Agronomy4future

Let’s say we collected relative light intensity data across a wide range of the light spectrum in an LED experiment. and I’d like to create light spectrum curves regarding relative light intensity. First, I’ll define wavelength colors. The color at different ranges of wavelengths is always the same, so if we run this code, we can obtain the same color range at wavelength (which would be the x-axis of the graph). and let’s create curve graph. I’ll highlight the ranges…

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Here is one dataset, and I’ll use facet_wrap() to create bar graphs. First, let’s summarize the data. Then, I’ll create a bar graph using facet_wrap() to divide panels by irrigation. Now, I want to draw a y-axis border for the ‘Irrigation_Yes’ panel. We can achieve this simply by adding scales=”free”. © 2022 – 2023 https://agronomy4future.com

Setting up experimental design according to your experiment goal is the first step to achieve your experiment’s success. In Agronomy studies, experimental design involves the combination of treatments deployed in the field, and these treatments should be randomized. Randomization is important in experimental design as it helps our experiments avoid biases due to physical or biological factors. Of course, there are no specific, unconditional rules for randomization. In a very old-fashioned way, you can write treatment numbers on paper, and…

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Here is one dataset Let’s check the data type of each variable. The time column is in character format. When opening the data in Excel, it is considered text. I wish to create a time series graph, but this cannot be accomplished when the variables are in text format. Therefore, we need to convert the text to a time format. Now we can adjust time using scale_x_datetime() full summary: https://github.com/agronomy4future/r_code/blob/main/How_to_convert_character_to_POSIXct_format_in_R.ipynb © 2022 – 2023 https://agronomy4future.com