computer poultry litter

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c o m p u t e r s a n d e l e c t r o n i c s i n a g r i c u l t u r e 6 4 ( 2 0 0 8 ) 212224

a v a i l a bl e a t w w w . s c i en c e d i r e c t . co m

j o u r n a l h o m e p a g e : w w w . e l s e v i e r . c o m / l o c a t e / c o m p a g

A comprehensive GIS-based poultry litter management

system for nutrient management planning and litter

transportation

M.S. Kang a,, P. Srivastava b, T. Tyson b, J.P. Fulton b, W.F. Owsley c, K.H. Yoo b

a Rural Systems Engineering, Seoul National University, Seoul, Republic of Koreab Biosystems Engineering, 200 Corley Building, Auburn University, Auburn, AL, USAc Animal Science, Auburn University, Auburn, AL, USA

a r t i c l e i n f o

Article history:

Received 28 August 2007

Received in revised form

21 April 2008

Accepted 8 May 2008

Keywords:

Broiler litter

Poultry litter

Decision support system

Comprehensive nutrient

management plan

Transportation analysis

Geographic information system

a b s t r a c t

Confined poultry (broiler) production in Alabama results in about 1.8 million tons of lit-

ter annually. Because poultry production mainly occurs in the Appalachian Plateau region

of north Alabama, this region suffers from excessive land application of litter, resulting in

buildup of phosphorus (P) in soils and runoff of pathogens and P from land-applied areas.

Conversely, the Black Belt region of south-central Alabama suffers from depressed agri-

cultural economy because of poor soil fertility. In order to achieve optimal poultry litter

management in Alabama, litter produced in the concentrated production areas within the

Appalachian Plateau region mustbe optimallydistributed in this region or transported south

for utilization in the Black Belt region. Hence, a comprehensive system to provide improved

waste management strategies (optimal land application and transportation) for sustainable

on- and off-farm litter utilization in Alabama is needed. The primary focus of this study

was to develop a comprehensive, geographic information system (GIS)-integrated poultry

litter decision support system (PLDSS) for on- and off-farm management of poultry litter in

the Appalachian Plateau and Black Belt regions of Alabama. The PLDSS is a user-friendly,

comprehensive system that supports nutrient management planning, transportation anal-

ysis, anddata management for poultry litter management using ArcObjects, Visual Basic for

Applications (VBA), and Network Analyst in ArcGIS. Important functional components and

analytical capability of ArcGIS 9.1 were implemented in several sets of customized tools.

Because the PLDSS allows efficient development of nutrient management plan, it can help

to reduce over-application of poultry litter. Also, through PLDSS transportation analysis,

the litter can be optimally transported to nutrient deficit areas. Therefore, the PLDSS will

helppoultry producerswith optimal, cost-effectiveand environmentallysound poultry litter

management in Alabama.

2008 Elsevier B.V. All rights reserved.

1. Introduction

Alabama consistently ranks in top three, with Arkansas and

Georgia, in broiler production. Currently, more than 4000 poul-

Corresponding author. Tel.: +82 2 880 4582; fax: +82 2 873 2087.E-mail address: [email protected] (M.S. Kang).

try growers (out of 25,000 in US) operate about 12,000 broiler

houses (out of about 85,000 in US) in Alabama. In 2004,

Alabama broiler producers marketed more than 1 billion birds

with receipts of $2.41 billion (an increase of 31% over the

0168-1699/$ see front matter 2008 Elsevier B.V. All rights reserved.

doi:10.1016/j.compag.2008.05.013
mailto:[email protected]://dx.doi.org/10.1016/j.compag.2008.05.013http://dx.doi.org/10.1016/j.compag.2008.05.013mailto:[email protected]


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c o m p u t e r s a n d e l e c t r o n i c s i n a g r i c u l t u r e 6 4 ( 2 0 0 8 ) 212224 213

previous year) and accounted for nearly 44% of total farm

and forestry receipts (USDA-NASS, 2005). However, confined

broiler (referredto as poultry hereafter)productionin Alabama

alone results in about 1.8 million tons of poultry litter annu-

ally, containing high levels of nitrogen (N), phosphorus (P),

pathogens, and other potential contaminants (e.g., Arsenic,

Copper, and Zinc) (Kingery et al., 1994). Land application of

the large amount of litter generated from poultry productionis confined primarily to relatively small areas of perennial tall

fescue pastureland in the Appalachian Plateau region of north

Alabama.

Because application of poultry litter to pastures and row

crops serves as a cheap alternative to commercial fertilizer,

over the years, application of poultry litter based on agro-

nomic N requirements of forage has resulted in soil P buildup

because of high P to N ratio in poultry litter. Even though P is

an essential nutrient for plant growth, runoff of P can accel-

erate eutrophication, resulting in severe impairment of water

bodies that support aquatic, recreational and drinking water

uses (Carpenter et al., 1998; Daniel et al., 1998). Additionally,

nationwide, P losses from agricultural areas have emerged asa critical Total Maximum Daily Load (TMDL) issue. In addi-

tion to P, other waterquality issues(e.g., pathogens) associated

with massive amount of litterproduced each year threaten the

sustainability of poultry industry in the Appalachian Plateau

region.

In order to minimize discharge of pollutants from land-

applied poultry litter, Alabamas National Pollutant Discharge

Elimination System (NPDES) rules for Animal Feeding Opera-

tions (AFOs) requiresall AFOs to implement best management

practices (BMPs) to protect water quality. While the rules

for the larger Confined Animal Feeding Operations (CAFOs)

require a registration procedure and a Natural Resources Con-

servation Service (NRCS) approved waste management plan,all size AFOs are required to implement BMPs (Mitchell and

Tyson, 2001). A comprehensive nutrient management plan

(CNMP) and a phosphorus (P)-Index is a way to help meet BMP

requirements for AFOs.

Contrary to the Appalachian Plateau region which suf-

fers from excessive amount of nutrients in the form of

poultry litter, the Black Belt region located in south-central

Alabama suffers from depressed agricultural economy that

stems from poor soil fertility in pasture, hayfields, and row

crops. Also, intensive row crop producing regions such as

the nearby Tennessee Valley region use very little poultry

litter as an alternative to commercial fertilizers in spite of

extensive research which has demonstrated its value for

cotton, corn, and other crops (Mitchell and Donald, 1995;

Sims, 1987; Wood et al., 1993). In order to achieve an opti-

mal poultry litter management in Alabama, poultry litter

produced in the concentrated production areas within the

Appalachian Plateau region must be optimally distributed

and land applied in this region or should be transported

south for utilization in the Black Belt region (Kang et al.,

2006). Important poultry litter management issues particu-

lar to Alabama (which are similar to issues in other poultry

producing states) include limited use of nutrient manage-

ment planning and P-Index by farmers, over-application of

litter to small areas near the production facility, and lack of

transportation infrastructure for transportation of excess lit-

ter to nutrient deficit areas. Thus, to address many of these

issues (i.e., to help Certified Animal Waste Vendors (CAWVs)

and County Conservation District staff to efficiently develop

a CNMP and a P-Index for AFOs and CAFOs, and to transport

excess litter, for a cost-effective and environmentally sound

management of poultry litter) a comprehensive decision sup-

port system (DSS) is needed. A CAWV is a person who is

certified to transport and land apply (on another farm afterdeveloping a nutrient management plan and P-Index) excess

litter produced at a particular poultry facility. Further, since

CNMP, P-Index, and transportation analysis are all spatial in

nature, integration of such a comprehensive DSS with GIS is a

must.

A DSS has been defined in many different ways, but

it can be regarded, in general, as an interactive, flexible,

and adaptable computer-based information system especially

developed for supporting the recognition and solution of a

complex, poorly structured or unstructured, strategic manage-

ment problem for improved decision-making (Berlekamp et

al., 2007). A DSS often become spatial decision system (SDSS)

by integrating functionalities or coupling with existing GIStools. Recent studies related to environmental SDSSs have

been mostly limited to land and water quality management

(Choi et al., 2005; Berlekamp et al., 2007; Dorner et al., 2007;

Reichert et al., 2007; Rudner et al., 2007; Schluter and Ruger,

2007; Ochola and Kerkides, 2004). An environmental SDSS

for poultry litter management often consists of various cou-

pled environmental models, databases and assessment tools,

which are integrated under a graphical user interface (GUI),

often realized by using spatial data management functionali-

ties provided by a GIS.

Currently, a number of spatial and non-spatial animal

waste/nutrient management planning tools are being devel-

oped and/or supported. Examples of these tools includeManure Management Planner (MMP) developed by the Purdue

University(http://www.agry.purdue.edu/mmp/ ); Spatial Nutri-

ent Management Planner (SNMP) developed by the University

of Missouri (http://www.cares.missouri.edu/snmp/); NRCS

Animal Waste Management Software (http://www.wcc.nrcs.

usda.gov/awm/); Purdues web-based Nutrient Manage-

ment Availability Calculator (http://www.agry.purdue.edu/

mmp/); AFOPro (De et al., 2004; http://www.esri.sc.edu/

Projects/usda/milestone.asp); AFOWizard (http://ip.research.

sc.edu/catalog/00299.htm); Crop Nutrient Tool (http://npk.

nrcs.usda.gov/nutrient body.html); WebGro (Paz et al., 2004);

and web-based conservation planning worksheets (Steiner et

al., 2006). In some studies on poultry litter, the environmentalimplications of excessive nutrients (Kingery et al., 1994; Ritter,

2000; Cabrera and Sims, 2000) and the value of poultry litter

as a fertilizer (Mitchell and Donald, 1995; Bukenya et al., 1999;

Bagley and Evans, 1998; McKinley et al., 2000; Binford et al.,

2001; Mitchell and Tu, 2005) have been quantified. A number

of tools or systems have been, or are being, developed in

response to the regulations mandating CNMP. However, appli-

cation of current tools in Alabama is limited because quite

often these tools are difficult to use County Conservation

District staff, CAWVs, and farmers; do not support record

keeping (to demonstrate compliance) required by Alabama

land application of animal waste regulations; and do not

integrate GIS-based transportation analysis for efficient,
http://dx.doi.org/10.1016/j.compag.2008.05.013http://dx.doi.org/10.1016/j.compag.2008.05.013http://dx.doi.org/10.1016/j.compag.2008.05.013http://dx.doi.org/10.1016/j.compag.2008.05.013http://www.agry.purdue.edu/mmp/http://www.cares.missouri.edu/snmp/http://www.wcc.nrcs.usda.gov/awm/http://www.wcc.nrcs.usda.gov/awm/http://www.agry.purdue.edu/mmp/http://www.agry.purdue.edu/mmp/http://www.esri.sc.edu/Projects/usda/milestone.asphttp://www.esri.sc.edu/Projects/usda/milestone.asphttp://ip.research.sc.edu/catalog/00299.htmhttp://ip.research.sc.edu/catalog/00299.htmhttp://npk.nrcs.usda.gov/nutrient_body.htmlhttp://npk.nrcs.usda.gov/nutrient_body.htmlhttp://npk.nrcs.usda.gov/nutrient_body.htmlhttp://npk.nrcs.usda.gov/nutrient_body.htmlhttp://ip.research.sc.edu/catalog/00299.htmhttp://ip.research.sc.edu/catalog/00299.htmhttp://www.esri.sc.edu/Projects/usda/milestone.asphttp://www.esri.sc.edu/Projects/usda/milestone.asphttp://www.agry.purdue.edu/mmp/http://www.agry.purdue.edu/mmp/http://www.wcc.nrcs.usda.gov/awm/http://www.wcc.nrcs.usda.gov/awm/http://www.cares.missouri.edu/snmp/http://www.agry.purdue.edu/mmp/


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214 c o m p u t e r s a n d e l e c t r o n i c s i n a g r i c u l t u r e 6 4 ( 2 0 0 8 ) 212224

cost-effective, and environmentally sound regional/statewide

management of poultry litter.

Hence, the objective of this study was to develop a com-

prehensive GIS-based poultry litter decision support system

(PLDSS) to assist with nutrient managementplanningfor AFOs

and CAFOs, assist with record keeping of litter application

activities, and to provide transportation analysis functions

for optimal, cost-effective and environmentally sound, poul-trylittermanagement in Alabama. Such a system will not only

help sustain and enhance poultry industry in the Appalachian

Plateau region, but will also help row crop agriculture to grow

in the Black Belt region of Alabama.

2. Development of the PLDSS

DSS are computer-based systems that share several key

characteristics, including (1) assisting users in their decision-

making in a flexible and interactive manner; (2) solving all

classes of problems, including ill-structured ones; (3) hav-

ing a powerful and user-friendly interface; and (4) having adata analysis and modeling engine (Franck et al., 2000). A

comprehensive GIS-based PLDSS for on- and off-farm usage

of poultry litter in the Appalachian Plateau and Black Belt

regions of Alabama was developed for potential use by County

Conservation District staffs who have access to ArcGIS sys-

tem.

The user interface and the analysis routines in PLDSS were

developed by programming the Visual Basic for Applications

(VBA) with ArcObjects available in ArcGIS. Important func-

tional components and the analytical capability of ArcGIS 9.1

were implemented in several sets of customized and user-

friendly tools. The VBA development environment consists of

two primary tools: the customized dialog box for interactivelymodifying the user interface and the Visual Basic Editor for

creating user forms and for writing, testing, and debugging

Visual Basic code. This system incorporates a poultry litter

database management system (PLDBMS) that was developed

using MySQL 5.0 for the efficient management of poultry litter

data. Since ArcGIS supports VBA for integrated macro devel-

opment and MySQL is one of the worlds most popular open

source database, they were used to development of PLDSS.

The systems GUI allows users with limited computer

knowledge to use the PLDSS by customizing its applications.

For example, for the users convenience, the GUI provides an

instrumental operating system with pull-down menus. Fur-

thermore, it aids the users decision-making process regardingpoultry litter management, transportation, and evaluation by

displaying the projected results of various alternatives in the

form of graphical images, tables, and charts. To make the

system user-friendly, this system was designed to provide

detailed help on theinput parameters byclicking on the ques-

tion box buttons in the sub-modules input windows. Further,

in order to facilitate the process of determining the ideal

input parameters, the system was designed so that placing

the cursor on the input parameters input window the system

suggests default value for the applicable parameter.

The PLDSS has four modules (Fig. 1), namely, the CNMP

Decision Module, the Transportation Analysis Module, the

CNMP Assessment Module, and the PLDBMS Module. More

detail on the conceptual framework of this system can be

found in Kang et al.(2006). Thispaper presents detailed imple-

mentation of PLDSS in ArcGIS using ArcObjects, VBA, and

Network Analyst.

2.1. CNMP Decision Module

The CNMPDecision Moduleof the PLDSS wasdeveloped basedon the methodology proposed by the Alabama Cooperative

Extension System (ACES; Mitchell and Tyson, 2001). The ACES

plan is composed of five steps: (1) estimate poultry litter and

compost produced; (2) determine the nutrient value of the

poultry litter and compost based on quantity and availability

of nutrients in the litter; (3) map and calculate the spreadable

land area available for application; (4) determine the target

crop and nutrient needs, including whether poultry litter is

applied based on a nitrogen limit or on phosphorus removal

by the crop; and (5) determine uses for excess litter that can-

not be used on thefarmwhere it is produced and CAWV needs

(Miles and Bock, 2006; Kang et al., 2006).

The CNMP Decision Module of the PLDSS consists of threesub-modules: (1) Farm Operation, a sub-module containing

general information regarding the AFOs that calculates total

litter produced and the total nutrient value of produced lit-

ter; (2) Fields, a sub-module that calculates the P-Index and

nutrient needs of a cropland/hay/pasture field; and (3) CNMP

Application, a sub-module that determines the amount of lit-

ter to be applied to the field and the excess litter (Fig. 1). All

of the data calculated and generated by the CNMP Module

are stored and managed in PLDSSs database, named PLDBMS

(discussed later).

2.1.1. Comprehensive nutrient management plan (CNMP)

The United States Department of Agriculture (USDA) and theUnited States Environmental Protection Agency (EPA) have

released a Unified National Strategy for AFOs. This strat-

egy represents the USDAs and EPAs plan for addressing

the water quality and public health concerns arising from

AFOs. The cornerstone of the strategy is the expectation

that all AFOs will develop and implement a site-specific

CNMP.

Due to the limited technical staff available, the states

County Conservation District staffs are only able to develop

CNMPs/P-Index for CAFOs. The owners/operators of the more

than 4000 AFOs in Alabama receive little assistance. Since

AFOs are not required by law to have a CNMP in place,

CAWVs and AFO owners/operators are often not interested ina comprehensive plan, but prefer a simple plan that works.

In an attempt to address this problem, the CNMP Decision

Module will simplify development of CNMP and P-Index for

County Conservation District staff. Further, this will allow

CAWVs to develop CNMP and P-Index themselves with assis-

tance from County Conservation District staff. Note that in

Alabama only CAWVs are certified to transport poultry litter

in accordance with the Alabama Department of Environmen-

tal Managements (ADEM) AFOs/CAFOs rules. AFOs are small

operations, while CAFOs are big animal feeding operations.

CAFOs are AFOs with 1000 animal (feed cattle) unit equiv-

alency or more. For poultry (broiler) production this means

about 100,000 chickens. Federal regulations require CAFOs to


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Fig. 1 Overall conceptual architecture of the poultry litter decision support system (PLDSS).

carry a permit and to develop detailed nutrient management

plans designed to keep animal waste from contaminating sur-

face and groundwater.

2.1.2. Estimation of poultry litter produced and nutrient

value

Annual production estimates for poultry litter and compost

are calculated by multiplying the market weight of birds pro-

duced each year by the production rate, which is estimated to

be about 0.5 pounds of poultry litter per market weight pound

of bird produced, as suggested by Auburn University Biosys-

tems Engineering and the Alabama poultry industry (Mitchell

and Tyson, 2001).The nutrient values of poultry litter and compost used

in this study were the average values for litter and com-

posted dead birds and were estimates of the plant available

nutrients during the first year under Alabama conditions,

as reported by ACES (Mitchell and Tyson, 2001). Avail-

able nutrients from surface-applied litter and compost were

475845 and 425845 pounds of NP2O5K2O per ton,

respectively. Note that in the case of surface-applied lit-

ter, the N value should be multiplied by 0.84 to account

for N volatilization (Mitchell and Tyson, 2001). The nutrient

removal for the targeted crop (Bermuda grass pasture) was

501243 pounds NP2O5K2O per tons (Mitchell and Tyson,

2001).

2.1.3. Determination of crop and nutrient needs for each

field

Calculating thecorrect rate of nutrient needs to applyis impor-

tant to prevent the buildup of excess phosphorus in soil and

the contamination of ground and surface waters. Crop and

nutrient needs in the PLDSS were determined based on the

methodology (described earlier) proposed by ACES (Mitchell

and Tyson, 2001).

To identify fields for litter and compost spreading and to

calculate spreadable acreage, the land cover classificationdata

provided by the United States Geological Survey (USGS) were

used in thissystem. Spreadable land area in the PLDSS was the

total land area in fields receiving litter minus required buffersfor property lines (see Mitchell and Tyson, 2001, for example,

determination of spreadable land area). Nutrient needs were

determined based on N limit or on P removal by the crop to

which poultry litter was applied. P application in excess of

that recommended by soil test is based on a P-Index of field

vulnerability for P runoff into surface waters.

2.1.4. Phosphorus (P)-Index

Non-point sources of agricultural P have a considerableimpact

on water quality at a watershed-scale (McDowell et al.,

2001). Out of the three management scenarios examined by

McDowell et al. (2001), the P-Index seems to be the most use-

ful. Consequently, in many states the P-Index risk rating of an


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agricultural field plays a major role in the development of a

nutrient management plan (De et al., 2004).

TheP-Indexis a toolthatis usedto assess thesite and man-

agement practices with regard to the potential risk posed by

P movement to water bodies (USDA-NRCS, 2001). The P-Index

rating indicates the specified areas (e.g., pastures) that should

benefitand thepoultry litterratesthat shouldbe applied (Kang

et al., 2006). Nutrients are applied based on two options andare modified based on theP-Index: (1) N limitbased on soil test

recommendations fromAuburn Universitys Soil Testing Labo-

ratory (http://www.ag.auburn.edu/agrn//croprecs/index.html)

and (2) anticipated crop P removal, namely, at the N rate, 3 P

removal by crop, 2P removal by crop, 1P removal by crop,

andno P applicationfor verylow/low, medium,high,veryhigh,

and extremely high vulnerability ratings, respectively. More

information about Alabamas P-Index has been provided by

Kang et al. (2006), USDA-NRCS (2001) and Mitchell and Tyson

(2001).

2.1.5. Determination of excess litter

Once the previous determinations are completed, the poultrylitter orcompost can belandapplied. Note that dead birdcom-

post was not considered for offsite transport because farmers

are required to usethe dead birdcompost on thefarmwhere it

is generated before spreading any litter. Because of the human

health issues, dead bird compost cannot be transported with-

out a special permit from the state veterinarians office of the

Alabama Department of Agriculture and Industries (ADAI). In

PLDSS, dead bird compost wasnot considered for offsitetrans-

port.

The excess litter produced is determined based on how

much litter can be reasonably applied to each field, and thus

whether the poultry farm operation can effectively use all

the nutrients in the litter in an environmentally sound man-ner. If more litter is produced than can be used, it should

be consigned to an Alabama CAWV. The assigned CAWV can

utilize the Transportation Analysis Module to find the opti-

mum way to transport litter to nutrient deficient areas in the

Appalachian Plateau or Black Belt regions of the state.

2.2. Transportation Analysis Module

The Transportation Analysis Module allows CAWVs to find

the best route to transport litter from production areas to

application areas by examining factors such as the best route,

the closest route to fields within a certain distance, and

OriginDestination matrix created using NetworkModel tool-box in ArcGIS 9.1. The workflow used by Network Analyst in

the model is the same as the workflow for Network Analyst

in ArcMap. More detail on conceptual workflow for modeling

various transportation network analyses usingthe ArcGIS Net-

workModel can be found in Kang et al.(2006). This module was

developed using VBA in conjunction with ArcObjects in ArcGIS

environment.

Currently, CAWVs are reluctant to risk transporting litter

very far from the source. Some of the reasons given for this

include cost of transportation, low value of litter, unable to

load/reload litter, storage problems, and inability to spread

litter. As mentioned earlier, this study focuses on many of

these issues because there is consensus among researchers

and practitioners that transportation of litter within the pro-

duction areas (for proper distribution and land application)

and from production areas to Black Belt and Tennessee Valley

regions is a possible solution to alleviate excess litter problem

in the Appalachian Plateau region.

2.3. CNMP Assessment Module

An important component of PLDSS is the CNMP Assessment

Module, which is composed of two sub-modules, namely, On-

Farm Application and Offsite Application. These sub-modules

are used to determine optimal uses for excess litter that can-

not be used on the farm where it is produced. Based on

all previous modules, this module determines optimal land

application, the value of poultry litter as a fertilizer, and

the transport cost including a cleanout cost. It is economi-

cally most effective to transport excess litter from a farm to

offsite based on the rank considering travel distance using

OD matrix. The results of these sub-modules are linked

and managed by the PLDBMS. According to Miles and Bock

(2006), a recent inquiryindicates thatcurrently north Alabamavendors are typically receiving about $10 per ton for land

application of litter. Thus, they assume as our base case that

vendors could deliver poultry litter for a cleanout cost of $4

per ton plus $6 per ton for hauling an average of 40 miles at

$0.15/ton-mile. These values were used to calculate transport

cost.

2.4. PLDBMS and Geodatabase Modules

A critical issue when coupling the GIS software with CNMP

and network analysis is the database that is integrated into

the spatial-temporal database model. The PLDSS procedure

generates a large volume of CNMP and GIS data. Ineffectivedata management will result in a computational bottleneck

that can seriously degrade the performance of the system.

The PLDSS offers data input, data search, data management,

analytical and geographic visualization capabilities that can

provide effective decision support. The PLDSS incorporates

two database modules, PLDBMS and Geodatabase. The unique

spatial object IDs (i.e., operation ID and field ID) from Geo-

database are used to connect the PLDBMS with Geodatabase

and models (Fig. 2).

The PLDBMS was developed for the efficient management

of datarelatedto poultry litter. Thissystem was created bypro-

gramming MySQL, a relational database management system,

and VBA in ArcGIS. The data collected by CNMP from the userare stored and managed in a database server called MySQL

(MySQL AB, 2006). To access information from the database

server and open database connectivity (ODBC), a driver called

MySQL ODBC was used. The PLDBMS and MySQL database

server were used for pre- and post-processing the CNMP data.

PLDBMS consists of Data Management and Data Search

sub-modules. These sub-modules facilitate basic functions

for efficient data searches, storage, updates and export. The

Data Management sub-module includes an Excel-based cus-

tom record keeping tool that may meet users needs for farm

and field information, litter application, and excess litter to

CAWV. The Data Search sub-module has a function that can

search data regarding all CNMP implementation.
http://www.ag.auburn.edu/agrn//croprecs/index.htmlhttp://www.ag.auburn.edu/agrn//croprecs/index.html


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Fig. 2 Overall structure of PLDBMS and Geodatabase.

The data sets were organized into a geodatabase of ArcGIS

as separate feature classes. The geodatabase is the heart of

a spatial and operational information system and provides

the central storage system that allows communication and

intermediate storage among the various subsystems (Kang

et al., 2006). This geodatabase, which is similar to the cov-

erage model, supports a model of topologically integrated

feature classes. It also extends the coverage model to supportcomplex networks, topologies, relationships among feature

classes, and other object-oriented features. Each separate fea-

ture class represents either a factor or a constraint to be used

within the PLDSS analysis. Additional attributes have been

included in some feature classes to more effectively support

the analysis.

3. Implementation of the PLDSS

3.1. Study area and geodata

Alabama is a major sink for nutrients because over 95% ofthe grain fed to Alabamas farm animals is imported (Kingery

et al., 1994). The eight leading poultry producing counties in

the state produce more than 100% of each countys P needs

in the form of poultry litter. Cullman was the leading poultry

producing county in the state, followed by DeKalb, Marshall,

and Blount during the 2003 and 2004 marketing years. The

Black Belt region was selected as the pasture area to which

the excess poultry litter should be transported. All poultry

houses, pastures, and local road information in the study area

are visible at a zoom factor of 1:800,000.

In order to identify the amount of poultry litter produced,

the broiler data for each county were obtained from the

National Agricultural Statistics Service (USDA-NASS, 2005;

Kang et al., 2006). Users can easily add and use the poultry

farm layer in the PLDSS if they have real data on location

of poultry farms. The PLDSS can easily be extended to work

with other real data due to its generic form and structure.

Forage pastures were selected for poultry litter application in

the study area, although using the CNMP the procedure can

be easily extended to other crops. The pasture polygons were

converted to a point type geodatabase for Network Analysis.The attributes such as ID number, coordinates of latitude and

longitude, and pasture area for each pasture polygon were

then calculated and added to the database table associated

with the point pasture theme.

To create the pasture data set, the land cover classification

data provided by the United States Geological Survey (USGS)

were used to reclassify pasture/hay from Landsat TM images

of the study area. The land cover data are in the form of a sin-

gle band raster image. Pasture/Hay in this study was defined

as areas of grass, legumes, or grasslegume mixtures planted

for livestock grazing or the production of seed or hay crops.

The hydrologic soil group and field slope for the calculation

of the P-Index were extracted from the soil map and digitalelevation model, respectively. To identify fields for litter and

compostspreadingand to calculate spreadablearea, a detailed

farm map such as an aerial photo of the fields to scale will

be needed. The pasture polygons were used to obtained field

boundary and spreadable area in this DSS because it is not

easy to use numerous aerial photos of each field for the whole

study area.

A geodatabase network dataset must be created to con-

duct various network analyses. A geodatabase-based network

dataset was created using the streets feature class for

Alabama. This work is conducted using ArcCatalog in ArcGIS.

More detail on the procedure of creating a geodatabase net-

work dataset can be found in ESRI (2005).


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3.2. CNMP Decision Module

Users will be able to accurately identify the spatial location

where the litter is being generated and the location of the

application fields. We now give a hypothetical example that

demonstrates the utility of the CNMP Decision Module.

Suppose a farmer with three poultry houses cleans his

chicken houses producing X amount of poultry litter. He alsohas some fields where he can apply some of the litter. He,

therefore, contacts a CAWV to handle his litter. The CAWV,

whois trained in theuse of PLDSS,locates thefarmers chicken

houses and available fields. The CAWV and users can locate

thefarms using thesubmenu to retrievean address or it is pos-

sible to select directly them on the GIS data in the PLDSS. He

then determines if the farmer already has a nutrient manage-

ment plan. If not, the CAWV uses the CNMP Decision Module

and creates a simple but effective nutrient management plan

for the farmers land. Once developed, the CAWV determines

the amount of litter that can be applied on the farmers fields

(assume this amount is Y, where Y< X). The CAWV then takes

a look at the CNMP and locates farmers that require litter.He then uses the Transportation Analysis Module to deter-

mine thecost associatedwith haulinglitter to various farmers

fields that could benefit from the litter. He evaluates various

alternatives and makes arrangements to haul the litter. Before

applying litter, the CAWV uses the P-Index/CNMP Module to

develop a nutrient management plan if the farmer (to whose

farm excess litter will be applied) does not already have one.

Once fully developed and implemented, this simple to use

PLDSS will provide numerous options for both the farmers

interested in disposing of their litter and those requiring litter.

CAWVs will also be able to perform their task much more effi-

ciently and effectively and keep an electronic record of their

activities.To demonstrate how the PLDSS can be used to help the

user efficiently develop nutrient management plans in the

concentrated poultry litter production areas for on-farm uti-

lization, the PLDSS was applied to Cullman county. To assess

the applicability of this systems CNMP, on-farm application

of the CNMP and a transportation analysis was carried out on

selected farms in the county (see Kang et al., 2006).

3.2.1. Farm Operation sub-module

The Farm Operation sub-module has three dialog boxes,

namely, General Information, Total Litter Produced, and Total

Nutrient Value.

3.2.1.1. General Information Dialog Box. The General Infor-

mation Dialog Box (Fig. 3) allows users to enter general

information regarding the CAFO/AFO owner/operator and

CAWV for which the CNMP is being prepared, including the

farm ID and contact information. All the information entered

for the selected farm is saved into the systems database. The

ID of the poultry farm randomly selected to assess the appli-

cability of this system was 161.

3.2.1.2. Total Litter Produced and Nutrient Value Dialog Boxes.

The Total Litter Produced Dialog Box (Fig. 4) allows the user

to estimate the amount of poultry litter and compost pro-

duced by the farm selected from the General Information

Dialog Box. The corresponding Total Nutrient Value Dialog

Box calculates the total nutrient value of litter. In reaching

this figure, about 20% weight loss during the composting pro-

cess and about 5% mortality were assumed. Total poultry

litter and compost produced by the selected farm were 712.5

and 89.6 ton, respectively. As shown in Fig. 5, available nutri-

ents in poultry litter and compost were 33,51741,32632,063

(NP2O5K2O, ton) and 376451984033 (NP2O5K2O, ton),respectively.

3.2.2. Fields sub-module

3.2.2.1. P-Index Dialog Box. The P-Index Dialog Box (Fig. 5)

allows users to select a field and determine the distance for

buffer zones in order to properly determine the amount of

land application with respect to the nutrient needs and vul-

nerability of P runoff. It then extracts the field attributes such

as the applicable field ID, hydrologic soil group, field slope

and spreadable area, etc., and calculates the P-Index. A good

example of the use of the P-Index Dialog Box is shown in the

P-Index worksheet for Alabama presented in Agronomy Tech-

nical Note AL-72 (USDA-NRCS, 2001). The P-Index worksheet

is a matrix with 11 field characteristics and five value factors.

Each field characteristic has a weighting factor that is mul-

tiplied by a value factor. The hydrologic soil group and field

slope (%) among 11 field characteristics were automatically

extracted from geodatabase of the PLDSS. The sum of these

values gives the P-Index result. The P-Index Dialog Box exam-

ines one field at a time, calculating the P-Index by the method

described above.

The P-Index calculation resulted in a value of 14 for the

selected field ID of 2281, with an area of 7.88ha and the P-

Index was Very low/Low (Fig. 5). The distance to calculate

the buffer zone was 25 ft recommended by buffer width for

property line.

3.2.2.2. Nutrient Needs Dialog Box. The Nutrient Needs Dialog

Box (Fig. 6(A)) allows the user to select a crop and then deter-

mine the amount of nutrient needed for each field based on

the results received from the P-Index Dialog Box. The execu-

tion of this module for nutrient needs resulted in 19.6 ton for

poultry litter type and 21.9 ton for compost type, respectively.

3.2.3. CNMP Application sub-module

Based on the results produced by running the Total Lit-

ter Produced and Total Nutrient Value Dialog Boxes (Farm

Operation sub-module) for the poultry farm selected andthe field selected by the P-Index and Nutrient Needs Dialog

Boxes (Fields sub-module), the CNMP Application sub-module

(Fig. 6(B and C)) enables the user to determine the land appli-

cation rate and calculates excess litter and compost.

The results of carrying out the CNMP Decision sub-

module for on-farm utilization were as follows: the amount of

land application showed 21.9 ton in compost. Consequently,

the excess litter and excess compost by the selected farm

were 712.5 and 67.7 ton, respectively. This means that the

Transportation Analysis module should be implemented to

optimize the transportation of the excess litterto a region with

a poor soil fertility problem, such as the Black Belt region of

the state.


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Fig. 3 The General Information Dialog Box showing the general information for the selected farm.

Fig. 4 The Total Litter Produced And Total Nutrient Value Dialog Boxes showing the total poultry litter produced from the

selected farm and the results that calculates its total nutrient value.


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Fig. 5 The P-Index Dialog Box showing the procedure that calculates the P-Index and determines the buffer zone from the

selected field and the results that calculates its P-Index.

Fig. 6 The Nutrient Needs Dialog Box (A) showing its results about calculating the nutrient needs for the selected field and

the CNMP application sub-modules showing their results about calculating the amount of land application (B) and excess

litter (C).


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Fig. 7 The result of the available area polygons within the 1.0 mile cut off and conceptual workflow for its modeling (A)

and the result of the origindestination matrix with a cut off value of 1.0 mile and default number of 10 to find destinations

(fields) and conceptual workflow for its modeling (B).

3.3. Transportation Analysis

For the CNMPs offsite utilization of excess litter, this module

suggests alternatives to the selected farm and field to make

it possible to determine the optimal transportation. Once

the user selects a farm, this module automatically carries out

the transportation analysis. Once a farm has been selected by

the CNMP module, unless the user changes the selection, the

information for that farm is used to create a link to obtain the

CNMP calculationresults.This module finds thebest routesfor

a given order of stops based on travel distance that is the least

costly path (distance cost) from a farm to fields. The Direc-

tions Window can also be displayed with turn-by-turn maps

that can be shown by clicking on the Show Map sub-module.

This modules applicability assessment was conducted by

making use of a randomly selected farm and carrying out

Fig. 8 The CNMP Assessment modules for on-farm (A) and offsite (B) application.


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Fig. 9 PLDBSS: (A) the data management sub-module for the CNMP data record form; (B) the CNMP data record form

exported to MS-Excel file format; and (C) the data search sub-module in the PLDBMS.

a transportation analysis within the county by running the

CNMP. The excess litter calculated by the CNMP Decision

module is then available for transport to the offsite, and theoutcome predicted. Fig. 7(A) shows the results based on cal-

culation of 0.3, 0.5, and 1.0 miles feasible area for the selected

farms, which can reveal how many land application locations

(fields) lie within each of these areas. This can also be used

to determine how best to relocate the least accessible farms

or place new ones to facilitate land application of the poultry

litter produced (Kang et al., 2006).

An OriginDestination (OD) cost matrix (Fig. 7(B)) is also

created to illustrate deliveries from the chicken houses to each

pasture. The results of this matrix can be used to identify the

land application areas that will be serviced by each chicken

house within a specific travel distance. Also, it determines

the total travel distance from each chicken house to its landapplication pastures.

3.4. CNMP Assessment Module

In order to perform an optimal poultry litter management

process, CNMP for on-farm utilization within the selected

county and transportation analysis for on-farm utilization in

the Black Belt region was conducted. The CNMP was applied

to all the fields from all the farms within Cullman County and

an OD matrix analysis was carried out for the excess litter.

Network analysis of the On-Farm Application and Offsite

Application sub-modules are similar to the Transportation

Analysis Module. These sub-modules enablethe user to deter-

mine the land application area and the ranking according to

travel distance from each of the farm to fields within a cer-

tain distance (1.0 mile for this example) (Fig. 8). This modulehelps theuser to selectthe optimal nutrient management plan

based on destination rank.

These sub-modules carried out optimal poultry litter man-

agement to transport the excess litter or compost from the

selected farm (chicken house) to the feasible area within

distance less than 1.0 mile for the On-Farm Application sub-

module and the Black Belt region for the Offsite Application

sub-module.

3.5. Implementation of the PLDBMS

The results of all previous modules are linked to the systems

database,named PLDBMS, which allows data storage, revision,and searches to be conducted through the Data Management

and Data Search sub-modules.

A summary worksheet (for record keeping) is generated

that contains general information, poultry litter informa-

tion, field information, land application, excess litter, etc.,

needed for the development of the CNMP on the selected

farm (Fig. 9(A)). This summary CNMP worksheet can then

be uploaded and exported as an Excel spreadsheet file

through the Data Management sub-module (Fig. 9(B)). Prior

to running each sub-module, the user can examine and

confirm the farm and field data that are used to calcu-

late the applied CNMP through the Data Search sub-module

(Fig. 9(C)).


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4. Conclusions

This study focused on the development and implementa-

tion of a GIS-integrated poultry litter decision support system

(PLDSS) for on- and off-farm applications of poultry lit-

ter in the Appalachian Plateau and Black Belt regions of

Alabama. Development of this DSS was initiated because offour main reasons. First, the poultry industry in Alabama

is mostly concentrated in the Appalachian Plateau region,

and improper distribution and over-application of litter for

more than 25 years in this region has resulted in buildup

of phosphorus in many pasture fields, which threatens

surface water quality. Second, currently available DSS for

land application of poultry litter do not support transporta-

tion analysis. Third, available DSS are difficult to use. And,

fourth, record keeping required by Alabama Department of

Environmental Management (to show compliance with reg-

ulations) is not supported by many of the currently available

DSSs.

Various modules provided in the PLDSS addressed many ofthese issues. For example, the CNMP module allows users to

develop a quick nutrient management plan and phosphorus-

Index, the transportation analysis module allows them to

minimize transportation cost, and the database manage-

ment module allows them to keep record of their activities.

We envision this system to be used by County Conserva-

tion District staff and/or the CAWVs in cooperation with the

County Conservation District staff. Once fully implemented,

the system will allow increased use of nutrient manage-

ment planning and P-Index, thus reducing over-application

of poultry litter. The transportation analysis will help dis-

tribute excess litter within the Appalachian Plateau region

or the Black Belt region. The transportation analysis willalso help minimize transportation cost. Thus proper use of

the PLDSS will help simultaneously minimize water qual-

ity impairment of water bodies and transportation cost,

thus providing optimal management of poultry litter in

Alabama.

The PLDSS will allow optimal land application and trans-

portation of litter first in the Appalachian Plateau region

and then transportation and land application in the Black

Belt region. This will ensure that the litter application pro-

tects the water quality in the Appalachian Plateau region,

minimizes transportation costs, and improves soil fertility

in the Black Belt region. Hence, this study will help alle-

viate water quality problems in the Appalachian Plateauregion and poor soil fertility problems in the Black Belt

region.

There are several benefits and implications of the PLDSS.

For example, if used for a long time, the PLDSS will supply

a detailed database of poultry litter applications. Using this

database, researchers will be able to study the hydrologic,

geomorphic, and ecological characteristics that control NPS

pollution in animal waste applied watershed. Further, this

database will provide a complete picture of theextent of poul-

try litter management problem in the Appalachian Plateau

region andthe accurate locationof thearea(within thisregion)

where poultry production is concentration. A company inter-

ested in developing value-added products from poultry litter

will then be able to identify hot spots of excess poultry litter.

Further, we will be able to accurately determine the potential

of expansion of poultry industry in the Appalachian Plateau

region.

As mentioned earlier, this system was designed for use

by County Conservation District staff and/or CAWVs, because

they have traditionally developed nutrient management plans

and P-Index for CAFOs and AFOs. Further, County Conserva-tion District staffs are trained in the use of ArcGIS system.

However, often County Conservation District staffs are unable

to assist all the poultry producers because of their concen-

tration in a few counties. The authors envision that to fully

optimize litter management (i.e., environmentally sustainable

application and proper distribution with minimum trans-

portation cost), in future, the litter management will need to

transferred directly in the hands of CAWVs, poultry produc-

ers, and farmers. With the increased useof web-based system,

a webGIS-based system with all the functionalities provided

in the PLDSS will be ideal. This will shift the task of proper

land application of litter and transportation of excess litter

in the hands of CAWVs, producers, and farmers. The trickwould be to develop this system in such a user-friendly man-

ner that a person with litter knowledge of computers is able to

use it.

r e f e r e n c e s

Bagley, C.P., Evans, R.R., 1998. Broiler Litter as a Feed or Fertilizerin Livestock Operations. Mississippi State UniversityExtension Service.

Berlekamp, J., Lautenbach, S., Graf, N., Reimer, S., Matthies, M.,2007. Integration of MONERIS and GRE/AT-ER in the decision

support system for the German Elbe River Basin.Environmental Modelling & Software 22 (2), 239247.Binford, G., Hansen, D., Malone, B., 2001. Poultry litter: resource or

waste? Nutrient management notes. Delaware NutrientManagement Program 2 (3).

Bukenya, J.O., Befecadu, J., Jones, H.S., Reddy, K.C., Baiyee-Mbi, A.,1999. Economic feasibility of substituting fresh poultry litterfor ammonium nitrate in cotton production. In: The AnnualMeetings of the Northeast Agricultural and ResourceEconomics Association.

Cabrera, M.L., Sims, J.T., 2000. Beneficial use of poultryby-products: challenges and opportunities: 425450. In: Power,

J.F., Dick, W.A. (Ed.), Land Application of Agriculture,Industrial, and Municipal By-Products, SSSA Book Ser. 6,SSSA, Madison, WI.

Carpenter, S.R., Caraco, N.F., Correll, D.L., Howarth, R.W.,Sharpley, A.N., Smith, V.H., 1998. Nonpoint pollution ofsurface waters with phosphorus and nitrogen. EcologyApplication 8, 559568.

Choi, J.Y., Engel, B.A., Theller, L., Harbor, J., 2005. Utilizingweb-based GIS and SDSS for hydrological land used changeimpact assessment. Transactions of the ASAE 48 (2), 815822.

De, S., Kloot, R.W., Covington, E., Bezuglov, A., Taduri, H., 2004.AFOPro: a nutrient management decision support system forthe United States. Computers and Electronics in Agriculture43, 6976.

Daniel, T.C., Sharpley, A.N., Lemunyon, J.L., 1998. Agriculturalphosphorus and eutrophication: a symposium overview.

Journal of Environmental Quality 27, 251257.Dorner, S., Shi, J., Swayne, D., 2007. Multi-objective modelling and

decision support using a Bayesian network approximation to


13/13


a non-point source pollution model. Environmental Modelling& Software 22 (2), 211222.

ESRI, 2005. ArcGIS 9-ArcGIS Network Analyst Tutorial. 380 NewYork Street, RedLands, CA, USA.

Franck, W.C., Thill, J.-C., Batta, R., 2000. Spatial decision supportsystem for hazardous material truck routing. TransportationResearch Part C (8), 337359.

Kang, M.S., Srivastava, P., Fulton, J.P., Tyson, T., Owsley, W.F., Yoo,

K.H., 2006. Optimal poultry litter management throughGIS-based transportation analysis system. Journal of KSAE 48(7), 7386.

Kingery, W.L., Wood, C.W., Delaney, D.P., Williams, J.C., Mullins,G.L., 1994. Impact of long-term land application of broilerlitter on environmentally related soil properties. Journal ofEnvironmental Quality 23, 139147.

McDowell, R.W., Sharpley, A.N., Beegle, D.B., Weld, J.L., 2001.Comparing phosphorus management strategies at awatershed scale. Journal of Soil and Water Conservation 56(4), 306315.

McKinley, B., Broome, M., Oldham, L., 2000. Poultry NutrientManagement Through Livestock Feedstuffs. Mississippi StateUniversity Extension Service, M1146.

Miles, T.R., Bock, B.R., 2006. North Alabama integrated poultry

and ethanol production (IPEP) feasibility study. NRCS GrantAgreement 68-3A75-3-144.

Mitchell, C.C., Donald, J.O., 1995. The value and use of poultrymanures as fertilizer. Alabama Cooperative Extension System(ACES) Cir. No. ANR 244. Auburn University, AL.

Mitchell, C.C., Tu, S., 2005. Long-term evaluation of poultry litteras a source of nitrogen for cotton and corn. Agronomy

Journal, American Society of Agronomy 97, 399407.Mitchell, C.C., Tyson, T.W., 2001. Nutrient management planning

for small AFOs: Broiler operations. Alabama CooperativeExtension System (ACES), ANR-0926, Timely Information,ETP220-01-00, 114.

MySQL AB, 2006. MySQL: the worlds most popular open sourcedatabase. Available at http://www.mysql.com, Uppsala,Sweden.

Ochola, W.O., Kerkides, P., 2004. An integrated indicator-basedspatial decision support system for land quality assessmentin Kenya. Computers and Delectronics in Agriculture 45, 326.

Paz, J.O., Batchelor, W.D., Pedersen, P., 2004. WebGro: a web-basedsoybean management decision support system. Agronomy

Journal, American Society of Agronomy 96, 17711779.Reichert, P., Borsuk, M., Hostmann, M., Schweizer, S., Sporri, C.,

Tockner, K., Truffer, B., 2007. Concepts of decision support forriver rehabilitation. Environmental Modelling & Software 22(2), 188201.

Ritter, F.W., 2000. Potential impact of land application of

by-products on ground and surface water quality: 263288. In:Power, J.F., Dick, W.A. (Ed.), Land Application of Agriculture,Industrial, and Municipal By-Products, SSSA Book Ser. 6,SSSA, Madison, WI.

Rudner, M., Biedermann, R., Schroder, B., Kleyer, M., 2007.Integrated grid based ecological and economic (INGRID)landscape modela tool to support landscape managementdecisions. Environmental Modelling & Software 22 (2),177187.

Schluter, M., Ruger, N., 2007. Application of a GIS-basedsimulation tool to illustrate implications of uncertainties forwater management in the Amudarya River Delta.Environmental Modelling & Software 22 (2), 158166.

Sims, J.T., 1987. Agronomic evaluation of poultry manure as anitrogen source for conventional and no-tillage corn.

Agronomy Journal, American Society of Agronomy 79,563670.

Steiner, J.J., Minoura, T., Imaeda, M., 2006. An automatedtemplate approach for generating web-based conservationplanning worksheets. Agronomy Journal, American Society ofAgronomy 98, 11811186.

USDA National Agricultural Statistics Service (USDA-NASS), 2005.Alabama agricultural statistics bulletin 47: Poultry review2005. USDA national Agricultural Statistics Service AlabamaField Office, 3942.

USDA Natural Resources Conservation Service (USDA-NRCS),2001. Phosphorus index for Alabama: A planning tool toassess & manage P movement. USDA Natural ResourcesConservation Service, Agronomy Technical Note (AL-72),Auburn, Alabama.

Wood, C.W., Torbert, H.A., Delaney, D.P., 1993. Poultry litter as afertilizer for Bermuda grass: effects on yield and quality.

Journal of Sustainable Agriculture 3 (2), 2135.
http://www.mysql.com/http://www.mysql.com/

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