Precision Farming or Precision Agriculture is generally defined as information and technology based farm management system to identify, analyse and manage spatial and temporal variability within fields for optimum productivity and profitability, sustainability and protection of the land resource by minimizing the production costs. Increasing environmental consciousness of the general public is necessitating us to modify agricultural management practices for sustainable conservation of natural resources such as water, air and soil quality, while staying economically profitable. The use of inputs (i.e. chemical fertilizers and pesticides) based on the right quantity, at the right time, and in the right place. This type of management is commonly known as "Site-Specific Management". The productivity gain in global food supply have increasingly relied on expansion of irrigation schemes over recent decades, with more than a third of the world's food now requiring irrigation for production. All-together, market-based global competition in agricultural products is challenging economic viability of the traditional agricultural systems, and requires the development of new and dynamic production systems.

An experiment was conducted to study the yield response of salad cucumber under different drip irrigation levels to determine the most suitable irrigation requirement for salad cucumber grown under naturally ventilated polyhouse. Drip irrigation applied at the rate of 2 litre plant-1 day-1 to the control plants was reduced by 5, 20, 35 and 50% by applying corresponding irrigation rates of 1.9, 1.6, 1.3 and 1 litre plant-1 day-1 under different treatments. Lowering irrigation level to 65% sustained the production and increased water use efficiency without decreasing the yield of cucumber. However, irrigation level of less than 65% reduced the yield without increasing water use efficiency. The maximum fruit number (49), fruit weight (7.194 kg plant-1) and fruit yield (88.8 t ha-1) were obtained from drip irrigation level of 65% (1.3 litre plant-1 day-1) and the lowest fruit number (35), fruit weight (5.043 kg plant-1) and fruit yield (62.26 t ha-1) from drip irrigation level of 50% (1 litre plant-1 day-1), with the lowest water application rate. Irrigation treatments had significant effects (P < 0.05) on yield. However, interaction within groups was found to be non significant. There were significant positive correlations (P < 0.01) between fruit number, fruit weight and fruit yield. The total quantity of water applied through 65% drip irrigation level was 144.4 mm and which showed 35 per cent water saving over control with highest water use efficiency (6148.31 kg ha-1 cm-1) and Benefit Cost (BC) ratio (3.41).

No abstract

Excessive application of fertilizers can cause wastage of fertilizer which increases input cost and environmental pollution. Implementation of Precision Agriculture through site specific nutrient management is the best suitable solution to increase nutrient application efficiency and thereby increase crop productivity. The present study was carried out in the Instructional Farm of KCAET campus, Tavanur, Malappuram, Kerala, to access the spatial variability of different soil chemical properties. The methodology follows the delineation of the study area, location of sampling points and soil samples were collected and analysed for the soil chemical properties such as pH, Electric Conductivity, Available Nitrogen, Available Phosphorous, Available Potassium, Boron and Sulphur using standard methods. Spatial variability maps of soil chemical properties were prepared by using Inverse Distance Weighing method of interpolation in ArcGIS. From this study, it could be concluded that, GIS along with GPS could be used as an effective tool for preparation of spatial variability maps for determining the spatial distribution of chemical properties of soils and thereby helps to achieve site specific nutrient recommendation which improves crop productivity, quality and reduce environmental stress. It also involves a lesser number of soil analysis and thus reduces the cost of operation compared to plot-to-plot analysis.

No abstract