From 46cf8aa4d1f5b39e5d93ed3ea921005c33d65081 Mon Sep 17 00:00:00 2001
From: Viktoria Petrova <vipet103@hhu.de>
Date: Mon, 25 Nov 2024 14:31:48 +0100
Subject: [PATCH] adjusting equation two in protocol

---
 ...orphologicalAndGrowth-relatedTraitsProtocol.md | 15 ++++-----------
 1 file changed, 4 insertions(+), 11 deletions(-)

diff --git a/assays/AssessmentOfMorphologicalAndGrowth-relatedTraits/protocols/AssessmentOfMorphologicalAndGrowth-relatedTraitsProtocol.md b/assays/AssessmentOfMorphologicalAndGrowth-relatedTraits/protocols/AssessmentOfMorphologicalAndGrowth-relatedTraitsProtocol.md
index cc70d04..aa2dc6b 100644
--- a/assays/AssessmentOfMorphologicalAndGrowth-relatedTraits/protocols/AssessmentOfMorphologicalAndGrowth-relatedTraitsProtocol.md
+++ b/assays/AssessmentOfMorphologicalAndGrowth-relatedTraits/protocols/AssessmentOfMorphologicalAndGrowth-relatedTraitsProtocol.md
@@ -7,23 +7,16 @@ The dry weight per row per plot was used to estimate the dry mass per plant (DMP
 **(1)**
 $$DMP=\frac{DM}{(TNP-NDP)+0.8\times NDP}$$
 
-
-
 where TNP was the total number of plants, NDP the number of damaged plants, 0.8 was the completeness of the damaged plants based on the observation during the harvest. DMP calculated as described above, was corrected separately for each time point for replicate and block effects. The corrected values were then used for further analyses.
 
 In the climate chamber experiment, the total aboveground DMP was measured by weighing at eight different time points (26, 36, 46, 57, 74, 102, 113, and 142 DAS) except for the two inbreds IG31424 and HOR1842, for which only the initial and the final DMP were determined at 26 and 142 DAS. Three replicates per genotype were collected for each time point.
 
 To assess the relationship between DMP and time, logistic (Verhulst, 1838), power-low (Paine et al., 2012), and quadratic regression (Lithourgidis and Dordas, 2010) models were fitted. The quadratic regression model was used:
 
- 
-(2)
-where 
- represents the initial biomass, 
- and c the growth rate parameters. This model had a high coefficient of determination (⁠
-⁠) and the highest heritability across all 23 barley inbreds. Thus, the quadratic regression was used for estimation of RGR. 
-⁠, 
-⁠, 
- represent the parameters in quadratic regression a, b, and c, respectively.
+**(2)**
+$$y_r=a+bt-ct^2$$
+
+where *a* represents the initial biomass, *b* and *c* the growth rate parameters. This model had a high coefficient of determination (⁠$$R^2$$⁠) and the highest heritability across all 23 barley inbreds. Thus, the quadratic regression was used for estimation of RGR. $$RGR_a$$, $$RGR_b$$, $$RGR_c$$ represent the parameters in quadratic regression *a*, *b*, and *c*, respectively.
 
 Morphological parameters were collected in multi-year and multi-environment field experiments that took place in the years 2017–2021 at Düsseldorf, Cologne, Mechernich, and Quedlinburg (Shrestha et al., 2022; Wu et al., 2022). Not all locations were used in all years to assess all parameters. Flag leaf length (FL, cm) and width (FW, cm), plant height (PH, cm), flowering time (FT), awn length (AL, cm), spike length (EL, cm), and spikelet number in one row of the spike (SR), seed length (SL, mm), seed width (SW, mm), seed area (SA, mm2), and thousand grain weight (TGW, g), grain weight (GW, kg per 10 m2), and net straw weight (NSW, kg per 10 m2) were measured as morphological parameters. FL, FW, AL, EL were measured by ruler, SL, SW, and SA were measured by MARViN seed analyser (MARViNTECH GmbH, Germany), and TGW was measured by MARViN and a balance.
 
-- 
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