Research at UAF - Decision Support System for Better Crop Productivity and Environmental Quality
Principal Investigator: Dr. Allah Bakhsh
Designation: Professor;
Department of Irrigation & Drainage; University of Agriculture, Faisalabad.
Telephone:041-9200183; 041-2004235
Fax: 041-9200193;
E-mail: bakhsh_uaf@yahoo.com
Co-PI: Dr. Anwar ul Hassan
Designation: Professor
Department of Soil Science University of Agriculture, Faisalabad.
Telephone: 9200193 ext 2914,
E-mail: anwarulhassan@yahoo.com
Funding Agency: Pakistan Science Foundation
Duration: 01-06-2008 to 31-05-2011
Cost: 1.08 Million

Progress Reports

Weighing of Fertilizer for Split Fertilizer Application

Abstract
Soil characteristics vary from point to point within a field and in turn have impact on the crop yields, water and chemical transport processes in the root zone. Spatial variability effects were recognized based on the wheat yield data analysis and this fact was also pointed out by the technical Reviewer. Low treatment of urea fertilizer @ 30 kg/ac produced maximum yield in terms of 17.71 kg of wheat grain per kg of urea, medium treatment @ 50 kg/ac urea produced wheat grain yield of 17.54 kg wheat grain per kg of urea, and high treatment of 70 kg/ac urea produced wheat grain yield of 13.08 kg per kg of urea. This shows that low treatment was utilized more efficiently, which is being investigated further by applying a wide range of treatments in the ongoing study. This analysis also shows that high treatment was not as much effective as the low and medium treatments showing the scope of precision agriculture practices.

Statement of problem
The current farming practices of uniform applications of agricultural chemical across the fields have resulted in zones of under and over application, which have reduced the chemical use efficiency and have also raised the environmental concerns. Therefore soils within a field need to be treated according to their productivity levels so that water and agricultural chemical use efficiency can be improved based on  the spatial variability effects. Precision agricultural practices based on the soil productivity and the related attributes have the potential to increase farmer’s income by applying the variable rate technology and applying the site-specific agricultural inputs. Under this scenario, there is a need to conduct research on agriculture issues and provide information about the soil attributes to asses the soil productivity and also guide the farmers about the use of site-specific agricultural inputs such as tillage, water and agro-chemicals to increase net returns of the farming community.

Objectives

  • Develop and integrate the GIS data layers of elevation, sand, silt, clay fractions, soil type, pH, organic matter, soil nutrients, and crop yields data to establish the cause-effect relationship for explaining the spatial variability in yield patterns.
  • Develop a Decision Support System within a GIS environment to assess the productivity potential of the various soil zones delineated on the basis of the soil properties and crop yield data.
  • Use the Decision Support System to help farmers apply agricultural inputs more efficiently and promote the sustainable irrigated agricultural practices.  

Methodology 
A piece of land of 25 acres has been selected at the Postgraduate Agricultural Research Station (PARS) of the University of Agriculture, Faisalabad, which is located in Rachna Doab (land between rivers Chenab and Ravi), with coordinates of 310 N and 73o E .

Field Layout and Land Preparation
The study area consists of 5 blocks and each block of 5 acres (figure. 1 below).

 

Crop Variability Assessment in consultation with other experts

Treatments:
T1 = High (Urea 70 Kg/acre)
T2 = Medium (Urea 50 Kg/acre)
T3 = Low (Urea 30 Kg/acre)
T4 = Control (No urea application)
Figure 1 Experimental layout of treatments
Four treatments were designed keeping in view the common rate of fertilizer application by the farmers, designated as the medium treatment (Urea @ 50 kg/acre) while the other two treatments were; low treatment (Urea @ 30 kg/acre); the high treatments (Urea @70kg/acre) and the control treatment, which received no fertilizer application. The treatments were applied to the experimental units, each of 0.4 acre (220 x 80 ft) in size. Each treatment was replicated 3 times in each block and the total number of replications was 60 having 12 experimental plots in each block for 4 treatments. Disc plough was used for primary tillage operation then cultivator was used for secondary operation and finally planker was used. Wheat sowing was performed using wheat drill, details are given in the annual report.

Total experimental area   = 24.36 acre or 10 ha (96480 m2 )
Total number of experimental plots  = 60    
Plot size = 24 m x 67m   (220 x 80 ft)

Conclusions:

  •  The high treatment T1 produced the maximum yield of 3656 kg/ha, which is 3 % higher than that of T2, which is 35 % higher than yield produced by T3 and 162 % more than that of T4 (control, No urea application). The treatment T2 produced the yield of 3561 kg/ha, which is 32 % higher than T3 and 155 % more than T4.
  • The high treatment T1, produced the maximum yield which is 2.62 times more than T4, 1.35 times more than T3 and almost equivalent to T2, showing no effect of high treatment compared with medium treatment on wheat yield for this study area.
  • The medium treatment T2 produced yield of 3561 kg/ha which was 2.55 times more than T4, and 1.31 times more than T3.
  • The low treatment, T3 produced yield of 2707 kg/ha which was 1.94 times, almost double than T4 treatment.
  • The medium treatment T3 produced maximum yield 17.71 kg per kg of fertilizer, T2 produced 17.54 kg yield per kg of fertilizer, where as T1 produced 13.08 kg per kg of fertilizer.
  • T1 treatment (Urea@ 70kg/acre) was not much effective in increasing the yield and needs further careful investigation. 
  • Both GIS and statistical analysis revealed that areas having higher yield were influenced by soil, topography and treatments levels.

Recommendations:

  • Fertilizer should be applied according to the potential of the soil
  • Stable yield patterns can be used to divide the fields in to equal potential management zones for application of the variable rate inputs.
  • GIS has the potential to study the combined effects of landscape, topography and yield.