Oil palm is of significant importance for our everyday life convenience. However, continuous expansion of oil palm plantations for the sake of better yield performance raises extensive concerns for the natural environment. According to the research article, deforestation is the major issue that continues to negatively impact the industry within Indonesia with approximately half a million hectares lost every subsequent year (ASEAN, 2018). AI technology in smart agriculture becomes an efficient solution to have a sustainable agricultural practice and strive for human-nature balance.
A thorough young oil palm health monitoring in the early stage is important for the plantation productivity. Based on the yellowish crown detection result, the AI-analytics system can suggest appropriate measures, such as a targeted fertilizer application, pest and disease management, or other interventions to address the underlying causes of the yellowish crown and improve the young tree health. Count of the young/immature tree population helps you to understand the survival rate and decide if some other actions are needed.
Besides, etiolation can occur in young plantations where plants may not receive adequate sunlight or nutrients due to dense shade or insufficient sunlight. If the existing issues cannot be detected in time, land owners and managers may apply more fertilizers to the whole plantation area. However, those fertilizers cannot have the effects as what the land owners expect but become a waste for the poor health of trees.
Anavision Smart Oil Palm Intelligence (SOPI) AI-analytics will greatly help you to adapt proper measures based on local conditions. The count of young or immature tree population helps you to understand the survival rate of current planted oil palm states to see any interventions to maintain good health across the plantation. To prevent the etiolation caused by the lack of light exposure due to the large leaf covered one another on the plantation, ‘Planting Distance Measurement’ and ‘Blank Spot Analysis’ keep an eye on the planted condition of current land use and plan for better layout strategy to reduce the land resource waste.
Figure 1. Generated image to show when SOPI detects the yellowish crown (oil palm with symptoms)
The application of SOPI will empower farmers and plantation managers with data-driven insights to make informed decisions, contributing to long-term viability and responsible growth of the oil palm industry. The well-trained AI model can extract relevant colors from aerial images of your plantation to identify presence of crowns with symptoms. SOPI’s oil palm health monitoring adopts yellowish crowns as oil palm with symptoms to enable agronomists take a deeper look at the issues, see if it is by a pest/disease infestation or nutrient deficiency and take actions for improvements. ‘Planting Distance Measurement’ and ‘Blank Spot Analysis’ play an important role in better planting layout for the land use. This is aimed to make every tree have equal access to nutrition and sunlight for healthy growth.
It’s important to note that the oil palm industry faces challenges related to environmental sustainability, deforestation, land use conflicts. Balancing the economic benefits with sustainable practices and responsible production is crucial to ensure the long-term viability and positive impact of the oil palm industry.
Figure 2. The process of how SOPI manages oil palm plantation
Feel free to visit our website for SOPI detailed information: https://anavision.com/deep-learning-based-smart-oil-palm/
Reference:
- Aseansc. (2019, May 12). ASEANSC. ASEAN Studies Center Universitas Gadjah Mada. https://asc.fisipol.ugm.ac.id/2018/12/21/challenges-indonesias-palm-oil-industry-overview/
