THE Global Positioning System (GSP) guided tractor senses the exact location of tractor within the field and sends signals to the computer which has a Geographical Information System (GIS), storing the soil nutrient requirement map in it.

The GIS, in consultation with a Decision Support System (DSS) decides the exact requirement of fertilizers for that location. It then commands a variable rate fertilizer applicator to apply the exact dosage at the precise location of farm. All this is done within a second, even before the tractor moves further in the field. This is precision farming (PF) applied in the highly developed parts of the world.

The precision farming versus traditional agriculture: In the PF, farm field is divided into “management zones” based on soil pH, weed mapping, salinity mapping, yield rates, pest infestation, evidence of drought and other factors that affect crop production.

The management decisions are based on the requirements of each zone and precision farming tools (e.g., GPS/GIS) are used to control zone inputs. In traditional farming methods the field is treated as a homogeneous area. Decisions are based on field averages and inputs are applied uniformly.

In precision farming, the management zones with a higher potential for economic return receive more inputs, if needed, than less productive areas and that is why this technology is also called ‘Variable Rate Technology’.

Yield monitors fitted to combine harvesters measure the amount and moisture levels of grains as they are harvested on different parts of a field, generating computer models that guide about the application or timing of inputs to the next crop.

Precision farming: The precision agriculture is the application of modern information technologies towards providing, processing and analyzing the multi-source data of high spatial and temporal resolution for decision-making and operations in the management of crop production. It may be used to improve a field or a farm management from several perspectives:

* Agronomical perspective: Adjustment of cultural practices to take into account the real needs of the crop (e.g., better fertilization management and management of other high-cost inputs).

* Technical perspective: Better time management at the farm level (e.g., planning the activity.

* Environmental perspective: Reduction of agricultural impacts (better estimation of crop fertilizer and agro-chemical needs implying limitation of run-off losses and the preservation/improvement of environment).

* Economical perspective: Increase of the output and/or reduction of the input, increased efficiency of inputs and yield estimation, timely harvest of the crop and better handling of produce.

* Precision farming technology is also useful in evaluating crop inputs, new products, new methods, etc. It can generate production comparisons for a particular field or farm, so that one can take management decisions on the use of inputs, products, and/or methods.

Evaluating these comparisons without precision farming technology is time consuming and often inaccurate. It may also help the farmer set a history of farm practices and results, and in decision making and traceability requirements.

The technology is restricted only to some developed countries. The exact reasons for limited implementation of PF in Asian countries include small land holdings, high-cost technology, heterogeneity of cropping systems, lack of technical expertise and knowledge. In the case of Pakistan, the two major problems are small land holdings and high cost of this technology.

Field scouting is a necessity in precision farming. When scouting, a portable GIS unit allows identifying and recording the location of problems or events that will affect production, including soil differences, insect infestations, fertility deficiencies, and weed problems. Remote sensing, and satellite and infrared images can also be employed while scouting the fields - but they can be time consuming and costly.

Soil testing requires walking through fields to take samples. Testing is based on grid sampling or topography differences, as well as on yield differences indicated by mapping. Agricultural data bases take time to accumulate. For example, because of weather variability, accurate information on site specific yield potential and problems may require several seasons of data.

Retesting soils at the same sites creates data on fertility trends. Information on soil characteristics and weather can be used to plan and improve scheduling of operations, which can increase machinery utilization rates and lower per-acre costs.

The GPS-based guidance systems can allow operators to achieve greater field efficiency under difficult conditions. They can reduce overlap and missed applications of inputs (e.g., spraying), helping fatigued operators maintain higher field efficiency.

In future, the precision technology will help farmers differentiate their production within a particular field. For example, a farmer may segregate higher protein wheat for marketing in more rewarding channels.

In addition, it will allow additional control required for managing the production of differentiated products, as opposed to the production of regular bulk crops. It will allow documentation of crops conditions and control of inputs to meet the requirements of crops. Agriculture is becoming a knowledge-based industry where a farmer knows the factor of profitability. Ownership of precision farming tools has a place in this strategy, but it is not the only option.

For progressive farmers, the least cost learning strategy will be using custom services to build data bases and gain experience with the spatial variability of their fields. With custom services, data ownership will be an issue.

Farmers who plan to use custom services to help build their precision farming data base should have a written contract that specifies their rights to data, and they should take care that the data is available in a format that can be transferred to other software.

For many grain farmers, a yield monitor will be the point of entry to ownership of precision farming tools. Yields are an essential layer in a spatial data base for land. Interpreting and using the yield maps is a key step in developing precision management skills.

Is it profitable: Long-run profitability depends on the development of management systems that link inputs applied with yields harvested on specific sites. These management systems will be a combination of computerized decision support systems and the accumulated wisdom of experienced managers. Decision support systems require data bases. Wisdom comes with long experience. These management systems will be site specific. Generic decision support systems will be developed, but their performance on farm will be enhanced by data from the farm.

History shows that most of the benefits of any new agricultural technology go to the early adaptor. Those who lag are often been forced out. Precision farming is expected to follow the same pattern. Those who begin to accumulate data and experience now will be ready to use improved precision technology as it matures. For it to be profitable, the technology needs to be used in ways that fit local conditions. For crop production, for example, profitability will depend on making the best of low-cost information.

The site-specific data bases will help improve management skills and profitability. The most profitable of this technology are to be found in information system applications, diagnosis of crop problems, equipment use efficiency, risk management, crop differentiation, and process control.

Benefits: Precision agriculture promises higher yields and lower input costs by streamlining the management and reducing the waste and labour costs. It also offers potential to employ less skilled, cheaper, farm machinery operators since theoretically, such systems can simplify and centralize decision-making.

In the future, precision farming will resemble robotic farming as the machinery is designed to operate autonomously, continuously adapting to incoming data. Farmers can share the data and results, and as a consequence costs are cut, yields improved, and the environment is maintained.

Farmers, industry, and universities are partners in developing these better crop “recipes” or can focus the area in which further research is needed.