Stories about crops and statistics (plus coding)
In the case of greenhouse pot experiments, image analysis to detect green leaf area is much simpler because of the well-controlled conditions. However, it is still mandatory to adjust settings to remove noise and isolate only the green leaves. This simple Python code provides an easy way to detect green leaf area. 1. Open Visual … Read more
I have soybean yield data that I want to upload to Github and access from R. First, let’s upload the data to Github. The data should be in .csv format. Click Add file, choose Upload files, and, after uploading, select the Raw button to view the data in .csv format as text. and you can … Read more
I’m planning to frequently collect biomass samples to observe how biomass accumulation differs among treatments or varieties over time. I assume that the growth will follow a curve pattern, characterized by slow accumulation during the early growing stage, followed by rapid growth, and eventually reaching a plateau. I want to visualize this curve through simulation, … Read more
Sometimes we need to convert our data to .json format, and I will introduce an easy way to do it using Python. I will use Google Colab. First, let’s mount Google Drive to Google Colab. Second, let’s upload a dataset from GitHub. I’ll convert this data to a .json file and download it to my … Read more
비 CS 전공자로서 코딩 공부는 늘 한계를 느끼곤 합니다. 혼자 코딩을 독학하며 현업에 필요한 프로그래밍 코드를 사용하고 있지만 가끔 “이 코드는 왜 이렇게 작동되는 것일까?” 에 대한 궁금증은 늘 가지고 있습니다. 그래서 여러 교육 플랫폼에서 온라인 강의를 들어봐도 대부분의 시각은 전공자에게 맞춰져 있기 때문에 저 같은 비 전공자가 따라 가기에는 종종 한계를 느끼곤 합니다. 최근 … Read more
I have corn yield data (Mg/ha) that I want to visualize. First, let’s upload the data. First, I’ll create yield distribution data. Now, we can see that the general grain yield varies from 10 to 30 Mg/ha, with some outliers. I’ll create a yield map to visualize this variation. https://github.com/agronomy4future/python_code/blob/main/Python_GIS_Interpolating_and_Plotting_Corn_Grain_Yield_Data.ipynb If you have the ArcGIS … Read more
In my previous post, I introduced stepwise regression to select the best model. I suggested that grain yield = -4616.47 + 10.53 * stem biomass + 41.03 * height, indicating that stem biomass and height are the most important variables affecting grain yield. ■ Stepwise Regression: A Practical Approach for Model Selection using R Now, … Read more
SCOPUS is one of the largest abstract and citation databases, providing access to a wide range of peer-reviewed literature across various disciplines. It ensures researchers have access to high-quality, up-to-date academic papers, conference proceedings, and other scholarly materials. Pybliometrics is a Python library that streamlines the retrieval of bibliometric data from SCOPUS. It simplifies accessing … Read more
Today, I’ll introduce one method for data normalization, utilizing the biomass with N and P uptake data available on my GitHub. I also aim to create regression graphs illustrating the relationship between biomass and either nitrogen or phosphorus. First, I’ll generate a regression graph for biomass with either nitrogen or phosphorus to observe the data … Read more
When creating a data table in R, it seems simple. How about using Python? © 2022 – 2023 https://agronomy4future.com
Kaggle is a popular online platform for data science and machine learning competitions, datasets, and tutorials. You can find high-quality data on Kaggle to practice data analysis. I have uploaded some of my data on Kaggle to share it with others. Recently, I’ve begun learning machine learning, and one of the most fundamental datasets for … Read more
Before diving into in-depth data analysis, a crucial step is data preprocessing. This essential process not only ensures better data quality but also significantly improves the efficiency of your analysis. In this guide, I will introduce a range of powerful Python methods for data preprocessing, equipping you with the tools to optimize your data for … Read more
□ How to use Google Colab for Python (power tool to analyze data)? Last time, I introduced how to mount your Google Drive in Google Colab. This time, I will explain how to set a folder path in Google Colab. First, let’s establish the connection between Google Colab and your Google Drive. The code is … Read more
In this session, using Python, I will draw a normal distribution graph using the actual data I collected. I measured individual grain areas for two wheat genotypes. For Cultivar_A, I measured the area for 1,225 grains and for Cultivar_B, I measured the area for 1,841 grains. Therefore, the total number of grain area data is … Read more
Today, I will explain the meaning of the F-value in testing for significance through statistical processing. Let me give you an example. Suppose we want to determine whether there are differences in the yield according to the varieties (A, B, C). The total experimental unit is 12 (3 varieties x 4 replicates). What would happen … Read more
Google Colaboratory (aka. Colab) is a cloud-based platform that provides a Jupyter notebook environment and therefore users can write and run Python code. You don’t have to install Anaconda to use Jupyter notebook. If you have a google account, simply you can analyze data. Google Colab is a powerful tool for collaborative coding and data … Read more