A SOFTWARE TOOL FOR SOIL INFORMATION MANAGEMENT. Eswara Rao Pinapothu

Transcription

1 A SOFTWARE TOOL FOR SOIL INFORMATION MANAGEMENT Eswara Rao Pinapothu Problem Report submitted to the College of Engineering and Mineral Resources At West Virginia University In partial fulfillment of requirements For the degree of Master of Science In Industrial Engineering Rashpal S. Ahluwalia, Ph.D Feng Yang, Ph.D James Gorman, Ph.D Department of Industrial and Management Systems Engineering Morgantown, West Virginia 2012 Keywords: Soil, Soil Testing, Soil Nutrients, Fertilizer, Aglime, Visual C#, MS Access

2 ABSTRACT West Virginia University has a soil testing laboratory located in the Division of Plant and Soil Sciences, Davis College of Agriculture, Natural Resources and Design. The mission of this laboratory is to provide basic soil fertility analysis. Presently, the laboratory processes approximately 10,000 soil samples per year, at no cost to West Virginia residents. It provides recommendations on how much Aglime and fertilizer (Nitrogen, Phosphate, and Potash) to use by testing the ph and nutrient values of the soil. The main drawback of the soil testing laboratory is that its software is MS-DOS based, which is not compatible with modern computers and it is not user friendly. This project developed a visual C# based software tool to generate soil testing reports. The report is created as an MS-Word document file which can be printed and mailed to a customer or sent electronically. The software uses MS Access to store sample data and test results. Soil testing personnel can search the database and generate several queries. The new software tool is user friendly and provides features that the current software lacks.

3 ACKNOWLEDGEMENTS This problem report is accomplished successfully with the assistance of many individuals. I would like to emphasize gratitude to my committee chairman, Dr. Rashpal Ahluwalia. I greatly appreciate his support, patience, and perseverance to finish this problem report on time. I express gratitude to my committee member Dr. James Gorman and Dr. Feng Yang for their constructive comments to accomplish the software tool successfully. I would like to extend gratefulness to all my committee members for serving on my committee and for their valuable suggestions. Above all, I would like to express gratitude to my parents, sisters and my relatives for their unconditional love and endless support during all phases of my life. I will be forever indebted to them. I would like to thank my friend Kartheek who motivated me to initiate this project. I would also like to greatly appreciate my friend Bhaskar Charan s support in designing and completing the software tool. I will be deeply thankful to my friend Mohita, for her time and support to complete this report. I would like to thank my close pals Deep and Jagadish who guided me not only in my academics but also through various projects during both my Bachelors & Masters degree. I would also like to thank my buddy Savan who inspired me during the course of Masters Program. I am very much grateful to all my friends Krishna, Jyothi, Spoorthi, Radhika, Raghu, Srikanth, Charan, and Naveen who made my life at Morgantown, WV more eventful, joyful, and most memorable. I thank my very dear friends Balaji, Vindhya, Chandralekha, Sekhar, and Spoorthy for being in my life. I cannot imagine my life without them. Finally, I would also like to express my deepest gratitude to my Mother Nagamani and my dear friends Preethi and Pravallika who were no more in this world. iii

4 TABLE OF CONTENTS ABSTRACT... ii ACKNOWLEDGEMENTS... iii LIST OF FIGURES... vii LIST OF TABLES... viii LIST OF ACRONYMS... x Chapter 1: Introduction Soil Soil Nutrients Soil Testing West Virginia University Soil Testing Laboratory and its Report Tool Problem Statement Methodology...4 Chapter 2: Literature Review History and Development of Soil Testing Soil Testing Approaches... 7 Chapter 3: Soil Testing Report Data Description Input Data Customer or Landowner Details Data Soil Sample Data Provided by the Customer Sample Tested Values Data Recommendations Nutrient Levels Soil ph Lime Requirement Cation Exchange Capacity Percent Base Saturation Methodology to Calculate Recommendation Values Nitrogen Recommended Values for Different Type of Crops iv

5 3.4.2 Phosphate (P2O5) Recommended Values for Different Type of Crops Potash Aglime Chapter 4: System Design Database System Database Database Management System (DBMS) Database Applications Microsoft Access: Database Tables Creating Tables in Datasheet View Creating Tables in Design View Tables used in the Soil Analysis Report Tool CUSTOMERS table ORDERS table TEXTURE table TILLAGE table STATE table COUNTY table CROP table Entity-Relationship Diagram NET Technology NET Framework Visual C#.NET Programming language Visual Studios IDE Windows Windows Form and Controls Database Connectivity with ADO.NET Connection Object Table Adapter Object Dataset Object Data Binding v

6 Chapter 5: User Interface Design Soil Data Recommendations Search Soil Analysis Report Chapter 6: Conclusion and Future Work Conclusion Future Work APPENDIX A: Old Software Recommendation Sheet APPENDIX B: Source Code REFERENCES vi

7 LIST OF FIGURES Figure 1.1: Soil components (Source physicalgeography.net)...1 Figure 2.1: Number of soil samples analyzed from Figure 2.2: Conceptual relationship between soil nutrients and plant response...8 Figure 2.3: Nutrient application rates for different soil fertility levels...9 Figure 4.1: The components of database system...29 Figure 4.2: Datasheet view...31 Figure 4.3: Tables used in this application...32 Figure 4.4: Entity - Relationship diagram...36 Figure 4.5:.NET architecture...37 Figure 4.6: Controls architecture...38 Figure 5.1: Main form...42 Figure 5.2: Soil data form...43 Figure 5.3: Recommendations form...44 Figure 5.4: Search form...45 Figure 5.5: Soil analysis report...46 vii

8 LIST OF TABLES Table 1.1 : Types of soil texture...1 Table 1.2 : Soil macro nutrients...2 Table 1.3 : Soil micro nutrients...2 Table 3.1 : Crop codes...11 Table 3.2 : Phosphorus levels in lbs/acre...12 Table 3.3 : Potassium levels in lbs/acre...12 Table 3.4 : Calcium levels in lbs/acre...12 Table 3.5 : Magnesium levels in lbs/acre...13 Table 3.6 : ph levels...3 Table 3.7 : Ranges and recommended ph for optimal growth of some of the field crops...13 Table 3.8 : Recommended Nitrogen values for different crops...16 Table 3.9 : Recommended Phosphate values for different crops...17 Table 3.10: Recommended Potash values for different crops...18 Table 3.11: Recommended Aglime values for crop code Table 3.12: Recommended Aglime values for crop code Table 3.13: Recommended Aglime values for crop code Table 3.14: Recommended Aglime values for crop code Table 3.15: Recommended Aglime values for crop code Table 3.16: Recommended Aglime values for crop code Table 3.17: Recommended Aglime values for crop code Table 3.18: Recommended Aglime values for crop code Table 3.19: Recommended Aglime values for crop code Table 3.12: Recommended Aglime values for crop code Table 3.21: Recommended Aglime values for crop code Table 3.22: Recommended Aglime values for crop code Table 3.23: Recommended Aglime values for crop code Table 3.24: Recommended Aglime values for crop code Table 3.25: Recommended Aglime values for crop code Table 3.26: Recommended Aglime values for crop code Table 3.27: Recommended Aglime values for crop code Table 3.28: Recommended Aglime values for crop code viii

9 Table 4.1: CUSTOMERS table...33 Table 4.2: ORDERS table...33 Table 4.3: TEXTURE table...34 Table 4.4: TILLAGE table...34 Table 4.5: STATE table...34 Table 4.6: COUNTY table...35 Table 4.7: CROP table...35 ix

10 LIST OF ACRONYMS GUI CEC K Ca Mg H Total K Ca Mg H Aglime T/A IDE N/A SIM Graphical User Interface Cation Exchange Capacity Milliequivalent of potassium (K) Milliequivalent of calcium (Ca) Milliequivalent of magnesium (Mg) Milliequivalent of hydrogen (H) Total percent base saturation Potassium percent base saturation Calcium percent base saturation Magnesium percent base saturation Hydrogen percent base saturation Agricultural lime Tons/ Acre Integrated Development Environment Not Applicable Soil Information Management x

11 Chapter 1: Introduction 1.1 Soil Soil is the most important component for the growth of plants and micro organisms. Soil supports life and also acts as the medium of growth. Soil is composed of broken rock particles that have been transformed due to climatic and environment conditions. Basic components of soil are air, water, mineral particles, and organic constituents with detailed percentages are shown in Figure 1.1 [1]. Figure 1.1: Soil components (Source: physicalgeography.net) [1] Soil texture is the relativee proportion of sand, silt and clay size particles in the soil. The different combinations of soil textures are shown in Table 1.1. The nutrient levels maintained in the soil are affected by the kind of soil texture. Table 1.1: Types of Soil Texture 1 Clay 2 Sandy Clay 3 Silty Clay 4 Sandy Clay Loam 5 Clay Loam 6 Silty Clay Loam Sandy Loam Loam Silty Loam Loamy Sand Sand Others 1

12 1.2 Soil Nutrients Amount of nutrients in the soil are the most critical factor that influence the growth of plants. Plants absorb these nutrients through water once they are dissolved. There might not be adequate amount of nutrients available in the soil for the healthy plant growth. This is an important reason to use fertilizers. Fertilizers balance the level of nutrients available to the plants [2]. Soil nutrients are categorized into two types: macro and micro nutrients as shown in Table 1.2 and Table 1.3. Macro nutrients are subdivided into two groups: primary and secondary nutrients. The primary nutrients are Nitrogen (N), Phosphorus (P), and Potassium (K). Due to the large consumption of these nutrients by the plants, they are generally lacking in the soil. The secondary nutrients are Calcium (Ca), Magnesium (Mg) and Sulfur (S). There are generally enough of these nutrients available in the soil, so fertilizers are not always needed. Micro nutrients are Boron (B), Copper (Cu), Iron (Fe), Chloride (CI), Manganese (Mn), Molybdenum (Mo) and Zinc (Zn). These elements are essential for plant growth but are needed in very little quantities [2]. The soil nutrients values can be measured through the soil testing process. 3 Sulfur (S) 1.3 Soil Testing Table 1.2: Macro Nutrients Primary 1 Nitrogen (N) 2 Phosphorus (P) 3 Potassium (K) Secondary 1 Calcium (Ca) 2 Magnesium (Mg) Table 1.3: Micro Nutrients 1 Boron (B) 2 Copper (Cu) 3 Iron (Fe) 4 Chloride (Cl) 5 Manganese (Mn) 6 Molybdenum (Mo) 7 Zinc (Zn) Soil Testing is a process of measuring the macro and micro nutrients in the soil. It could be an easy and cost effective way to manage agronomic soils. Soils testing nutrient values are very important for plant growth by providing the best recommendations of the amounts of fertilizers and agricultural limestone to be used. Analysis of nutrient levels and ph levels, is used to make the best choice when recommending fertilizers and other nutrients. Some of the advantages of soil testing are [3]: 2

13 Encourages plant growth by providing the best recommendations of Aglime and fertilizer quantities to be used Diagnoses of soil nutrients provides the information on whether or not there are sufficient nutrients available in the soil Saves money by not spending on unessential lime and fertilizers Promotes environmental quality 1.4 West Virginia University Soil Testing Laboratory and its Report Tool The West Virginia University soil testing laboratory is located in the Division of Plant and Soil Sciences, Davis College of Agriculture, Natural Resources and Design. The mission of this laboratory is to provide basic soil fertility analysis for customers. Presently, the laboratory processes approximately 10,000 soil samples per year at no cost to West Virginia residents. It uses MS-DOS based soil testing software to generate recommendations on the amount of Aglime and fertilizer (Nitrogen, Phosphate, and Potash) by using the ph and nutrient values that are obtained after testing the soil. These recommendations depend upon the soil area, the crops they are growing, and soil nutrient contents. West Virginia University soil testing report tool uses different codes for different crops. It considers two soil tillage methods: conventional and no-till. The inputs of the tool are: customer details [first name, last name, street, city, state, county, and phone], sample details [Lab ID, sample received date, sample ID, previous crop, soil name, texture, cost sharing, acres, tillage method, and crop code] and sample nutrient values [lime, ph, phosphorus, potassium, calcium, and magnesium]. Using these inputs, the tool generates a recommendations output sheet consisting of the amount of fertilizer and Aglime to be used in tons per acre. It also gives the amount and range of nutrients values available in the given soil sample [4]. The current input and report format are shown in Appendix A and B, respectively. The main drawbacks of the current tool are: The tool is MS-DOS based, which is not compatible with modern computers Developed in mid 80 s, it is not user friendly and the Graphical User Interface (GUI) is hard and troublesome to use Similar data needs to be re-entered (For example, multiple samples from the same customer require multiple entries of customer name and address) 3

14 1.5 Problem Statement The Division of Plant and Soil Sciences, Davis College of Agriculture, Natural Resources and Design at West Virginia University analyzes soil samples sent by citizens of West Virginia and surrounding states. The soil samples are analyzed for their ph value and also for major nutrients like Calcium, Magnesium, Potassium and Phosphorous. Recommendations are then made on the amount of Aglime and fertilizer (Nitrogen, Phosphate, and Potash) that should be applied to the sampled area. The recommendations depend on the factors like amount of nutrients available in the soil, intended crop and soil history. The ph and nutrient values that are obtained by the soil analysis are entered into computer software called West Virginia University Soil Test Report, which recommends the amount of Aglime and fertilizer (Nitrogen, Phosphate, and Potash) that should be applied to the sampled area. Data provided by the customer is combined with laboratory results of the sample soil are used to create a computerized soil test report that shows soil test results and nutrient recommendations. The West Virginia University Soil Test Report tool was developed in the mid 80 s and is not user friendly and the Graphical User Interface (GUI) is hard and troublesome to use. To rectify the drawbacks of the current tool, a Visual C# tool is developed for efficient handling of data, friendly user graphic interface and to cut down on repetitive processes involved in entering the data. This tool also provides the user an option to search customer details and conduct variety of queries. 1.6 Methodology To generate recommendations for fertilizer and Aglime after soil testing, a windows based application tool is designed using Visual C#.NET as front-end and MS Access as backend. A.NET database application is the connectivity between a database and the controls on Windows Forms. This connectivity is bridged by ActiveX Data Objects.NET (ADO.NET). ADO.NET is a collection of objects (classes) that are designed to support data access and data manipulation [5]. This project is aimed at developing a database application that allows users to modify data in a Data Base Management System (DBMS) of soil information through a user-friendly 4

15 interface. A Graphical User Interface (GUI) is developed around the soil database and users are allowed to view and potentially modify the data. The procedure to develop this database application was divided into several top-level processes [5]: 1) Connecting to the database 2) Fetching data using database queries 3) Displaying data on Windows forms 4) Editing data in the application 5) Saving data back in the database 6) Visual C# coding to calculate the recommendations 7) Pulling data to display recommendation sheet 8) Take a print out or make a file of the recommendation sheet 5

16 Chapter 2: Literature Review 2.1 History and Development of Soil Testing The history and development of soil testing are considered in three periods: , , and [6]. During the period of , the first records of soil testing analysis was that of Daubeny in England in 1845 [6]. In that test period, the words active and dormant were used to express the more and less soluble nutrient constituents of a soil respectively and carbonate water solvent was used for extracting the active portion of soil. During this time frame, Liebig, Hilgard and Dyer proposed different methods to determine the soil conditions to suggest fertilizers to the land [6]. The second period , mainly focused on the fundamental chemical composition of soils as related to crop production. The third period , struggled for developing new methods which could be applied universally and to adjust with chemical procedures for specific soil conditions [6]. Soil testing is being used since late 1940 s in USA [7]. Initially, soil tests were developed to specify whether the fertilizer was needed or not. In the early 1960 s, it was estimated that farmers were spending 10-20% of their gross incomes on fertilizers and lime [8]. They needed to know exactly how much, when and where the fertilizers should to be applied in order to reduce the amount spent on fertilizers and lime. Since soil testing gives the exact information, people increased the use of it to increase their benefits. Due to excellent results of soil testing, the number of people using testing of soil samples for their fields has been increasing tremendously. North Carolina statistics of number of soil samples analyzed for different years for the period are shown in Figure 2.1 [8]. 6

17 Figure 2.1: Number of Soil Samples Analyzed from Every state in the United States has several soil testing laboratories which provide recommendations for the soil samples. Some of these laboratories are at state universities with an aim to serve farm landowners. The universities which conduct research on soil testing analysis have soil testing laboratories to test the samples in order to generate recommendations for fertilizers and Aglime for different crops. Laboratories implement different approaches in order to get recommendations using a computerized model. 2.2 Soil Testing Approaches West Virginia University uses an approach which was described in a guide written by Devinder to understand clearly how the WVU soil testing report tool works [4]. This guide helps the landowners to understand the soil testing report and make the results more useful in their farming operations. In this guide, soil testing report is divided into three sections: 1) Soil sampling 2) Laboratory analysis, and 3) Results and recommendations for soil fertility management 7

18 The first section of the soil testing report is soil sampling which gives details of soil sample or soil location. This information contains field name or number, field size, soil texture, tillage method, liming history, and previous crop in the field. The second section of the soil testing report is laboratory analysis which contains the information of soil ph, potassium, calcium, magnesium, phosphorus, cation exchange capacity, base saturation, and lime requirement. Nutrient values of the soil are extracted by a mixture of sulfuric and hydrochloric acid which are expressed in pounds per acre. These values are categorized into: Low, Med, High and Very High. These nutrient values for a given sample depend upon the method used to extract. Nutrient values can be different if different extraction methods are used. The third section of soil testing report is the results and recommendations. The results for fertilizer and agricultural limestone are expressed in lbs/acre and tons/acre respectively. Recommendations for phosphate and potash are based on soil testing but not nitrogen. It is based upon expected crop yields in the field. Joseph categorized relative fertility levels into three divisions: below optimum, optimum and above optimum [9]. Below optimum is divided into subgroups: very low, low, and medium. A conceptual relationship between soil nutrients and plant response given by Joseph is shown in Figure 2.2. Figure 2.2: Conceptual relationship between soil nutrients and plant response [9] 8

19 It was also mentioned that if the soil fertility categories falls below optimum, the recommendations for nutrients for a specific crop should be made to achieve its complete yield and should be able to build the soil fertility level into the optimum range overtime. If the soil fertility level is below optimum, the recommendations are designed to replace the removed amount of nutrients to bring back to the optimum level. If the soil nutrient level is above optimum, then it is better not to recommend nutrients for that particular soil as they will bring the nutrient level down to optimum level. This can be seen in Figure 2.3 [9]. Figure 2.3: Nutrient application rates for different soil fertility levels [9] The University of Vermont uses modified Morgan s solution to analyze the soil nutrients for its soil testing [10]. They made some changes in nutrient recommendations which have better results for the crop growth. Soil labs can get different results and different recommendations for the same sample of the soil because of the different chemical extracting methods used. But there is a possibility of multiple correlations existing between any two methods for different soils or soil conditions [11]. The important reasons for the differences are: 1) The type of equipments or tools used to detect the nutrients in extracting 2) The quality and techniques used by the lab employees 3) The method of reporting the results 4) Also based on crop response in relation to soil types and climate within regions 9

20 Chapter 3: Soil Testing Report 3.1 Data Description In general, a soil testing system requires soil and crops data from the landowner or customer. The input data used to develop this tool is divided into three categories as shown below: 1) The customer or landowner details 2) Soil sample details which are provided by the customer and the soil data 3) The output data i.e., the Aglime and fertilizer recommendations are calculated. 3.2 Input Data Customer or Landowner Details Data Customer or landowner details are the name and address of the customer which are a part of the inputs required for the tool. They are First Name, Last Name, Street, County, City, State, and Phone number Soil Sample Data Provided by the Customer Soil sample details are essential input data which helps the tool to display detailed information of the soil sample in the recommendation section. They are Lab ID, Sample received date, Sample ID, Previous crop, Soil name, Texture, FSA cost sharing, Acres or square foot, Tillage method and Crop code. The definitions of these terms are as follows: 1) Lab ID is the sample identification number which is assigned by the lab operator 2) Sample receive date is the date when the sample was received 3) Sample ID is the sample identification number assigned by customer in order to recognize his soil samples 4) Previous crop is the crop that was grown in the area where the sample was collected 5) Soil name is the name of soil given by the customer 6) The relative proportions of sand, silt, and clay size particle is called soil texture. The different combinations of soil texture are described in Table 1.1 7) Acres or square feet are the size of area where soil sample was collected 8) Generally, Tillage method is either Conventional, or No-Till 10

21 9) Crop codes are shown in Table 3.1. The code is used to identify the crop and generates related crop recommendations. Table 3.1: Crop codes 1 Tall grass hay or pasture (less than 30% legume) 2 Tall grass and legume hay (more than 30% legume) 3 Tall grass and legume pasture (more than 30% legume) 4 Blue grass and white clover pasture (more than 30% legume) 5 Grass pasture (less than 30% legume) 6 Alfalfa or alfalfa and grass hay 7 Grass or grass and legume seeding 8 Alfalfa or clover seeding 9 Corn grain 10 Corn silage 11 Strawberries 12 Orchard, grapes, and nut crops 13 Small grains 14 Soybeans 15 Burley Tobacco 16 Home gardens 17 New lawn Seedings 18 Established lawns or turf Others 11

22 3.2.3 Sample Tested Values Data Once the soil sample is tested, the amount of nutrient values such as lime, ph, phosphorus, potassium, calcium, and magnesium are obtained. With these values, we can generate recommendations of fertilizer and Aglime for that sampling area. The output also provides the ranges of available nutrient levels in the soil sample. 3.3 Recommendations Nutrient Levels A standard soil test measures the level of phosphorous (P), potassium (K), calcium (Ca), and magnesium (Mg) present in the soil. These are important elements in healthy soils, and should be maintained at optimum levels. The different ranges of P, K, Ca, Mg nutrient levels present in the soil are shown in Tables 3.2, 3.3, 3.4, and 3.5, respectively. Table 3.2: Phosphorus levels in lbs/acre Range Level 0-25 Low Med High >80 Very High Table 3.3: Potassium levels in lbs/acre Range Level 0-60 Low Med High >240 Very High Table 3.4: Calcium levels in lbs/acre Range Level Low Med High >4000 Very High 12

23 Table 3.5: Magnesium levels in lbs/acre Range Level 0-99 Low Med High >500 Very High Soil ph The soil s ph level is either acidic, neutral or alkaline. The ph value levels are shown in Table 3.6. ph values ranges from 0 to 14. The ph of the soil usually in the range 4.5 to 8.5. A ph level between 5.8 and 6.5 is considered to be best for the production of most field crops but Alfalfa grows best at ph [12]. Table 3.7 Shows the normal ph ranges and recommended ph values for optimal growth of various field crops [24]. Table 3.6: ph Levels < 7.0 Acidic = 7.0 Neutral > 7.0 Alkalinity Table 3.7: Ranges and recommended ph for optimal growth of some of the field crops [24] Crop Species Normal growth ph Range Recommended ph Range Alfalfa 6.5 to to 7 Barley 6.3 to to 6.5 Birdsfoot trefoil 6 to to 6.5 Clovers 5.8 to to 6.2 Corn 5.8 to to 6.2 Grasses 5.8 to to 6.2 Oats 5.8 to to 6.2 Soybeans 6.5 to to 7 Wheat 6.3 to to

24 3.3.3 Lime Requirement It is determined by buffer ph value. The lime requirement determines the amount of ground lime that should be added to a soil to raise its ph to target value [4] Cation Exchange Capacity CEC is the indicator of the nutrient holding capability of the soil. It estimates the soil ability to attract, retain and exchange cation elements. It is measured in milliequivalent per 100 grams of soil (meq/100g). Milliequivalent (meq) contents of K, Ca, Mg and hydrogen (H) are calculated as shown in equations (1), (2), (3), (4). It can be determined by adding all the calculated milliequivalent (meq) contents of K, Ca, Mg and hydrogen (H) and is shown in equation (5). = (1) = Mg = (2) (3) H =2 H (4) CEC= + + Mg +H (5) Percent Base Saturation Percent base saturation is the percentage of the exchange sites that are occupied by the basic cations. Percent saturation contents of K, Ca, Mg and H are calculated as shown in the equations (6), (7), (8), and (9). It can be calculated by adding all the calculated percent saturation contents of K, Ca, Mg and H as shown in equation (10). =100 (6) 14

25 =100 Mg =100 H =100 (7) (8) (9) Total =K + Ca + Mg (10) 3.4 Methodology to Calculate Recommendation Values Since Crop Code is the key for all recommendations, we need to make sure that crop code is correct. Required recommendations are generated for fertilizer (nitrogen, Phosphate, Potash) and Aglime. The way of calculating these recommendations are explained below Nitrogen Recommended Values for Different Type of Crops Nitrogen (N) recommended values depend upon the crop code. * or ** represents foot note at bottom of the recommendation sheet as shown below. Table 3.8 shows the amounts of nitrogen which can apply to their respective crops. 15

26 Table 3.8: Recommended Nitrogen values for different crops Crop ID Crop Description Nitrogen (lbs/acre) 1 Tall grass hay or pasture (less than 30% legume) (lbs/acre) Tall grass and legume hay (more than 30% legume) (lbs/acre) 0 3 Tall grass and legume pasture (more than 30% legume) (lbs/acre) 0 4 Blue grass and white clover pasture (more than 30% legume) (lbs/acre) 0 5 Grass pasture (less than 30% legume) (lbs/acre) Alfalfa or alfalfa and grass hay (lbs/acre) 0 7 Grass or grass and legume seeding (lbs/acre) * 8 Alfalfa or clover seeding (lbs/acre) * 9 Corn grain (lbs/acre) Corn silage (lbs/acre) Strawberries (lbs/acre) Orchard, grapes, and nut crops (lbs/acre) ** 13 Small grains (lbs/acre) Soybeans (lbs/acre) 0 15 Burley tobacco (lbs/acre) Home gardens (lbs/ 1000 sq ft) 2 17 New lawn seedings (lbs/ 1000 sq ft) 2 18 Established lawns or turf (lbs/ 1000 sq ft) 3 * For pure grass seeding, apply lbs/acre of N, for grass legume mixtures apply 0-30 Lbs/A of N. * For Alfalfa or clover seeding, apply 0 to 30 Lbs/A of N. (Usually 15 lbs/acre is adequate). ** For orchard, grapes, and nut crops, apply sufficient N fertilizer to maintain or obtain desired shoot growth and vigor. If nitrogen has not been applied previously, a convenient starting point would be an application of 1/4 lb of acre 16 % N carrier per tree per year of age. In future years, use more or less depending upon tree response. 16

27 3.4.2 Phosphate (P2O5) Recommended Values for Different Type of Crops Phosphate (P 2 O 5 ) values depend upon the phosphorus (P) levels and its crop code. For example, if the crop code is 3, the phosphorus level is very high and P value is less than 100 then the phosphate value is 25. If the phosphorus value is more than 100 then its value is 0. Table 3.9 shows all the values of phosphate with respect to crop code. For very high level of phosphorus without any conditional value of it, phosphate is zero. Table 3.9: Recommended Phosphate [P 2 O 5 ] values for different crops P Levels (lbs/acre) Crop Description Very High ID Low Med High (P- condition) 1 Tall grass hay or pasture (less than 30% legume) (lbs/acre) (P<=100) 2 Tall grass and legume hay (more than 30% legume) (lbs/acre) (P<=100) 3 Tall grass and legume pasture (more than 30% legume) (lbs/acre) (P<=100) 4 Blue grass and white clover pasture (more than 30% legume) (lbs/acre) Grass pasture (less than 30% legume) (lbs/acre) (P<=100) 6 Alfalfa or alfalfa and grass hay (lbs/acre) (P<=100) 7 Grass or grass and legume seeding (lbs/acre) (P<200) 8 Alfalfa or clover seeding (lbs/acre) (P<100); 40 (P<200) 9 Corn grain (lbs/acre) (P<200) 10 Corn silage (lbs/acre) (P<200) 11 Strawberries (lbs/acre) Orchard, grapes, and nut crops (lbs/acre) Small grains (lbs/acre) Soybeans (lbs/acre) (P<200) 15 Burley tobacco (lbs/acre) Home gardens (lbs/ 1000 sq ft) (P<100) 17 New lawn seedings (lbs/ 1000 sq ft) (P<100) 18 Established lawns or turf (lbs/ 1000 sq ft)

28 3.4.3 Potash Potash recommended values depend upon the potassium (K) level available in the soil and its crop code. Table 3.10 displays all the values with respect to crop code and potassium level content in the soil. For very high level of potassium without any conditional value of it, potash is zero. 18

29 Crop ID Table 3.10: Recommended Potash [K 2 O] (Lbs/Acre) values for different crops Description Tall grass hay or pasture (Less than 30% legume) (lbs/acre) Tall grass and legume hay (more than 30% legume) (lbs/acre) Tall grass and legume pasture (more than 30% legume) (lbs/acre) Blue grass and white clover pasture (more than 30% legume) (lbs/acre) Grass pasture (less than 30% legume) (lbs/acre) K LEVELS (lbs/acre) Low Med High Very High (K-condition) Alfalfa or alfalfa and grass hay (lbs/acre) (K<=550) 7 Grass or grass and legume seeding (lbs/acre) Alfalfa or clover seeding (lbs/acre) Corn grain (lbs/acre) (K< 550) 10 Corn silage (lbs/acre) (K<=550) 11 Strawberries (lbs/acre) Orchard, grapes, and nut crops (lbs/acre) Small grains Soybeans (lbs/acre) Burley tobacco (lbs/acre) (K<375) 16 Home gardens (lbs/ 1000 sq ft) New lawn seedings (lbs/ 1000 sq ft) Established lawns or turf (lbs/ 1000 sq ft)

30 3.4.4 Aglime Aglime is an agricultural liming material which has the ability to neutralize soil acidity by increasing the soil s ph value [13]. Most soils need regular applications of Aglime to maintain ph in a specific range for crop production. Maintaining a good ph value is very important for escalating nutrients values in the soil. Aglime value mainly depends upon the magnesium, calcium, ph, lime requirement (LR), recently limed and crop factors. The most common Aglimes used are ground and dolomitic limestone. Aglime values for particular crops can be calculated by using the formula shown in equation (11) and (12). Equation (11) is only applicable to calculate the Aglime for the crop codes from 1 to 15. = (( 2+0.5)/2) (11) Equation (12) is applicable to calculate the Aglime for the crop codes 16, 17 and 18. = ( ) 10 (12) Based on the calculated Aglime values and other nutrients present in the soil, as shown in Tables 3.11, the amount of Aglime is recommended in units (tons/acre). Aglime values are different for different crops as shown in Tables 3.11 to Table Table 3.11 shows the amount of recommended values of Aglime for Tall Grass Hay or Pasture (Less Than 30% Legume). 20

31 Table 3.11: Recommended Aglime values for Crop code 1 Inputs Recommendations Calculated Aglime ph LR Mg Recently limed Aglime < 2 N/A N/A N/A N/A 2 T/A Ground Lime > 3 N/A N/A N/A N/A 3 T/A Ground Lime N/A < = 6 < 2.4 > = 100 NO 2 T/A Ground Lime N/A < 6 > 2.4 > = 100 NO 3 T/A Ground Lime N/A > 6.3 N/A > =100 NO None N/A < = 6 < 2.4 < 100 NO 2 T/A Dolomitic Lime N/A >6 < 2.4 < 100 NO Note 1 N/A <6.6 >= 2.4 < 100 NO 3 T/A Dolomitic Lime N/A >= 6.6 N/A < 100 NO 0.5 T/A Dolomitic Lime N/A >= 5.7 >1 N/A YES 0 T /A 1- The above recommendations are for a yield goal of 3 TO 4 Tons/Acre and assume a soil ph corrected to 6.5. N needs depend on desired yield goal. K application should be reduced if Magnesium (Mg) is low (less than 100 Lbs/A). 1- Use any fertilizer or approved organic material that will supply the plant nutrients recommended. Your county agent can suggest locally available fertilizers to suit the recommendation. Apply 50 LBS/A of N by itself or with a complete fertilizer in late winter and/or September. An additional 50 lbs/a of N can be applied after the first cutting if desired. Retest your soil each fall. The amount of recommended values of Aglime for Tall Grass and Legume Hay (More Than 30% Legume) as shown in Table

32 Table 3.12: Recommended Aglime values for Crop code 2 Inputs Calculated Aglime ph LR Mg Recently limed Recommendations Aglime < 2 N/A N/A N/A N/A 2 T/A Ground Lime > 3 N/A N/A N/A N/A 3 T/A Ground Lime N/A <=6 < 2.4 >=100 NO 2 T/A Ground Lime N/A <6 > 2.4 >=100 NO 3 T/A Groundlime N/A <6 > = 2.4 >=100 NO 2 T/A Groundlime N/A >6.3 N/A >=100 NO None N/A <=6.6 < 2.4 <100 NO 2 T/A Dolomitic Lime N/A <6.6 < 2.4 <100 NO Note 2 N/A <6.6 > = 2.4 <100 NO 3 T/A Dolomitic Lime N/A >=6.6 N/A <100 NO 0.5 T/A Dolomitic Lime N/A >6 >1 N/A YES 0 T/A 2- The above recommendations are for a yield goal of 3 to 4 Tons/Acre and assume a soil ph corrected to 6.5. Use any fertilizer or approved organic material that will supply the plant nutrients recommended. Your county agent can suggest locally available fertilizers to suit the recommendation. Fertilizer application can be made in fall or in late February to early March. Retest your soil each fall. 22

33 The amount of recommended values of Aglime for Tall Grass and Legume Pasture (More Than 30% Legume) as shown in Table 3.13 Table 3.13: Recommended Aglime values for Crop code 3 Inputs Recommendations Calculated Aglime ph LR Mg Ca Recently limed Aglime < 2 N/A N/A N/A N/A N/A 2 T/A Ground Lime > 3 N/A N/A N/A N/A N/A 3 T/A Ground Lime N/A <=6 < 2.4 >=100 N/A NO 2 T/A Ground Lime N/A <6 > 2.4 >=100 <4000 NO 3 T/A Ground Lime N/A <=6 >=2.4 >=100 >=5000 NO 2 T/A Ground Lime N/A >6.3 N/A >=100 N/A NO None N/A <6 <2.4 <100 <4000 NO 2 T/A Dolomitic Lime N/A >6 <2.4 <100 >4000 NO Note 3 N/A <6.6 <2.4 <100 >=4000 NO None N/A <6.6 >=2.4 <100 N/A NO 3 T/A Dolomitic Lime N/A >=6.6 N/A <100 N/A NO 0.5 T/A Dolomitic Lime N/A >6 >1 N/A N/A YES 0 T/A 3- The above recommendations are for a yield goal of 3 to 4 Tons per Acre and were made assuming a ph corrected to Use any fertilizer or approved organic material that will supply the plant nutrients recommended. Your county agent can suggest locally available fertilizers to suit the recommendation. Fertilizer application can be made in fall or in late February to early March. Retest your soil each fall. 23

34 The amount of recommended values of Aglime for Blue Grass and White Clover Pasture (More Than 30% Legume) as shown in Table 3.14 Calculated Aglime Table 3.14: Recommended Aglime values for Crop code 4 Inputs ph LR Mg Ca Recently limed Recommendations Aglime < 2 N/A N/A N/A N/A N/A 2 T/A Ground Lime > 3 N/A N/A N/A N/A N/A 3 T/A Ground Lime N/A <=6 <2.4 >=100 N/A NO 2 T/A Ground Lime N/A <6 >2.4 >=100 <4000 NO 3 T/A Ground Lime N/A <=6 >=2.4 >=100 >=5000 NO 2 T/A Ground Lime N/A >6.3 N/A >=100 N/A NO None N/A <=6 <2.4 <100 <4000 NO 2 T/A Dolomitic Lime N/A >6 <2.4 <100 >4000 NO Note 4 N/A <6.6 <2.4 <100 >=4000 NO None N/A <6.6 >=2.4 <100 N/A NO 3 T/A Dolomitic Lime N/A >=6.6 N/A <100 N/A NO 0.5 T/A Dolomitic Lime N/A >6 >1 N/A N/A YES 0 T/A 4- The above recommendations assume a ph of 6.0 and up for acidic soils, and a ph of 5.5 and up for lime-influenced soils. Grazing management has marked effect on composition and productivity of pastures. Summer and fall application of 50 Lbs/A of Nitrogen may benefit unimproved pastures with little legume, or where increased fall production is desired. For longer intervals between topdressings, adjust P2O5 accordingly, but use K2O as shown above. 4-Use any fertilizer or approved organic material that will supply the plant nutrients recommended. Your county agent can suggest locally available fertilizers that suit the recommendation. Fertilizer can be applied in late winter. Little or no nitrogen is needed where clover is 30% or more of the stand. Retest your soil regularly. 24

35 The amount of recommended values of Aglime for Grass Pasture (Less Than 30% Legume) as shown in Table Calculated Aglime Table 3.15: Recommended Aglime values for Crop code 5 Inputs Recommendations ph LR Mg Ca Aglime < 2 N/A N/A N/A N/A 2 T/A Ground Lime > 3 N/A N/A N/A N/A 3 T/A Ground Lime N/A < = 6 < 2.4 > = 100 N/A 2 T/A Ground Lime N/A <6 >2.4 > = 100 < T/A Ground Lime N/A <=6 <=2.4 > = 100 > = T/A Ground Lime N/A >6.3 N/A > = 100 N/A None N/A <=6 <2.4 < 100 < T/A Dolomitic Lime N/A >6 <2.4 < 100 > 4000 Note 5 N/A <6.6 <2.4 < 100 > = 4000 None N/A <6.6 >=2.4 < 100 N/A 3 T/A Dolomitic Lime 5- The above recommendations are for a yield goal of 3-4 tons/acre and assume a soil ph corrected to 6.5. Nitrogen (N) applications depend on the desired yield goal. 5-Use any fertilizer or approved organic material that will supply the plant nutrients recommended. Your county agent can suggest locally available fertilizers to suit the recommendation. Apply 50 Lbs/A of N by itself or with a complete fertilizer in late winter. An additional 50 Lbs/A of N can be applied after each cutting if desired. Retest your soil each fall. The amount of recommended values of Aglime for Alfalfa or Alfalfa and Grass Hay as shown in Table

36 Table 3.16: Recommended Aglime values for Crop code 6 Inputs Calculated Aglime Recommendations Aglime 1 2 T/A Ground Lime > 4 4 T/A Ground Lime Otherwise Calculated Aglime T/A Dolomitic Lime The amount of recommended values of Aglime for Grass or Grass and Legume Seeding as shown in Table Table 3.17: Recommended Aglime values for Crop code 7 Inputs Recommendations Calculated Aglime Mg Aglime 1 N/A 2 T/A Ground Lime > 4 N/A 4 T/A Ground Lime Otherwise <100 Calculated Aglime T/A Dolomitic Lime The amount of recommended values of Aglime for Alfalfa or Clover Seeding as shown in Table Table 3.18: Recommended Aglime values for Alfalfa or Crop code 8 Inputs Recommendations Calculated Aglime Mg Aglime 1 N/A 2 T/A Ground Lime >4 N/A 4 T/A Ground Lime Otherwise <100 Calculated Aglime T/A Dolomitic Lime The amount of recommended values of Aglime for Corn Grain as shown in Table

37 Table 3.19: Recommended Aglime values for Crop code 9 Inputs Recommendations Calculated Aglime ph Mg Aglime > 4 N/A N/A 4 T/A Ground Lime Otherwise N/A <100 Calculated Aglime T/A Dolomitic Lime N/A >= 6.5 < T/A Dolomitic Lime The amount of recommended values of Aglime for Corn Silage as shown in Table Calculated Aglime Table 3.20: Recommended Aglime values for Crop code 10 Inputs Recommendations ph LR Mg Aglime > 4 N/A N/A N/A 4 T/A Ground Lime N/A N/A > 0 < 100 Calculated Aglime T/A Dolomitic Lime N/A >= 6.5 N/A < T/A Dolomitic Lime The amount of recommended values of Aglime for Strawberries as shown in Table Table 3.21: Recommended Aglime values for Crop code 11 Inputs Recommendations Calculated Aglime ph Mg Aglime > 4 N/A N/A 4 T/A Ground Lime N/A N/A <100 Calculated Aglime T/A Dolomitic Lime N/A > = 5.8 N/A 0 T/A The amount of recommended values of Aglime for Orchard, Grapes, and Nut Crops as shown in Table

38 Table 3.22: Recommended Aglime values for Crop code 12 Inputs Recommendations Calculated Aglime Aglime > =4 4 T/A Ground Lime < 4 Cal Aglime T/A Ground Lime The amount of recommended values of Aglime for Small Grains as shown in Table Table 3.23: Recommended Aglime values for Crop code 13 Inputs Recommendations Calculated Aglime Mg Aglime > 4 N/A 4 T/A Ground Lime < =4 N/A Calculated Aglime T/A Otherwise <100 Calculated Aglime T/A Dolomitic Lime The amount of recommended values of Aglime for Soybeans as shown in Table Table 3.24: Recommended Aglime values for Crop code 14 Inputs Recommendations Calculated Aglime Mg Aglime > 4 N/A 4 T/A Ground Lime < =4 N/A Calculated Aglime T/A Otherwise <100 Calculated Aglime T/A Dolomitic Lime The amount of recommended values of Aglime for Burley Tobacco as shown in Table

39 Calculated Aglime Table 3.25: Recommended Aglime values for Crop code 15 Inputs Recommendations ph Recently limed Aglime N/A <5.5 YES Calculated Aglime T/A > 4 N/A NO 4 T/A Ground Lime >=1 > = 6 NO 1 T/A Ground Lime N/A > = 6.2 NO 0 Tons/Acre N/A > 5.5 YES 0 Tons/Acre The amount of recommended values of Aglime for Home Gardens as shown in Table Table 3.26: Recommended Aglime values for Crop code 16 Inputs Recommendations Calculated Aglime ph Ca Aglime > 180 N/A N/A 180 * Lbs / 1000 Sq Ft N/A > 5.5 > * Lbs / 1000 Sq Ft N/A >5 > * Lbs / 1000 Sq Ft Otherwise N/A N/A Calculated Aglime Lbs / 1000 Sq Ft The amount of recommended values of Aglime for New Lawn Seedings as shown in Table Table 3.27: Recommended Aglime values for Crop code 17 Inputs Recommendations Calculated Aglime ph Ca Aglime > 180 N/A N/A 180 Lbs / 1000 Sq Ft N/A >6 > Lbs / 1000 Sq Ft Otherwise N/A N/A Calculated Aglime Lbs / 1000 Sq Ft 29

40 The amount of recommended values of Aglime for Established Lawns or Turf as shown in Table Table 3.28: Recommended Aglime values for Crop code 18 Inputs Recommendations Calculated Aglime ph Ca Aglime > 180 N/A N/A 180 Lbs / 1000 Sq Ft N/A >6 > Lbs / 1000 Sq Ft Otherwise N/A N/A Calculated Aglime Lbs / 1000 Sq Ft These recommendations and calculations are applicable only to the state of West Virginia as the data for the Soil Analysis has been taken from the state. 3.5 Test Report The recommendation report should be made in a format which should be able to show all the information including customer details, sample details, soil sample tested nutrient values and its ranges, and recommendations of fertilizer and Aglime for that specific crop. 30

41 Chapter 4: System Design 4.1 Database System A database system is a combination of database, DBMS, and applications programs. All data files are collected and stored in one location called as database and all database applications are interact with DBMS, whichh centrally manages the database [5]. Users can access only database application which manages the database through DBMS. The various components of a database system are shown in the Figure 4.1. Figure 4.1: The components of database system [5] Database A database is an organized collection of data which can be easily accessed, managed and updated. It typically contains aggregations of data records or files [19]. Databases are constructed in such a way to meet the data analysis needs of users. Many databases start as a spreadsheet. As the data grows, it becomes difficult to handle the spreadsheets. It is a good idea to transfer the data to a database created by a database management system (DBMS) [20]. 31

42 4.1.2 Database Management System (DBMS) DBMS is a tool which allows defining, creating and managing databases access. Now-adays different types of DBMS softwares are available. For examples, Oracle, Microsoft SQL Server, IBM DB2, Microsoft Access, Informix, dbase, and FoxPro Database Applications Database applications are computer programs which allow users to enter and retrieve the information through a user friendly interface. In this project, users can easily insert, retrieve and query database tables in MS Access through a database application developed in C #.NET. 4.2 Microsoft Access: Microsoft Access is a relational database management tool that is used to create, modify and manage the data. Access provides its own environment to assist in building of database process. There are several reasons to select MS Access in this project. They are 1) MS Access is easy to learn and can be used to connect as back-end with many other windows based applications. 2) In spite of its simplicity, it provides many features which can be found in commercial DBMS softwares. 3) Finally, Access supports two standard query languages, Structured Query Language (SQL) and Query By Example (QBE). An Access database is a collection of working elements known as data objects (tables, queries, forms reports, relationships, and toolbars). An access data object performs all the functions of a DBMS. Access stores data in various tables and is based on the relational model [5] Database Tables Access database tables are useful to store and relate its data [5]. A table consists of records and fields. Each column of a grid contains information about the subject of the table and each row represents complete entry for a particular subject. The most common methods used to build tables in Access are: 1. Datasheet View 2. Design View 32

43 Creating Tables in Datasheet View One of the simplest ways to build new tables is by entering data directly into the Datasheet View in Access. Access allows the user to manually enter data to specify the number of rows and columns in the table. Figure 4.2 shows datasheet view of an Access Table. Figure 4.2: Datasheet View In general, datasheet view compromises the flexibility for the sake of simplicity i.e. the designer cannot control the field data types and it will not allow the user to specify validation rules for the data that is entered into the new table. Design view provides a more comprehensive and flexible option to create a table [5] Creating Tables in Design View Access divides the Design View into two halves: design grid (upper half) and field properties (lower half) [5]. The design grid allows the user to define the field names, their data types and description of each field. Field properties display the properties of each field in the design grid. Table 4.1 Shows design view of a access table 33

44 4.3 Tables used in the Soil Analysis Report Tool In this application, the following tables were created as shown in Figure CUSTOMERS (CID, First Name, Last Name, Street, City, State, County, Zip code, phone, ) 2. ORDERS (Lab ID, CID, Received date, Sample ID, County Serial Number, Previous Crop, Soil Name, Texture, Cost sharing, Soil limed last 12 months, Acres, SqFeet, StateID, Tmethod, CropID, SpH, Slime, SP, SK, SCa, SMg) 3. TEXTURE (ID, Texture Name) 4. TILLAGE (ID, Tname) 5. STATECODE (Code, State) 6. COUNTY (ID, State Code, State, County) 7. CROP (CropID, Desc) Figure 4.3: Tables used in this application CUSTOMERS table Table 4.1 shows the fields in customer details table in MS Access. This table is used to store the customer details. Table 4.1: CUSTOMERS table 34

45 4.3.2 ORDERS table Soil sample data includes all the fields of data which was given by the customers through the soil form questionnaire and soil tested values are stored in this order table as shown in Table 4.2. Since Lab ID is uniquely identifying each record of this table, it is considered as a primary key and CID, stateid, Tmethod, cropid are foreign keys. Table 4.2: ORDERS table TEXTURE table Table 4.3 shows the texture table designed in MS Access database for Soil Analysis Report Tool. This table has fields that store the information about soil textures. The field ID is the primary key. Table 4.3: TEXTURE table 35

46 4.3.4 TILLAGE table key. Table 4.4 shows the tillage methods which are being used in farming. ID is the primary Table 4.4: TILLAGE table STATE table Table 4.5 shows all state codes of United States designed for Soil Analysis Report Tool. This table is used to select a state code from the list. Since each state has a number of counties, county table depends up on the selection of state code. Table 4.5: STATE table COUNTY table Table 4.6 shows the counties related to their states for this tool. Here StateCode is a foreign key and ID is the primary key. Table 4.6: COUNTY table 36

47 4.3.7 CROP table Table 4.7 shows all crops grow in West Virginia state. In this table CropID is the primary key and CropName consists of all crop names. Table 4.7: CROP table 4.4 Entity-Relationship Diagram The relationships that exist among different tables which were designed for the Soil Analysis Report Tool known are defined in the entity-relationship diagram is shown in Figure 4.7. Relationships are logically defined between the tables using primary and foreign keys [17]. Figure 4.4: Entity - Relationship Diagram 37

48 4.5.NET Technology NET Framework Microsoft created an innovative and revolutionary platform called the.net Framework for developing web/windows applications. The.NET Framework supports programming language such as C#, C++, Visual Basics, Jscript and also older software s like COBOL etc. It mainly consists of an enormous library of code that can be used using object oriented programming language [14]. The.NET Framework has two main components: the common language runtime and the.net Framework class library. The.NET architecture is shown in the Figure 4.5 [15]. Figure 4.5:.NET architecture [15] Visual C#.NET Programming language C# is one of the languages that can be used to create applications in.net. It is advancement of the C and C++ languages and specifically to work with.net platform. Due to the simplicity of language syntax, developing applications using C# is easier than using C++. [14] 38

49 4.5.3 Visual Studios IDE Windows Visual Studio Integrated Development Environment (IDE) consists of various windows that help in application development process. The four windows are: 1. The Solution Explorer provides access to all files and components of the project. It also allows the user to add new items or delete old items from the project and build and run the project. 2. The Tool Box called as control box, displays icons for adding components in building applications without writing any code. Each icon can be dragged and dropped on to the windows form which creates a code in code editor within visual studio IDE. 3. The Property Window assists to change properties of the components which are built on the windows form. Properties are attributes of an object and can be used to control the behavior of objects. 4. The Server Window gives the user access to the available servers. It is very important to create data connectivity. This window helps the user to drag and drop the data tables on to the windows form [5] Windows Form and Controls The user interface is the most important part of an application. We can build the user interface by dragging and dropping controls from a toolbox on to the windows form. It is associated with each form and control in a code-behind-form file. Controls play an essential role in the building up of an application s user interface. They can help in programming style to make user interface more attractive and also provide entirely new functionality. Most controls in.net are derived from System.Windows.Forms.Control class. Many of these classes are themselves base classes for others controls, as it is the case with the Label and Textbox Base classes as shown in Figure 4.7 [14]. Figure 4.6: Controls Architecture [14] 39

50 4.6 Database Connectivity with ADO.NET ADO.NET objects that are required to develop a database application are as follows 1. Connection object To connect the application 2. Table Adapter object To fetching data using SQL queries 3. Dataset object To temporarily a subset of the database in memory 4. Data binding To displaying data in Windows form controls Connection Object An ADO.NET connection object assists in building a connection between the database and the application which can be used to fetch and save data from and to the database. The server explorer window and the data sources window have several tools which help in creating and configuring data connections [5] Table Adapter Object Once connection is created, the next need is to fetch the data into an application. Table Adapter provides communication between a database and application. It is also used to send updated data from application back to the database. Visual Studio enhances tools like table adapter configuration wizard and the table adapter query configuration wizard which allows the user to easily create and configure table adapters [22] Dataset Object Dataset object is a disconnected storage area. It is used for modification of relational data. Dataset object is a temporary data storage area that manages queried data for an application. The windows controls are bind to all datasets and they depend on the datasets for their data [23] Data Binding After fetching data on to the datasets, the last task is to display data on windows form for users to view and edit. The data source window and properties window are very important to exhibit data on to windows forms [5]. 40

51 Chapter 5: User Interface Design User interface design is the design of software applications which makes the user s interface easy to understand, comfortable to interact and efficient. User interface design uses graphics for interacting with software or computer applications by employing graphical images, widgets, along with text, to represent the information and actions available to a user [17]. tasks: The first screen in the application is shown in Figure 5.1. The user can perform three Enter Soil Data, Recommendations, and Queries. It has four buttons: 1) Soil Data The soil data form where we can input the data opens by clicking this button. 2) Recommendations This button opens the recommendations form where we can see the results and recommendations of a sample soil. 3) Search Search button enables the user to search various records in the database. Before click this button, user needs to select the field name to search by. 4) Help Instructions document of this tool opens by clicking this button. 41

52 Figure 5.1: Main Form 5.1 Soil Data In the soil data form, the user enters the customer details, sample details and soil tested results which are stored in the MS Access database. In this form, first name and last name have textboxes as well as a drop down menu which provide existing customer data. These textboxes suggest the names, if that customer name already exists in the database. If first name and last name matches with existing data, then it will automatically generate the remaining data of the customer details such as street, city, county, zip code, and phone. Then sample data can be entered in a regular pattern because sample data is unique for different samples. In this form, State, County, Crop Code, Soil texture and Tillage Method Code are drop down menus which can be selected easily. In the Test Result section, all the values such as ph, L.R, P, K, Ca, and Mg obtained by soil testing process can be entered. Lab ID is a unique 42

53 number to identify the soil sample, which has to be given by the user. The save button save all the entered data to appropriate Access table as shown in Figure 5.2. Figure 5.2: Soil Data Form 5.2 Recommendations The recommendation form shows all of the previous information along with recommendations for Aglime and Fertilizer. The Print button creates a word document and prints the document. User can edit and this word document to the county agent by clicking on the to county agent button. Figure 5.3 shows the recommendation form. 43

54 Figure 5.3: Recommendations Form 5.3 Search Search button enables the user to search various records in the database. The user needs to select the field name to search by. The various fields under search by are Lab ID, Last Name, County, Zip Code, Crop Code, Date and Phone. After selecting the search by, the information has to be given in text box for Lab ID, Last Name, County, Zip Code, Crop Code and Phone; for 44

55 the Date option, From date and To date has to be selected in order get search records for that particular period. Once the user hits the Search button, the search results are displayed in grid view at bottom of the main form. Figure 5.4 shows the search form. If the user needs the particular data details or recommendations from the search results, the user has to double click on that sample data, and then the Recommendation form is opened with all necessary data on that form. The search results also show a serial number to specify the total number of records retrieved. Figure 5.4: Search Form 5.4 Soil Analysis Report Recommendation Form is converted to word document as shown in Figure 5.5 by clicking on the Print button which is provided on the Soil Analysis Form. The word document shows all the information of soil sample, tested results and recommendations of Aglime and Fertilizer. User can edit and this word document to the customers and county agent. 45

56 Figure 5.5: Soil Analysis Report 46

57 Chapter 6: Conclusion and Future Work 6.1 Conclusion A window based Soil Information Management [SIM] software tool for the soil testing laboratory of West Virginia University was developed. The tool was implemented in visual studio with MS-Access as the database. This tool Provide the following improvements over existing software are: It is compatible with the windows operating system It eliminates the re-entering of customer data by retrieving the data already in the database It develops recommendations report which shows all the elements of tested sample soil along with the recommendations It creates a soil analysis report as a word document which can be stored or printed It enables the users to search any record of the soil database. It provides seven options to search the soil data; they are Lab ID, last name, county, zip code, crop code, date and phone. It can soil analysis report to customer. 6.2 Future Work The tool was developed for the window environment. It could be expanded to web environment. Additional test methods also be developed. 47

58 APPENDIX A: Old Software Recommendation Sheet 48