Stories about crops and statistics (plus coding)
JK Here I have one dataset. I want to predict grain weight using grain dimension data such as length, width, and area, and identify the best prediction model for estimating grain weight. As a result, I developed the following models. and I’ll calculate Log-likelihood for each model. To do that, I need to know each model … Read more
Principal Component Analysis (PCA) is a statistical technique used for dimensionality reduction while preserving as much variability in the data as possible. It transforms the original variables in a dataset into a new set of uncorrelated variables called principal components, ordered by the amount of variance they capture from the original dataset. Here’s the step … Read more
Mean Absolute Error (MAE) is a metric used to measure the accuracy of a model’s predictions. It calculates the average magnitude of the errors in a set of predictions, without considering their direction. In other words, MAE measures the average absolute difference between the actual values and the predicted values. MAE is typically used in … Read more
■ [R package] Normalization Methods for Data Scaling (Feat. normtools) In my previous post, I introduced the R package normtools(), which I developed to normalize data using various methods. This time, I’ll demonstrate how to use the R package normtools() for data normalization. 1. Data upload This data includes kernel number (KN), average kernel weight … Read more
The damage to sorghum grain can result from a variety of causes, including environmental, biological, and mechanical factors. Here are some common causes: 1. Excessive Rainfall and Humidity 2. Pest Infestation 3. Temperature Stress 4. Mechanical Damage During Harvest 5. Soil Conditions 6. Delayed Harvest 7. Post-Harvest Factors To minimize sorghum grain damage, it is … Read more
Llama 3, or Large Language Model Meta AI 3, is an advanced iteration of Meta’s language models, designed to facilitate a wide array of natural language processing tasks with enhanced capabilities. This model leverages state-of-the-art techniques in deep learning and transformer architectures, providing improved performance in text generation, comprehension, and contextual awareness. We can install … Read more
■ [Data article] Data Normalization Techniques: Excel and R as the Initial Steps in Machine Learning In my previous post, I explained how to normalize data using various methods and demonstrated how to perform the calculations for each method. To simplify these calculations, I recently developed an R package that easily generates normalized data. 1. … 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
■ Python GIS: Interpolating and Plotting Corn Grain Yield Data In my previous post, I explained how to create a GIS map using Python. Today, I’ll introduce how to create the same GIS map using R. First, let’s install all the required packages. and I’ll upload a dataset for practice. Next, I’ll extract columns for … Read more
I want to create a normal distribution graph with a specific variance. First, it’s necessary to create the data. I’ll generate data with a mean of 100 and a variance of 100 (which means the standard deviation is 10). However, it’s important to establish a range. To do this, I’ll set up a range of … Read more
Growing Degree Days (GDDs) are a measure of heat accumulation used to predict crop development rates such as the growth of crops. The GDDs are calculated to provide a simple model to estimate the growth and development of plants, especially crops, based on the daily temperature. To calculate GDDs, the base temperature for each crop … Read more
These days, image analysis equipment can easily provide grain area measurements (mm²), and the large datasets acquired instantly from this equipment offer more insights into wheat grains. While grain weight can be a good indicator of wheat yield, obtaining data on grain weight is challenging with the available equipment. Currently, average grain weight is calculated … Read more
■ Introduction ■ What is Probability Density Function (PDF) and Cumulative Distribution Function (CDF): How to calculate using Excel and R? In my previous post, I explained what the Probability Density Function (PDF) and the Cumulative Distribution Function (CDF) are. I also explained the formula for the PDF and demonstrated how to manually calculate it in Excel. … Read more
■ What is Finlay-Wilkinson Regression Model? In my previous post, I introduced what Finlay-Wilkinson Regression Model is and how to calculate adaptability (or stability). Actually, adaptability and stability are opposite concept with the same data. Have you ever heard heritability (h2)? Heritability is a key concept in genetics and breeding that measures how much of … 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 predicted grain weight from length and width of grains using Random Forest. ■ Machine Learning: Predicting Values with Multiple Models- Part I Now, my next question is how the model accuracy changes when grain area and genotype are added. If you followed my previous post closely, you should be able … Read more
Machine learning (ML) is a field of artificial intelligence (AI) that enables computers to learn from and make predictions or decisions based on data. Rather than being explicitly programmed to perform a specific task, ML algorithms use data to identify patterns and make inferences or predictions. Machine Learning can be divided into supervised and unsupervised … Read more
Machine learning (ML) is a field of artificial intelligence (AI) that enables computers to learn from and make predictions or decisions based on data. Rather than being explicitly programmed to perform a specific task, ML algorithms use data to identify patterns and make inferences or predictions. What is Classification in Machine Learning? Classification is a … Read more
Sorghum panicle de-graining is an experimental technique used to study grain size and assimilate availability. De-graining is used to artificially increase assimilate availability to the remaining grains by removing a portion of the panicle. Typically, researchers remove the top half of selected panicles at anthesis (flowering stage). This is done before significant grain development has occurred. … Read more
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 … Read more
Soybean growth is divided into two main phases: Vegetative (V) stages and Reproductive (R) stages. The vegetative stages are characterized by leaf and node development, while the reproductive stages begin with flowering and include pod development, seed development, and plant maturation. The reproductive stage R1, also known as the beginning bloom stage, is defined as having … Read more
■ Unit conversion □ Area Acre ha m2 ft2 Acre 1 0.404686 4,046.86 43,560 ha 2.47105 1 10,000 107,639 m2 0.000247105 0.0001 1 10.7639 ft2 0.000022956 0.00000929 0.092903 1 □ Weight lbs kg lbs 1 0.453592 kg 2.20462 1 bushel [corn] 56 56 * 0.453592 = 25.4 bushel [wheat] 60 60 * 0.453592 = 27.2 bushel … Read more
Kim, J., Savin, R. and Slafer, G.A., 2021. Weight of individual wheat grains estimated from high-throughput digital images of grain area. European Journal of Agronomy, 124, p.126237. https://www.sciencedirect.com/science/article/pii/S1161030121000095 ■ Context and Objective This study focuses on estimating the weight of individual wheat grains using high-throughput digital images of grain area. Given the importance of average … Read more
Photoperiodicity refers to the response of plants to the relative lengths of day and night, which regulates their growth and flowering. It is an important factor in agriculture as it allows growers to optimize crop yields and quality by understanding and manipulating the photoperiod requirements of different plant species. In terms of photoperiodicity, plants can … Read more
Understanding the difference between autotrophic and heterotrophic respiration is crucial in crop science. These processes play a vital role in the carbon cycle and have significant implications for carbon emissions, climate change, and sustainable agriculture. 1. Autotrophic Respiration Autotrophic respiration is the process by which plants convert the carbohydrates produced during photosynthesis into energy. This … Read more
Identifying the vegetative growth stages of soybean is crucial for effective crop management. These stages are marked by the development of trifoliolate leaves, which are a key indicator starting from the V1 stage. Here’s a brief guide on how to recognize these stages: ■ Emergence (VE) The first stage is emergence (VE), where the soybean … 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
I’ll create one data. In genotype D, yield data was missed, so it was indicated as NA. Now I’ll calculate the mean of total yield across all genotypes. As you see above, we can’t calculate the mean dud to NA. To obtain the mean of total yield, we should exclude NA. Using subset(), we can … 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