A workflow for selecting seeding density in desert species experiments

2022 ◽  
Vol 198 ◽  
pp. 104701
Author(s):  
Christopher J. Lortie ◽  
Nargol Ghazian ◽  
Mario Zuliani
Keyword(s):  
Seeding Density ◽  
Desert Species

SEEDING DENSITY OF DIFFERENT FISH SPECIES IN POLYCULTURE

2017 ◽  
pp. 74-79
Author(s):  
Yuriy Borisovich Lvov
Keyword(s):  
Fish Species ◽  
Silver Carp ◽  
Seeding Density ◽  
Habitat Conditions ◽  
Method Of Calculation ◽  
Fish Breeding ◽  
Trophic Preferences ◽  
Breeding Zone ◽  
Practical Progress

The article touches upon the principles, biological basics and practical progress of introduction of specific and age polyculture of fishes. Using the results of the analysis of literary and long-term native data, there has been offered the gradation of 12 fish species from different families by resistance to habitat conditions. Crucian ( Carassius gibelio ) has been chosen as the most sustainable object of cultivation. There has been taken an attempt to calculate the number of seeding different fish species in polyculture taking into account their physiological features is made. Subject to specific physiological features of the studied species, there was carried out recalculation of their natural reproductive performance in different fish-breeding zones, which is traditionally carried out for a carp ( Cyprinus carpio ). In particular, in the second fish-breeding zone with area of 1 hectare it is possible to breed 120 kg of carp, or 150 kg of crucian, or 75 kg of silver carp ( Hypophthalmichthys ). Overall productivity is made up of a share of fishes in polyculture, but taking into account tolerance of species, it can be lower than productivity calculated for carp. The method of calculation and formulas which give the chance to determine seeding density of fish species for breeding in polyculture have been offered. This technique makes it possible to use trophic preferences and consider tolerance of each species to the conditions of breeding areas.

scholarly journals Variable-rate in corn sowing for maximizing grain yield

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eder Eujácio da Silva ◽  
Fábio Henrique Rojo Baio ◽  
Daniel Fernando Kolling ◽  
Renato Schneider Júnior ◽  
Alex Rogers Aguiar Zanin ◽  
...  
Keyword(s):  
Grain Yield ◽  
Vegetative Growth ◽  
Maximum Yield ◽  
Influential Factors ◽  
Plant Population ◽  
Seeding Density ◽  
Corn Yield ◽  
Growth Indices ◽  
Experimental Conditions ◽  
Soil Attributes

AbstractSowing density is one of the most influential factors affecting corn yield. Here, we tested the hypothesis that, according to soil attributes, maximum corn productivity can be attained by varying the seed population. Specifically, our objectives were to identify the soil attributes that affect grain yield, in order to generate a model to define the optimum sowing rate as a function of the attributes identified, and determine which vegetative growth indices can be used to predict yield most accurately. The experiment was conducted in Chapadão do Céu-GO in 2018 and 2019 at two different locations. Corn was sown as the second crop after the soybean harvest. The hybrids used were AG 8700 PRO3 and FS 401 PW, which have similar characteristics and an average 135-day cropping cycle. Tested sowing rates were 50, 55, 60, and 65 thousand seeds ha−1. Soil attributes evaluated included pH, calcium, magnesium, phosphorus, potassium, organic matter, clay content, cation exchange capacity, and base saturation. Additionally, we measured the correlation between the different vegetative growth indices and yield. Linear correlations were obtained through Pearson’s correlation network, followed by path analysis for the selection of cause and effect variables, which formed the decision trees to estimate yield and seeding density. Magnesium and apparent electrical conductivity (ECa) were the most important soil attributes for determining sowing density. Thus, the plant population should be 56,000 plants ha−1 to attain maximum yield at ECa values > 7.44 mS m−1. In addition, the plant population should be 64,800 plants ha−1 at values < 7.44 mS m−1 when magnesium levels are greater than 0.13 g kg−1, and 57,210 plants ha−1 when magnesium content is lower. Trial validation showed that the decision tree effectively predicted optimum plant population under the local experimental conditions, where yield did not significantly differ among populations.

scholarly journals Expansion and characterization of bone marrow derived human mesenchymal stromal cells in serum-free conditions

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Samatha Bhat ◽  
Pachaiyappan Viswanathan ◽  
Shashank Chandanala ◽  
S. Jyothi Prasanna ◽  
Raviraja N. Seetharam
Keyword(s):  
Bone Marrow ◽  
Mesenchymal Stromal Cells ◽  
Stromal Cells ◽  
Population Doubling ◽  
Seeding Density ◽  
Population Doubling Time ◽  
Differentiation Potential ◽  
Serum Free ◽  
Safety Issues ◽  
Free Media

AbstractBone marrow-derived mesenchymal stromal cells (BM-MSCs) are gaining increasing importance in the field of regenerative medicine. Although therapeutic value of MSCs is now being established through many clinical trials, issues have been raised regarding their expansion as per regulatory guidelines. Fetal bovine serum usage in cell therapy poses difficulties due to its less-defined, highly variable composition and safety issues. Hence, there is a need for transition from serum-based to serum-free media (SFM). Since SFM are cell type-specific, a precise analysis of the properties of MSCs cultured in SFM is required to determine the most suitable one. Six different commercially available low serum/SFM with two different seeding densities were evaluated to explore their ability to support the growth and expansion of BM-MSCs and assess the characteristics of BM-MSCs cultured in these media. Except for one of the SFM, all other media tested supported the growth of BM-MSCs at a low seeding density. No significant differences were observed in the expression of MSC specific markers among the various media tested. In contrary, the population doubling time, cell yield, potency, colony-forming ability, differentiation potential, and immunosuppressive properties of MSCs varied with one another. We show that SFM tested supports the growth and expansion of BM-MSCs even at low seeding density and may serve as possible replacement for animal-derived serum.

scholarly journals Optimizing interleukin-2 concentration, seeding density and bead-to-cell ratio of T-cell expansion for adoptive immunotherapy

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Sasan Ghaffari ◽  
Monireh Torabi-Rahvar ◽  
Sajjad Aghayan ◽  
Zahra Jabbarpour ◽  
Kobra Moradzadeh ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Growth Kinetics ◽  
Cell Expansion ◽  
Mononuclear Cells ◽  
Adoptive Cell Therapy ◽  
Interleukin 2 ◽  
Seeding Density ◽  
Healthy Donors ◽  
T Cell Expansion

Abstract Background The successful ex vivo expansion of T-cells in great numbers is the cornerstone of adoptive cell therapy. We aimed to achieve the most optimal T-cell expansion condition by comparing the expansion of T-cells at various seeding densities, IL-2 concentrations, and bead-to-cell ratios. we first expanded the peripheral blood mononuclear cells (PBMCs) of a healthy donor at a range of 20 to 500 IU/mL IL-2 concentrations, 125 × 103 to 1.5 × 106 cell/mL, and 1:10 to 10:1 B:C (Bead-to-cell) ratios and compared the results. We then expanded the PBMC of three healthy donors using the optimized conditions and examined the growth kinetics. On day 28, CD3, CD4, and CD8 expression of the cell populations were analyzed by flow cytometry. Results T-cells of the first donor showed greater expansion results in IL-2 concentrations higher than 50 IU/mL compared to 20 IU/mL (P = 0.02). A seeding density of 250 × 103 cell/mL was superior to higher or lower densities in expanding T-cells (P = 0.025). Also, we witnessed a direct correlation between the B:C ratio and T-cell expansion, in which, in 5:1 and 10:1 B:C ratios T-cell significantly expanded more than lower B:C ratios. The results of PBMC expansions of three healthy donors were similar in growth kinetics. In the optimized condition, 96–98% of the lymphocyte population expressed CD3. While the majority of these cells expressed CD8, the mean expression of CD4 in the donors was 19.3, 16.5, and 20.4%. Conclusions Our methodology demonstrates an optimized culture condition for the production of large quantities of polyclonal T-cells, which could be useful for future clinical and research studies.

Self-Organized, Tubular Hybrid Vascular Tissue Composed of Vascular Cells and Collagen for Low-Pressure-Loaded Venous System

1995 ◽  
Vol 4 (6) ◽  
pp. 597-608 ◽  
Author(s):  
Jiro Hirai ◽  
Takehisa Matsuda
Keyword(s):  
Vascular Tissue ◽  
Venous System ◽  
Seeding Density ◽  
Outer Diameter ◽  
Type I ◽  
Dependent Manner ◽  
Mixed Solution ◽  
Vascular Cells ◽  
Collagen Concentration ◽  
Inner Diameter

A tubular, hierarchically structured hybrid vascular tissue composed of vascular cells and collagen was prepared. First, a cold mixed solution of bovine aortic smooth muscle cells (SMCs) and Type I collagen was poured into a tubular glass mold composed of a mandrel and a sheath (example of dimensions: inner diameter, 1.5 mm; outer diameter, 7 mm; length, 7 cm). Upon incubation at 37°C, an SMC-incorporated collagenous gel was formed. After the sheath was removed, the resulting fragile tissue, when cultured in medium, thinned in a time-dependent manner to form an opaque, dense tissue. Higher SMC seeding density and lower initial collagen concentration induced more rapid and prominent shrinkage of the tissue. Morphologic investigation showed that over time, bipolarly elongated SMCs and collagen fiber bundles became positioned around the mandrel. Both components became circumferentially oriented. When the mandrel was removed, a tubular hybrid medial tissue was formed. A hybrid vascular tissue with a hierarchical structure was constructed by seeding endothelial cells onto the inner surface of the hybrid medial tissue. Prepared tissues tolerated luminal pressures as great as 100 mmHg and mechanical stress applied during an anastomotic procedure. This method allowed us to prepare a tubular hybrid medial tissue of predetermined size (inner diameter, wail thickness, and length) by selecting appropriate mold design, initial collagen concentration, and SMC seeding density. Such hybrid vascular tissues may provide physiological functions when implanted into the venous system.

Seeding density modulates migration and morphology of rabbit chondrocytes cultured in collagen gels

2009 ◽  
Vol 102 (1) ◽  
pp. 294-302 ◽  
Author(s):  
Ali Baradar Khoshfetrat ◽  
Masahiro Kino-oka ◽  
Yasunori Takezawa ◽  
Takeyuki Yamamoto ◽  
Katsura Sugawara ◽  
...  
Keyword(s):  
Seeding Density ◽  
Collagen Gels

Seeding metrics for image velocimetry performances in rivers

2021 ◽  
Author(s):  
Silvano Fortunato Dal Sasso ◽  
Alonso Pizarro ◽  
Sophie Pearce ◽  
Ian Maddock ◽  
Matthew T. Perks ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Optical Sensors ◽  
Large Scale ◽  
Surface Flow ◽  
Surface Velocity ◽  
Seeding Density ◽  
Earth System ◽  
Science Data ◽  
Image Velocimetry ◽  
Hydraulic Conditions

&lt;p&gt;Optical sensors coupled with image velocimetry techniques are becoming popular for river monitoring applications. In this context, new opportunities and challenges are growing for the research community aimed to: i) define standardized practices and methodologies; and ii) overcome some recognized uncertainty at the field scale. At this regard, the accuracy of image velocimetry techniques strongly depends on the occurrence and distribution of visible features on the water surface in consecutive frames. In a natural environment, the amount, spatial distribution and visibility of natural features on river surface are continuously challenging because of environmental factors and hydraulic conditions. The dimensionless seeding distribution index (SDI), recently introduced by Pizarro et al., 2020a,b and Dal Sasso et al., 2020, represents a metric based on seeding density and spatial distribution of tracers for identifying the best frame window (FW) during video footage. In this work, a methodology based on the SDI index was applied to different study cases with the Large Scale Particle Image Velocimetry (LSPIV) technique. Videos adopted are taken from the repository recently created by the COST Action Harmonious, which includes 13 case study across Europe and beyond for image velocimetry applications (Perks et al., 2020). The optimal frame window selection is based on two criteria: i) the maximization of the number of frames and ii) the minimization of SDI index. This methodology allowed an error reduction between 20 and 39% respect to the entire video configuration. This novel idea appears suitable for performing image velocimetry in natural settings where environmental and hydraulic conditions are extremely challenging and particularly useful for real-time observations from fixed river-gauged stations where an extended number of frames are usually recorded and analyzed.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;strong&gt;References &lt;/strong&gt;&lt;/p&gt;&lt;p&gt;Dal Sasso S.F., Pizarro A., Manfreda S.,&amp;#160;Metrics for the Quantification of Seeding Characteristics to Enhance Image Velocimetry Performance in Rivers.&amp;#160;Remote Sensing,&amp;#160;12, 1789 (doi: 10.3390/rs12111789), 2020.&lt;/p&gt;&lt;p&gt;Perks M. T., Dal Sasso S. F., Hauet A., Jamieson E., Le Coz J., Pearce S., &amp;#8230;Manfreda S, Towards harmonisation of image velocimetry techniques for river surface velocity observations. Earth System Science Data, https://doi.org/10.5194/essd-12-1545-2020, 12(3), 1545 &amp;#8211; 1559, 2020.&lt;/p&gt;&lt;p&gt;Pizarro A., Dal Sasso S.F., Manfreda S.,&amp;#160;Refining image-velocimetry performances for streamflow monitoring: Seeding metrics to errors minimisation,&amp;#160;Hydrological Processes, (doi: 10.1002/hyp.13919), 1-9, 2020.&lt;/p&gt;&lt;p&gt;Pizarro A., Dal Sasso S.F., Perks M. and Manfreda S., Identifying the optimal spatial distribution of tracers for optical sensing of stream surface flow, Hydrology and Earth System Sciences, 24, 5173&amp;#8211;5185, (10.5194/hess-24-5173-2020), 2020.&lt;/p&gt;

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