of late-onset Huntington's disease (&gt;59 years) is assumed to be low and the clinical course milder. However, previous literature on late-onset disease is scarce and inconclusive. Objective: Our aim is to study clinical characteristics of late-onset compared to common-onset HD patients in a large cohort of HD patients from the Registry database. Methods: Participants with late- and common-onset (30–50 years)were compared for first clinical symptoms, disease progression, CAG repeat size and family history. Participants with a missing CAG repeat size, a repeat size of ≤35 or a UHDRS motor score of ≤5 were excluded. Results: Of 6007 eligible participants, 687 had late-onset (11.4%) and 3216 (53.5%) common-onset HD. Late-onset (n = 577) had significantly more gait and balance problems as first symptom compared to common-onset (n = 2408) (P &lt;.001). Overall motor and cognitive performance (P &lt;.001) were worse, however only disease motor progression was slower (coefficient, −0.58; SE 0.16; P &lt;.001) compared to the common-onset group. Repeat size was significantly lower in the late-onset (n = 40.8; SD 1.6) compared to common-onset (n = 44.4; SD 2.8) (P &lt;.001). Fewer late-onset patients (n = 451) had a positive family history compared to common-onset (n = 2940) (P &lt;.001). Conclusions: Late-onset patients present more frequently with gait and balance problems as first symptom, and disease progression is not milder compared to common-onset HD patients apart from motor progression. The family history is likely to be negative, which might make diagnosing HD more difficult in this population. However, the balance and gait problems might be helpful in diagnosing HD in elderly patients