Agronomy4future

This year, in the no-tillage field, the farmer has sprayed herbicide three times since planting. These days, the hot trend is carbon farming, and all approaches aim to mitigate GHG emissions, suggesting that no-tillage is beneficial for carbon sequestration. Although the academic trend consistently indicates that carbon farming is important, in reality, farmers have been using more herbicides to suppress weeds. Is carbon farming good for farmers and real farming systems? No-tillage might mitigate GHG emissions, but more herbicides are…

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In my previous post, I demonstrated how to create a data table using Python. If you’re interested, please refer to the post below. ■ How to create a data table in Python? I’ll summarize this data by mean and standard error. full code: https://github.com/agronomy4future/python_code/blob/main/How_to_summarize_data_using_Python.ipynb

One of the problems that can occur when drawing graphs using R is that the x-axis of the graph is sorted alphabetically. There is data as shown above. I used this data to create a graph as shown below. The above graph displays Amonium Sulfate first according to alphabetical order. However, I want to show the treatments in the following order: Calcium Nitrate first, followed by Urea, then Sodium Nitrate, and lastly Ammonium Sulfate. Here are two ways to change…

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GxE interaction is when the phenotypic difference between a pair of genotypes is larger or smaller in one environment than in another environment. It is important to understand that what genotypes have different phenotypic values in two environments is not the same as GxE interaction. Please look at above graph. Both genotypes had a different phenotype in the two different environments (Env1 and Env2), but there was no interaction in this case because the difference between the phenotypic values was…

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geom_hline(data=data.frame(variety=c(“A”, “B”)), aes(yintercept=c(195.4028, 206.0819)), linetype=”dashed”, color=”Dark blue”) +

geom_text(aes(family=”serif”,fontface=6), x=65, y=0.02, label=paste(“Pistolo\n”,pistolo_CT_MEAN, “±”, round(pistolo_CT_SE,digits=2)),size=7, col=”Black”)

label=paste(round(mean(na.rm=T,long_low$KW),digit=1),”mg”)

scale_x_discrete(limits=rev)

#guides(color=”none”) +