Comparison of the Gherkin yield under differnt biofertilizer regimes
Tharaka Wijerathna and Chapa Devapriya
6/23/2021
Question: What is the best fertilizer regime
Hypothesis: Bio-fertilizers perform better than inorganic fertilizers
library(tidyverse) # for ggplot2 and tidyrOriginal dataset
gherkinCrude <- read_csv("~/ChapGherkin/ChapaData.csv")## Warning: Missing column names filled in: 'X2' [2], 'X3' [3], 'X5' [5], 'X6' [6],
## 'X7' [7], 'X8' [8], 'X9' [9], 'X10' [10], 'X12' [12], 'X13' [13], 'X14' [14],
## 'X15' [15], 'X16' [16], 'X17' [17], 'X18' [18], 'X20' [20]gherkinCrude## # A tibble: 222 x 20
## `1ST HARVEST` X2 X3 `LENGTH(cm)` X5 X6 X7 X8 X9 X10
## <chr> <chr> <chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <lgl>
## 1 <NA> WEIGHT POD NU… 1 2 3 4 5 NA NA
## 2 R1T1 3852 15 16.5 16 15.1 14.2 15.5 15.5 NA
## 3 R1T2 4254 15 18 16 17.1 16.5 15.4 16.6 NA
## 4 R1T3 3112 11 16.5 16 15.2 17.1 13.5 15.7 NA
## 5 R1T4 3714 14 15.2 17.1 16.4 15.5 16.2 16.1 NA
## 6 R1T5 4016 15 17.5 16.2 18.3 17.4 16.1 17.1 NA
## 7 R1T6 5142 18 16.7 17.1 16.2 15.3 15.4 16.1 NA
## 8 R2T1 3160 13 13.6 15 15.4 16.5 17 15.5 NA
## 9 R2T2 2988 11 16.6 15.5 15.5 16.1 16.3 16 NA
## 10 R2T3 2010 7 17.6 14.1 17 17 16.3 16.4 NA
## # … with 212 more rows, and 10 more variables: GIRTH(mm) <chr>, X12 <dbl>,
## # X13 <dbl>, X14 <dbl>, X15 <dbl>, X16 <chr>, X17 <lgl>, X18 <lgl>,
## # Servival Rate <chr>, X20 <dbl>This data set has already been cleaned, pivoted and arranged into different csv sheets
These data includes
1.Length of the fruit 2.Girth of the fruit 3. Yield of the fruit 4. Survival rate of the plants
fruitlengthGherkin <- data.frame(read_csv("~/ChapGherkin/Fulldatasets/fruitlengthGherkin.csv"))
fruitgirthGherkin <- data.frame(fruitlengthGherkin$treatment, read_csv("~/ChapGherkin/Fulldatasets/fruitgirthGherkin.csv"))
colnames(fruitgirthGherkin) <- c("treatment", "girth1", "girth2", "girth3", "girth4", "girth5")
yieldGherkin <- data.frame(read_csv("~/ChapGherkin/Fulldatasets/yieldGherkin.csv"))
srGherkin <- read_csv("~/ChapGherkin/Fulldatasets/srGherkin.csv")Fruit length
summary(fruitlengthGherkin)## treatment length1 length2 length3
## Length:180 Min. : 6.20 Min. : 9.20 Min. : 9.70
## Class :character 1st Qu.:14.40 1st Qu.:14.40 1st Qu.:14.30
## Mode :character Median :15.50 Median :15.50 Median :15.40
## Mean :15.49 Mean :15.32 Mean :15.37
## 3rd Qu.:16.77 3rd Qu.:16.20 3rd Qu.:16.60
## Max. :21.60 Max. :21.00 Max. :21.00
## NA's :2 NA's :7 NA's :22
## length4 length5
## Min. :10.20 Min. : 7.70
## 1st Qu.:14.50 1st Qu.:14.30
## Median :15.50 Median :15.50
## Mean :15.66 Mean :15.52
## 3rd Qu.:17.00 3rd Qu.:16.50
## Max. :19.70 Max. :20.40
## NA's :45 NA's :67Lets further arrange the data set
fruitl_dftemp <- pivot_longer(fruitlengthGherkin, names_to = "trial", values_to = "length", cols = starts_with("length"))
fruitl_df <- fruitl_dftemp[, -2]
fruitl_dfsumz = summarise(fruitl_df, mean(fruitl_df),sd=sd(length))## Warning in mean.default(fruitl_df): argument is not numeric or logical:
## returning NAhead(fruitl_dfsumz)## # A tibble: 1 x 2
## `mean(fruitl_df)` sd
## <dbl> <dbl>
## 1 NA NAfruitlsplit <- split.data.frame(fruitl_df, fruitl_df$treatment)
fruitlsplitmeans <- c()
fruitsplitsd <- c()
for (i in 1:length(fruitlsplit)) {
fruitlsplitmeans[i] <- mean(fruitlsplit[[i]]$length, na.rm = TRUE)
fruitsplitsd[i] <- sd(fruitlsplit[[i]]$length, na.rm = TRUE)
}
fruitlmeans_df <- data_frame(unique(fruitl_df$treatment), fruitlsplitmeans, fruitsplitsd) %>% `colnames<-`(c("treatment", "mean", "sd"))## Warning: `data_frame()` was deprecated in tibble 1.1.0.
## Please use `tibble()` instead.Lets visualize the data
gflbarplot <- ggplot(fruitlmeans_df, aes(x=factor(treatment, level = c("ewcompjeewamurthum", "vircompjeewamurthum", "noadditivecomp", "indonesianfert", "inorganicfert", "normalsoil")), y=mean, color = "lightblue")) +
geom_bar(color = "black", stat="identity", alpha = 0.5, position = "dodge") +
geom_errorbar(color = "black", aes(ymin = mean - sd, ymax= mean + sd), stat = "identity", position = "dodge", size = 0.5, width = 0.2) +
labs(title = "", x="Treatment", y="Length of the fruit (cm)", family = "Times New Roman") +
theme_bw() +
scale_x_discrete(labels=c("Compost + EWC + JM","Compost + JM", "Compost", "Indonesian fertilizer", "Inorganic fertilizer", "Reference")) +
theme(
panel.background = element_rect(fill = "transparent"), # bg of the panel
plot.background = element_rect(fill = "transparent", color = NA), # bg of the plot
panel.grid.major = element_blank(), # get rid of major grid
panel.grid.minor = element_blank(),
axis.line.x = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.line.y = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.title.x = element_text(face="bold", size=15, margin=margin(15,0,0,0), family = "Times New Roman"),
axis.text.x = element_text(size=8, face = "bold", colour = "black", family = "Times New Roman"),
axis.title.y = element_text(face="bold", size=15, margin=margin(0,15,0,0), family = "Times New Roman"),
axis.text.y = element_text(size=9, face = "bold", colour = "black", family = "Times New Roman"),
plot.title = element_text(lineheight=.8, face="bold",size=30, margin = margin(0,0,15,0), family = "Times New Roman"),
)
ggsave(plot = gflbarplot, file = "gflbarplot.png",
type = "cairo-png", bg = "transparent",
width = 20, height = 15, units = "cm", dpi = 800)
gflbarplot
gflboxplot <- ggplot(fruitl_df, aes(x=treatment, y=length)) +
geom_boxplot(stat = "boxplot") +
theme_bw() +
scale_x_discrete(labels=c("Compost + EWC + JM","Compost + JM", "Compost", "Indonesian fertilizer", "Inorganic fertilizer", "Reference")) +
labs(title= "", x="Treatment", y="Length of the fruit (cm)", family = "Times New Roman") +
theme(
panel.background = element_rect(fill = "transparent"), # bg of the panel
plot.background = element_rect(fill = "transparent", color = NA), # bg of the plot
panel.grid.major = element_blank(), # get rid of major grid
panel.grid.minor = element_blank(),
axis.line.x = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.line.y = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.title.x = element_text(face="bold", size=15, margin=margin(15,0,0,0), family = "Times New Roman"),
axis.text.x = element_text(size=8, face = "bold", colour = "black", family = "Times New Roman"),
axis.title.y = element_text(face="bold", size=15, margin=margin(0,15,0,0), family = "Times New Roman"),
axis.text.y = element_text(size=9, face = "bold", colour = "black", family = "Times New Roman"),
plot.title = element_text(lineheight=.8, face="bold",size=30, margin = margin(0,0,15,0), family = "Times New Roman"),
)
ggsave(plot = gflboxplot, file = "gflboxplot.png",
type = "cairo-png", bg = "transparent",
width = 20, height = 15, units = "cm", dpi = 800)## Warning: Removed 143 rows containing non-finite values (stat_boxplot).gflboxplot## Warning: Removed 143 rows containing non-finite values (stat_boxplot).
Highest mean fruit length was observed for indonesian fertiliser. However, the boxplot shows a consistency of larger sized fruits in compost and jeewamurthum treated virgin soil.
Higher number of outliers below the IQR for inorganic fertilizers.
ANOVA to statistically assess the difference of means.
gfl.aov <- aov(data = na.omit(fruitl_df), length ~ treatment)
summary(gfl.aov)## Df Sum Sq Mean Sq F value Pr(>F)
## treatment 5 30.5 6.094 1.58 0.163
## Residuals 751 2897.1 3.858Fruit girth
summary(fruitgirthGherkin)## treatment girth1 girth2 girth3
## Length:180 Min. :11.80 Min. :10.60 Min. :11.30
## Class :character 1st Qu.:48.73 1st Qu.:45.57 1st Qu.:46.40
## Mode :character Median :53.42 Median :51.50 Median :51.06
## Mean :51.64 Mean :49.80 Mean :49.77
## 3rd Qu.:56.55 3rd Qu.:54.80 3rd Qu.:54.77
## Max. :70.40 Max. :67.80 Max. :71.50
## NA's :2 NA's :7 NA's :22
## girth4 girth5
## Min. :13.20 Min. :13.20
## 1st Qu.:48.89 1st Qu.:46.67
## Median :52.00 Median :52.82
## Mean :51.25 Mean :51.95
## 3rd Qu.:55.73 3rd Qu.:56.00
## Max. :66.40 Max. :69.95
## NA's :45 NA's :67fruitg_dftemp <- pivot_longer(fruitgirthGherkin, names_to = "trial", values_to = "girth", cols = starts_with("girth"))
fruitg_df <- fruitg_dftemp[, -2]
fruitgsplit <- split.data.frame(fruitg_df, fruitg_df$treatment)
fruitgsplitmeans <- c()
fruitsplitsd <- c()
for (i in 1:length(fruitgsplit)) {
fruitgsplitmeans[i] <- mean(fruitgsplit[[i]]$girth, na.rm = TRUE)
fruitsplitsd[i] <- sd(fruitgsplit[[i]]$girth, na.rm = TRUE)
}
fruitgmeans_df <- data_frame(unique(fruitg_df$treatment), fruitgsplitmeans, fruitsplitsd) %>% `colnames<-`(c("treatment", "mean", "sd"))gfgbarplot <- ggplot(fruitgmeans_df, aes(x=factor(treatment, level = c("ewcompjeewamurthum", "vircompjeewamurthum", "noadditivecomp", "indonesianfert", "inorganicfert", "normalsoil")), y=mean, color = "lightblue")) +
geom_bar(color = "black", stat="identity", alpha = 0.5, position = "dodge") +
geom_errorbar(color = "black", aes(ymin = mean - sd, ymax= mean + sd), stat = "identity", position = "dodge", size = 0.5, width = 0.2) +
labs(title = "", x="Treatment", y="Girth of the fruit (cm)", family = "Times New Roman") +
theme_bw() +
scale_x_discrete(labels=c("Compost + EWC + JM","Compost + JM", "Compost", "Indonesian fertilizer", "Inorganic fertilizer", "Reference")) +
theme(
panel.background = element_rect(fill = "transparent"), # bg of the panel
plot.background = element_rect(fill = "transparent", color = NA), # bg of the plot
panel.grid.major = element_blank(), # get rid of major grid
panel.grid.minor = element_blank(),
axis.line.x = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.line.y = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.title.x = element_text(face="bold", size=15, margin=margin(15,0,0,0), family = "Times New Roman"),
axis.text.x = element_text(size=8, face = "bold", colour = "black", family = "Times New Roman"),
axis.title.y = element_text(face="bold", size=15, margin=margin(0,15,0,0), family = "Times New Roman"),
axis.text.y = element_text(size=9, face = "bold", colour = "black", family = "Times New Roman"),
plot.title = element_text(lineheight=.8, face="bold",size=30, margin = margin(0,0,15,0), family = "Times New Roman"),
)
ggsave(plot = gfgbarplot, file = "gfgbarplot.png",
type = "cairo-png", bg = "transparent",
width = 20, height = 15, units = "cm", dpi = 800)
gfgbarplot
gfgboxplot <- ggplot(fruitg_df, aes(x=treatment, y=girth)) +
geom_boxplot(stat = "boxplot") +
theme_bw() +
scale_x_discrete(labels=c("Compost + EWC + JM","Compost + JM", "Compost", "Indonesian fertilizer", "Inorganic fertilizer", "Reference")) +
labs(title= "", x="Treatment", y="Girth of the fruit (cm)", family = "Times New Roman") +
theme(
panel.background = element_rect(fill = "transparent"), # bg of the panel
plot.background = element_rect(fill = "transparent", color = NA), # bg of the plot
panel.grid.major = element_blank(), # get rid of major grid
panel.grid.minor = element_blank(),
axis.line.x = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.line.y = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.title.x = element_text(face="bold", size=15, margin=margin(15,0,0,0), family = "Times New Roman"),
axis.text.x = element_text(size=8, face = "bold", colour = "black", family = "Times New Roman"),
axis.title.y = element_text(face="bold", size=15, margin=margin(0,15,0,0), family = "Times New Roman"),
axis.text.y = element_text(size=9, face = "bold", colour = "black", family = "Times New Roman"),
plot.title = element_text(lineheight=.8, face="bold",size=30, margin = margin(0,0,15,0), family = "Times New Roman"),
)
ggsave(plot = gfgboxplot, file = "gfgboxplot.png",
type = "cairo-png", bg = "transparent",
width = 20, height = 15, units = "cm", dpi = 800)## Warning: Removed 143 rows containing non-finite values (stat_boxplot).gfgboxplot## Warning: Removed 143 rows containing non-finite values (stat_boxplot).
Highest mean fruit length was observed for indonesian fertiliser. However, the boxplot shows a consistency of larger sized fruits in compost and jeewamurthum treated virgin soil.
Higher number of outliers below the IQR for inorganic fertilizers.
Lets perform ANOVA to statistically assess this.
gfg.aov <- aov(data = na.omit(fruitg_df), girth ~ treatment)
summary(gfg.aov)## Df Sum Sq Mean Sq F value Pr(>F)
## treatment 5 207 41.44 0.525 0.757
## Residuals 751 59264 78.91Total yield (g)
summary(yieldGherkin)## treatment yield numoffruits
## Length:180 Min. : 136 Min. : 1.000
## Class :character 1st Qu.: 799 1st Qu.: 4.000
## Mode :character Median :1527 Median : 6.000
## Mean :1811 Mean : 6.989
## 3rd Qu.:2520 3rd Qu.: 9.000
## Max. :6184 Max. :21.000
## NA's :2 NA's :2yielddftemp <- filter(yieldGherkin, !is.na(yieldGherkin$yield))
summary(yielddftemp)## treatment yield numoffruits
## Length:178 Min. : 136 Min. : 1.000
## Class :character 1st Qu.: 799 1st Qu.: 4.000
## Mode :character Median :1527 Median : 6.000
## Mean :1811 Mean : 6.989
## 3rd Qu.:2520 3rd Qu.: 9.000
## Max. :6184 Max. :21.000#calculating fruit weight
yield_df <- data.frame(yielddftemp$treatment,(yielddftemp$yield/yielddftemp$numoffruits))
colnames(yield_df) <- c("treatment", "weight")
fruitw_df <- yield_df
fruitwsplit <- split.data.frame(fruitw_df, fruitw_df$treatment)
fruitwsplitmeans <- c()
fruitwsplitsd <- c()
for (i in 1:length(fruitgsplit)) {
fruitwsplitmeans[i] <- mean(fruitwsplit[[i]]$weight, na.rm = TRUE)
fruitwsplitsd[i] <- sd(fruitwsplit[[i]]$weight, na.rm = TRUE)
}
fruitwmeans_df <- data_frame(unique(fruitw_df$treatment), fruitwsplitmeans, fruitwsplitsd) %>% `colnames<-`(c("treatment", "mean", "sd"))Lets visualize the data
gfwbarplot <- ggplot(fruitwmeans_df, aes(x=factor(treatment, level = c("ewcompjeewamurthum", "vircompjeewamurthum", "noadditivecomp", "indonesianfert", "inorganicfert", "normalsoil")), y=mean, color = "lightblue")) +
geom_bar(color = "black", stat="identity", alpha = 0.5, position = "dodge") +
geom_errorbar(color = "black", aes(ymin = mean - sd, ymax= mean + sd), stat = "identity", position = "dodge", size = 0.5, width = 0.2) +
labs(title = "", x="Treatment", y="Weight of the fruit (g)", family = "Times New Roman") +
theme_bw() +
scale_x_discrete(labels=c("Compost + EWC + JM","Compost + JM", "Compost", "Indonesian fertilizer", "Inorganic fertilizer", "Reference")) +
theme(
panel.background = element_rect(fill = "transparent"), # bg of the panel
plot.background = element_rect(fill = "transparent", color = NA), # bg of the plot
panel.grid.major = element_blank(), # get rid of major grid
panel.grid.minor = element_blank(),
axis.line.x = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.line.y = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.title.x = element_text(face="bold", size=15, margin=margin(15,0,0,0), family = "Times New Roman"),
axis.text.x = element_text(size=8, face = "bold", colour = "black", family = "Times New Roman"),
axis.title.y = element_text(face="bold", size=15, margin=margin(0,15,0,0), family = "Times New Roman"),
axis.text.y = element_text(size=9, face = "bold", colour = "black", family = "Times New Roman"),
plot.title = element_text(lineheight=.8, face="bold",size=30, margin = margin(0,0,15,0), family = "Times New Roman"),
)
ggsave(plot = gfwbarplot, file = "gfwbarplot.png",
type = "cairo-png", bg = "transparent",
width = 20, height = 15, units = "cm", dpi = 800)
gfwbarplot
gfwboxplot <- ggplot(fruitw_df, aes(x=treatment, y=weight)) +
geom_boxplot(stat = "boxplot") +
theme_bw() +
scale_x_discrete(labels=c("Compost + EWC + JM","Compost + JM", "Compost", "Indonesian fertilizer", "Inorganic fertilizer", "Reference")) +
labs(title= "", x="Treatment", y="Weight of the fruit (g)", family = "Times New Roman") +
theme(
panel.background = element_rect(fill = "transparent"), # bg of the panel
plot.background = element_rect(fill = "transparent", color = NA), # bg of the plot
panel.grid.major = element_blank(), # get rid of major grid
panel.grid.minor = element_blank(),
axis.line.x = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.line.y = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.title.x = element_text(face="bold", size=15, margin=margin(15,0,0,0), family = "Times New Roman"),
axis.text.x = element_text(size=8, face = "bold", colour = "black", family = "Times New Roman"),
axis.title.y = element_text(face="bold", size=15, margin=margin(0,15,0,0), family = "Times New Roman"),
axis.text.y = element_text(size=9, face = "bold", colour = "black", family = "Times New Roman"),
plot.title = element_text(lineheight=.8, face="bold",size=30, margin = margin(0,0,15,0), family = "Times New Roman"),
)
ggsave(plot = gfwboxplot, file = "gfwboxplot.png",
type = "cairo-png", bg = "transparent",
width = 20, height = 15, units = "cm", dpi = 800)
gfwboxplot
Highest mean fruit length was observed for indonesian fertiliser. However, the boxplot shows a consistency of larger sized fruits in compost and jeewamurthum treated virgin soil.
Higher number of outliers below the IQR for inorganic fertilizers.
Lets perform ANOVA to statistically assess this.
gfw.aov <- aov(data = na.omit(fruitw_df), weight ~ treatment)
summary(gfw.aov)## Df Sum Sq Mean Sq F value Pr(>F)
## treatment 5 26653 5331 0.671 0.646
## Residuals 172 1365448 7939Survival rate
srsplit <- split.data.frame(srGherkin, srGherkin$treatment)
srsplitmeans <- c()
srsplitsd <- c()
for (i in 1:length(srsplit)) {
srsplitmeans[i] <- mean(srsplit[[i]]$survival, na.rm = TRUE)
srsplitsd[i] <- sd(srsplit[[i]]$survival, na.rm = TRUE)
}
srmeans_df <- data_frame(unique(srGherkin$treatment), srsplitmeans, srsplitsd) %>% `colnames<-`(c("treatment", "mean", "sd"))srbarplot <- ggplot(srmeans_df, aes(x=factor(treatment, level = c("ewcompjeewamurthum", "vircompjeewamurthum", "noadditivecomp", "indonesianfert", "inorganicfert", "normalsoil")), y=mean, color = "lightblue")) +
geom_bar(color = "black", stat="identity", alpha = 0.5, position = "dodge") +
geom_errorbar(color = "black", aes(ymin = mean - sd, ymax= mean + sd), stat = "identity", position = "dodge", size = 0.5, width = 0.2) +
labs(title = "", x="Treatment", y="Survival rate of the plants (%)", family = "Times New Roman") +
theme_bw() +
scale_x_discrete(labels=c("Compost + EWC + JM","Compost + JM", "Compost", "Indonesian fertilizer", "Inorganic fertilizer", "Reference")) +
theme(
panel.background = element_rect(fill = "transparent"), # bg of the panel
plot.background = element_rect(fill = "transparent", color = NA), # bg of the plot
panel.grid.major = element_blank(), # get rid of major grid
panel.grid.minor = element_blank(),
axis.line.x = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.line.y = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.title.x = element_text(face="bold", size=15, margin=margin(15,0,0,0), family = "Times New Roman"),
axis.text.x = element_text(size=8, face = "bold", colour = "black", family = "Times New Roman"),
axis.title.y = element_text(face="bold", size=15, margin=margin(0,15,0,0), family = "Times New Roman"),
axis.text.y = element_text(size=9, face = "bold", colour = "black", family = "Times New Roman"),
plot.title = element_text(lineheight=.8, face="bold",size=30, margin = margin(0,0,15,0), family = "Times New Roman"),
)
ggsave(plot = srbarplot, file = "srbarplot.png",
type = "cairo-png", bg = "transparent",
width = 20, height = 15, units = "cm", dpi = 800)
srbarplot
srboxplot <- ggplot(srGherkin, aes(x=treatment, y=survival)) +
geom_boxplot(stat = "boxplot") +
theme_bw() +
scale_x_discrete(labels=c("Compost + EWC + JM","Compost + JM", "Compost", "Indonesian fertilizer", "Inorganic fertilizer", "Reference")) +
labs(title= "", x="Treatment", y="Survival rate of the plants (%)", family = "Times New Roman") +
theme(
panel.background = element_rect(fill = "transparent"), # bg of the panel
plot.background = element_rect(fill = "transparent", color = NA), # bg of the plot
panel.grid.major = element_blank(), # get rid of major grid
panel.grid.minor = element_blank(),
axis.line.x = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.line.y = element_line(colour = 'black', size=0.5, linetype='solid'),
axis.title.x = element_text(face="bold", size=15, margin=margin(15,0,0,0), family = "Times New Roman"),
axis.text.x = element_text(size=8, face = "bold", colour = "black", family = "Times New Roman"),
axis.title.y = element_text(face="bold", size=15, margin=margin(0,15,0,0), family = "Times New Roman"),
axis.text.y = element_text(size=9, face = "bold", colour = "black", family = "Times New Roman"),
plot.title = element_text(lineheight=.8, face="bold",size=30, margin = margin(0,0,15,0), family = "Times New Roman"),
)
ggsave(plot = srboxplot, file = "srboxplot.png",
type = "cairo-png", bg = "transparent",
width = 20, height = 15, units = "cm", dpi = 800)
srboxplot
sr.aov <- aov(data = na.omit(srGherkin), survival ~ treatment)
summary(sr.aov)## Df Sum Sq Mean Sq F value Pr(>F)
## treatment 5 1290 258.03 2.81 0.0662 .
## Residuals 12 1102 91.83
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Interpretations
Bio-fertilizers perform better than inorganic fertilizers. However, these effects are not statistically significant according to one-way ANOVA (P>0.05).