Data collection methods are specific techniques for acquiring data, while the instrument is a device. Validity in data collection from experiments is mainly achieved through applying principles of experimentation, including choosing a suitable design, randomization, and blocking. It also includes a selection of the most suitable tools and methods, standardizing data collection protocols and procedures, calibrating instruments, and ensuring that laboratories are adequately equipped and managed. Data collection in agronomic experiments is organized into three phases: site characterization, the implementation process, and the harvesting phase. During the site characterization phase, soil sampling and analysis are crucial. This involves collecting soil samples from various locations within the experimental site to assess soil properties, such as nutrient status and texture. Soil analysis is then conducted to evaluate the fertility status of the soil. In the implementation phase, sampling is done at various stages to monitor growth stages and plant health. Alongside this, ongoing soil and plant analyses may be conducted to evaluate nutrient levels and assess responses to treatments. State-of-the-art and efficiently run laboratories are key to maintaining the accuracy and reliability of laboratory results. The harvesting phase measures total yields to assess the effectiveness of the treatments. For legumes, estimating nitrogen fixation is particularly important. Techniques such as isotopic techniques and acetylene reduction assay are used. In screening experiments, lattice designs are commonly used to screen a large number of varieties effectively. Overall, data collection from specific crops depends on the objectives and nature of the crop but mainly includes growth parameters and yield components.