DOI: 10.5061/dryad.69p8cz9cm
title: The growth traits of Trifolium pratense under unsterilized and sterilized cow dung

description: The dataset on nodulation, biomass, relative growth rate (RGR),
 phosphatase activity (PME), and mycorrhizal colonization rate
 of Trifolium pratense fertilized by the gradient cow dung supply
 (sterilized and unsterilized). The results showed that the growth of T.
 pratense increased with increasing dung supply, while sterilization
 decreased growth by 15-20% (p=0.068). Root nodulation increased with
 increasing dung supply but was significantly lower with sterilized dung.
 Both root PME activity and mycorrhizal colonization decreased with
 increasing dung supply but were unaffected by sterilization.
description: <strong>Materials and methods </strong>
 <em>Cow dung, soil and Trifolium pratense
 plants</em> Dung of highland cow (<em>Bos
 taurus L.</em>) was collected in a coastal dune nature reserve,
 National Park Zuid-Kennemerland, in the Netherlands (52.3961°N, 4.5921°E)
 on 25 February 2020. Cow dung was collected from six different
 individuals. They were watched with binoculars until they excreted dung,
 after which it was directly collected in a plastic bag. The samples were
 kept in a cooled box during transportation to the Biology Department of
 the Vrije Universiteit Brussel (VUB) and then stored at 4°C until further
 processing. Next, subsamples of different dung samples (different
 individuals) were mixed, sieved, and divided into two parts. One part
 (about 100 g) was sterilized at 120 °C with an autoclave pressure steam
 sterilizer (Vapour Line 135-B, VER International, the USA). The second
 part was kept unsterilized. Small subsamples of sterilized and
 unsterilized dung (ca. 10 g) were dried in the oven at 70°C for 72
 hours.  Seeds of <em>Trofolium pratense
 </em>obtained from a local provider (EcoFlora) were germinated in
 potting soil 3 weeks before the experiment. Then seedlings were
 transplanted from the germination trays to the experimental pots. Their
 roots were washed in demi water before planting in the sand. The biomass
 of the seedlings at the start of the experiment was on average 4.0 ± 0.1
 mg (dry weight determined of 5 seedlings from the germination tray). This
 average value was used for calculating the relative growth rate
 (RGR). <em>Experimental design and
 measurements</em> On 25 March 2022, <em>T.
 pratense </em>seedlings were transplanted to pots (0.4L) filled with
 a mixture of quartz sand with fresh cow dung, and 2 g of fresh soil. One
 seedling was planted per pot, and pots were placed on individual saucers.
 The quartz sand (obtained from Sibelco, type S32), had negligible N and P
 concentrations; levels below detection limits. The dung was supplied
 either in a sterilized or unsterilized treatment, and the dung supply
 level covered gradients of 1, 2, 4, 8, 12, 16, 24, 32, 48, and 64 mg N per
 pot. All treatments were duplicated. Thus, the total number of pots was:
 10 dung supply levels × 2 dung sterilization treatments × 2 replicates =
 40 pots. These pots were randomly distributed in a compartment of the
 greenhouse at the VUB Etterbeek campus in Brussels, and were watered with
 demi water supplied in the saucers addressing the demand of the plants,
 i.e. two or three times a week to prevent water limitation. After six
 weeks, leaf chlorophyll content represented by light absorption (SPAD
 values) was measured in three leaves of all
 <em>T.pratense</em> plants, using a Chlorophyll Meter 502-SPAD
 Plus (Konica Minolta, Munich, Germany). After 7 weeks
 (12 May 2022) the plants were harvested by washing the sand from the
 roots, and separating plants into shoots and roots. The shoots were put in
 paper bags and dried at 70°C for 48 hours, after which dry mass was
 measured. The roots were carefully inspected for the presence of root
 nodules, and the number of nodules was recorded and used as a proxy for
 nodulation rate. After this step, the roots were dried with tissue paper
 and fresh root weight was measured. Subsequently, ca. 100 mg fresh roots
 (representative subsamples) were put in reaction tubes for the analysis of
 root PME activity. The root PME activity was determined using the
 para-nitrophenyl phosphate (pNPP) spectrophotometric method. Absorbance at
 410 nm was measured with Genesys<sup>TM</sup> 10 Series
 Spectrophotometer (Thermo Spectronic, Darmstadt, Germany), and the ‘μmol
 pNPP cleaved per g fresh root per hour’ was used to indicate root PME
 activity. A second subsample of the fresh roots was weighed (to enable dry
 mass calculation later) and put in a stored 50% glycerol solution. These
 subsamples were used to measure the root mycorrhizal colonization rate
 using the root segment colonization weighting method. Thereto, the roots
 were cleaned and stained, after which the mycorrhizal colonization was
 assessed for 25 root fragments (length 1 cm) for each root sample. Due to
 the limited quantity of root samples available, we lack data on the
 mycorrhizal colonization rates of two plants. Finally, a third subsample
 of the fresh roots was used to determine the moisture content of the fresh
 roots. Of these subsamples, both fresh weight and dry weight (after 48
 hours at 70°C) were determined. The moisture contents of these subsamples
 were also used to calculate the dry weights of the subsamples used for
 root PME activity and mycorrhizal colonization. This enabled the
 calculation of total root biomass, total biomass, and root mass ratio (RMR
 = dry root mass / dry total plant mass). The RGR was calculated as (ln(dry
 plant mass at harvest) – ln(dry plant mass at the start) / (the number of
 days) (Hunt, 1990).
 <em>Statistics</em> Prior to
 conducting all statistical analyses, the dung supply was transformed by
 log(x+1), and the SPAD values representing leaf chlorophyll content by
 log(x) to meet assumptions of normality and homogeneity. We used the
 function ‘lmer’ in the <em>lme4</em> package for linear
 mixed-effects modelling (LMMs) on RGR, root PME activity, mycorrhizal
 colonization rate, biomass, RMR and leaf chlorophyll (log(SPAD)), with the
 replicate as a random factor and obtained the ANOVA result by Type III
 Wald Chi-squared tests using the function ‘Anova’ in
 the <em>car</em> package (version 3). Additionally, we fitted
 a model of the number of root nodules by generalized linear mixed-effects
 modeling (GLMMs) with Poisson distribution using the function ‘glmer’ in
 the <em>lme4</em> package. Moreover, we also assessed the
 relationship between RGR with the number of root nodules and with the
 mycorrhizal colonization rate under the two dung sterilization treatments
 and the gradient of dung supply by LMMs. Statistical analyses were
 conducted using R Statistical Computing version 4.3.2.
description: # The growth traits of Trifolium pratense under unsterilized and
 sterilized cow dung
 [https://doi.org/10.5061/dryad.69p8cz9cm](https://doi.org/10.5061/dryad.69p8cz9cm) ## Description of the data and file structure The growth traits of Trifolium pratense under adding sterilized or unsterilized fresh cow dung collected in European coastal dune ecosystem. The total number of samples was: 10 dung supply levels × 2 dung sterilization treatments (unsterilized vs. sterilized) × 2 replicates = 40 samples The N concentration was 13.3 ± 0.1 mg g-1 dry dung, and the P concentration was 1.91 ± 0.04 mg g-1 dry dung. The N:P ratio was 7.0 ± 0.2. Due to the autoclave pressure steam sterilization approach, the water content of sterilized dung after cooling down and evaporating decreased by 2.5% compared to unsterilized fresh dung. Therefore, the moisture contents of sterilized and unsterilized dung were 79.4 % and 81.90 %, respectively. Below is the table about gradients of N, P and fresh dung supply applied in the experiment. | Gradient of N supply (mg pot-1) | Gradient of P supply (mg pot-1) | Gradient of fresh sterilized dung (g pot-1) | Gradient of fresh unsterilized dung (g pot-1) | | :------------------------------ | :------------------------------ | :------------------------------------------ | :-------------------------------------------- | | 1 | 0.14 | 0.36±0.01 | 0.42±0.01 | | 2 | 0.29 | 0.73±0.01 | 0.83±0.01 | | 4 | 0.57 | 1.46±0.03 | 1.66±0.03 | | 8 | 1.15 | 2.92±0.05 | 3.32±0.06 | | 12 | 1.72 | 4.38±0.08 | 4.98±0.09 | | 16 | 2.29 | 5.84±0.11 | 6.65±0.12 | | 24 | 3.44 | 8.76±0.16 | 9.97±0.18 | | 32 | 4.59 | 11.68±0.21 | 13.29±0.24 | | 48 | 6.89 | 17.52±0.32 | 19.94±0.36 | | 64 | 9.18 | 23.36±0.42 | 26.59±0.48 | ### Files and variables #### File: total\_data.csv **Description:**  ##### Variables * sterilization trt: 2 levels; S is for sterilized cow dung and C is for unsterilized cow dung (factor, no unit) * N supply: 10 levels; 1, 2, 4, 8, 12, 16, 24, 32, 48, 64 mg N supply (factor, mg N/pot) * log(N supply): 10 levels; log(1) to log(64) (factor, no unit) * nodules: the number of root nodules of Trifolium pratense (dependent variable, counts) * log(SPAD): for chlorophyll (dependent variable, no unit) * root biomass: dry root biomass (dependent variable, g) * shoot biomass: dry shoot biomass (dependent variable, g) * total biomass: dry total biomass = dry root biomass + dry shoot biomass (dependent variable, g) * RMR: root mass ratio; RMR = dry root mass / dry total plant mass (dependent variable, g/g) * RGR: relative growth rate; RGR = (ln(dry plant mass at harvest) – ln(dry plant mass at the start) / (the number of days) (dependent variable, g/g·day) * PME: root phosphomonoesterase activity; ‘μmol pNPP cleaved per g fresh root per hour’ (dependent variable, µmol pNPP cleaved per g fresh root per hour) * nodules/biomass: the number of root nodules/total biomass (dependent variable, no unit) * myco: mycorrhizal colonization rate (dependent variable, %) * dung amount: the amount of dung supply (factor, g/pot) * log(dung amount): it's acturally log(dung amount+1) (factor, no unit) * replicate: 2 levels (random factor, no unit) ## Code/software rm(list = ls())#clear global environment \#loading packages library(car) library(tidyverse) library(dplyr) library(nlme) library(lme4) \#loading dataset from the local folder total &lt;- read.table("total data.csv",header = T,sep = ",") total$sterilization.trt &lt;- factor(total$sterilization.trt) \#linear mixted effects modelling '+(1|replicate)' aganist with log(dung amount+1) model_nodules &lt;- glmer(nodules~sterilization.trt*log.dung.amount.+(1|replicate),data = total,family = 'poisson') Anova(model_nodules,type='III') model_RGR &lt;- lmer(RGR~sterilization.trt*log.dung.amount.+(1|replicate),data = total) Anova(model_RGR,type='III') model_chlo &lt;- lmer(log.SPAD.~sterilization.trt*log.dung.amount.+(1|replicate),data = total) Anova(model_chlo,type='III') model_RMR &lt;- lmer(RMR~sterilization.trt*log.dung.amount.+(1|replicate),data = total) Anova(model_RMR,type='III') model_PME &lt;- lmer(PME~sterilization.trt*log.dung.amount.+(1|replicate),data = total) Anova(model_PME,type='III') model_myco &lt;- lmer(myco~sterilization.trt*log.dung.amount.+(1|replicate),data = total) Anova(model_myco,type='III') model.root &lt;- lmer(root.biomass~sterilization.trt*log.dung.amount.+(1|replicate),data = total) Anova(model.root,type='III') model.shoot &lt;- lmer(shoot.biomass~sterilization.trt*log.dung.amount.+(1|replicate),data = total) Anova(model.shoot,type='III') model.totbio &lt;- lmer(total.biomass~sterilization.trt*log.dung.amount.+(1|replicate),data = total) Anova(model.totbio,type='III') ## Access information Data are from the greenhouse experiment performed at Vrije Universiteit Brussel (Etterbeek campus) in spring 2022.