Agriculture in South Asia and South-East Asia regions is under extreme pressure to deliver unprecedented productivity to meet demand, while facing increasing pressures for land and water resources from other sectors. In India, some suggest that agriculture requires a new green revolution to support livelihoods of continued population growth and urbanization. In South East Asia both subsistence and plantation crops are seeing sustained price increases. These are anticipated to continue for at least the medium term. In both cases, agricultural growth must be contained within the same ecological footprint. Land is not available for expansion in many areas. Even where it is, society demands that agriculture should not take more land but improve productivity to produce more from the same or less land and water resources. The only option is to intensify production and this seems easily achievable, through the more intelligent use of existing technologies, and specifically so fertilizers - yields of cereals are currently low to moderate over many areas and efficiency of plantations is highly patchy. The goal is therefore to support intensification of agriculture, which enables it to produce more while not increasing its ecological footprint, or reducing it where and when required.
We propose a small but key role for IPNI – to establish a learning process around analysis of data on fertilizer performance. This will support member companies as they mobilize in response to the call for intensification. Agricultural technologies for intensification are all available. Fertilizer is the mainstay of these, accounting for the lion’s share of input costs and almost half of the response in yields. Yet there seems substantial scope for improvement in the way fertilizer is used. Why is this so? We see the major problem as one of uncertainty. Uncertainty about the size, location and nature of opportunities to intensify prevents intensification. Uncertainty hampers trust-building in supply chains. For suppliers, the problem is that uncertainty reduces the total perceived benefits of fertilizer to users. For buyers, uncertainty compounds the return fertilizers provide to investment. The scale of potential gain to farmers remains enormous. In essence, uncertainty assists no one actor in the supply chain. We will show how to reduce uncertainty by building a learning process around statistical analysis of performance. Data for analysis is provided from a combination of field trials and modeling. This will be accompanied by a process of dialogue to engage actors. Data will be portrayed in map and table format to assist easy interpretation. Dialogue will improve interpretation of data, but also identify where additional analysis is needed. Learning is an on-going process.
Plantation intelligence is organized to reflect the structure of the industry and the different stresses it is under. The oil palm industry is in a growth period, with strong and sustained demand for product. At the same time, it is looking to improve internal processes as it intensifies. Plantation intelligence includes analysis of not just fertilizer performance management but plantation operations under a range of best management practices, which are seen as essential to enable the industry as it adapts to rapidly changing conditions. Yet, fertilizer management will likely remain center stage due to its importance in the intensification process