Automatic plant-based water status monitoring in grapevine using an improved water transport and storage model

2017 ◽  
pp. 191-196 ◽  
Author(s):  
A. Baert ◽  
K. Steppe
Keyword(s):  
Water Transport ◽  
Water Status ◽  
Storage Model ◽  
Status Monitoring ◽  
And Storage

Linking stem diameter variations to sap flow, turgor and water potential in tomato

2010 ◽  
Vol 37 (5) ◽  
pp. 429 ◽  
Author(s):  
Tom De Swaef ◽  
Kathy Steppe
Keyword(s):  
Sap Flow ◽  
Water Status ◽  
Turgor Pressure ◽  
Stem Diameter ◽  
Water Shortages ◽  
Storage Model ◽  
Solanum Lycopersicum L ◽  
Yield Threshold ◽  
And Storage

Water status plays an important role for fruit quality and quantity in tomato (Solanum lycopersicum L.). However, determination of the plant water status via measurements of sap flow (FH2O) or stem diameter (D) cannot be done unambiguously since these variables are influenced by other effectors than the water status. We performed a semi-seasonal and a diurnal analysis of the simultaneous response of FH2O and D to environmental conditions, which allowed us to distinguish different influences on ΔD such as plant age, fruit load and water status and to reveal close diurnal relationships between FH2O and ΔD. In addition, an analysis of the diurnal mechanistic link between both variables was done by applying a slightly modified version of a water flow and storage model for trees. Tomato stems, in contrast with trees, seemed to maintain growth while transpiring because a large difference between turgor pressure (Ψp) and the yield threshold (Γ) was maintained. Finally, the simultaneous response of D and FH2O on irrigation events showed a possibility to detect water shortages.

Internal Water Status and Water Transport in Seed Onion Plants 1

1971 ◽  
Vol 63 (5) ◽  
pp. 779-784 ◽  
Author(s):  
A. A. Millar ◽  
W. R. Gardner ◽  
S. M. Goltz
Keyword(s):  
Water Transport ◽  
Water Status ◽  
Internal Water

Effects of Environment on Growth and Survival of Douglas-fir Transplants

1974 ◽  
Vol 4 (2) ◽  
pp. 193-200
Author(s):  
E. B. Tregunna ◽  
M. Crown
Keyword(s):  
Storage Time ◽  
Water Status ◽  
Douglas Fir ◽  
Planting Date ◽  
Growth And Survival ◽  
Lower Elevation ◽  
Survival And Growth ◽  
And Storage ◽  
Root Treatment ◽  
Spring Planting

Variation in lifting date, planting date, planting site, seedling history, root treatment, and storage time were tested for their effects on Douglas-fir transplants. Survival, water status, types of damage, and both shoot and root growth were measured. Survival decreased with later spring planting date in the field, but this was partly offset by trends in browsing. Survival was greater at the lower elevation. Differences in seed lot, or conditions in the nursery, resulted in differences in tree size, which had some effects because the larger trees were browsed more. Survival and growth were not markedly different between root treatments. Cold storage increased survival of trees lifted late in the spring. The relative turgidity of leaves from bareroot trees in storage was related to lifting date and subsequent survival. Survival decreased severely as lifting date progressed through March.

scholarly journals A negative storage model for precise but compact storage of genetic variation data

Database ◽  
2020 ◽  
Vol 2020 ◽  
Author(s):  
Guillermo Gonzalez-Calderon ◽  
Ruizheng Liu ◽  
Rodrigo Carvajal ◽  
Jamie K Teer
Keyword(s):  
Genomic Data ◽  
The State ◽  
Data Systems ◽  
Storage Model ◽  
Novel Approach ◽  
Whole Exome ◽  
Variation Data ◽  
Block Storage ◽  
And Performance ◽  
And Storage

Abstract Falling sequencing costs and large initiatives are resulting in increasing amounts of data available for investigator use. However, there are informatics challenges in being able to access genomic data. Performance and storage are well-appreciated issues, but precision is critical for meaningful analysis and interpretation of genomic data. There is an inherent accuracy vs. performance trade-off with existing solutions. The most common approach (Variant-only Storage Model, VOSM) stores only variant data. Systems must therefore assume that everything not variant is reference, sacrificing precision and potentially accuracy. A more complete model (Full Storage Model, FSM) would store the state of every base (variant, reference and missing) in the genome thereby sacrificing performance. A compressed variation of the FSM can store the state of contiguous regions of the genome as blocks (Block Storage Model, BLSM), much like the file-based gVCF model. We propose a novel approach by which this state is encoded such that both performance and accuracy are maintained. The Negative Storage Model (NSM) can store and retrieve precise genomic state from different sequencing sources, including clinical and whole exome sequencing panels. Reduced storage requirements are achieved by storing only the variant and missing states and inferring the reference state. We evaluate the performance characteristics of FSM, BLSM and NSM and demonstrate dramatic improvements in storage and performance using the NSM approach.

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