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Soil microorganisms play an important role in increasing nutrient availability for maize plants through the processes of nitrogen fixation, phosphate solubilization, and humic acid production. These processes not only increase maize productivity but also reduce dependence on synthetic chemical fertilizers, thus supporting agricultural sustainability. This study explores the benefits of microorganisms such as Rhizobium, Azospirillum, Pseudomonas, and arbuscular mycorrhizal fungi in enhancing nutrient uptake, protecting plants from environmental stress, and improving soil quality. Challenges in the application of microorganism technology include adaptation to diverse environmental conditions and low farmer adoption. However, advances in genomic technology and biotechnology open up opportunities to optimize the benefits of soil microorganisms. The implementation of this microorganism-based technology has the potential to support efficient, environmentally friendly and sustainable maize farming.

In Indonesia, maize has replaced rice as the staple food. However, many farmers fail to achieve optimal maize growth rates and yields because the maize planting techniques developed by them depend only on their knowledge and understanding of the relevant sciences relevant to maize planting. To determine the effect of applying different spacing and planting depths on the growth and yield of maize was the objective of this study. A factorial RAK model with two factors was used in this study. There were three levels of planting distance notation (J) in this RAK: 70 x 25 cm for Planting Distance 1, 70 x 40 cm for Planting Distance 2, and 75 x 50 cm for Planting Distance 3. There were also four levels of planting depth notation (K): 3 cm for Depth 1, 5 cm for Depth 2, 7 cm for Depth 3, and 8 cm for Depth 4. The results showed that it could really affect the growth and yield of corn at the correlation of spacing 75 x 50 cm and depth 5 cm. Farm women also contribute to this activity with their experience and skills because the higher the presence of farm women who contribute will make the results of corn farming higher.

Abstract -  Corn plants are one of the plants that are easy to grow and relatively fast to get results but also a plant that is vulnerable to pests and diseases. The symptoms that arise require an expert or agricultural expert to be able to diagnose. Limited time and expert labor is one of the causes of delayed diagnosis, causing a decrease in farmers' yields. This is the basis for making this expert system by adopting knowledge from agricultural experts about the symptoms of corn disease using the Forward Chaining method. To support the research conducted, researchers used the Research and Development (R&D) research method and the design used the Object Oriented Programming (OOP) method using the Unified Modeling Language (UML). Software is built using the PHP programming language, MySQL as a database, and Bootstrap as an interface design with a web-based system.