msu-ceco/aec_v1 · Datasets at Hugging Face

text stringlengths 0 1.09k
Figure 2b presents the same map as in figure 2a.
The difference is that as the lateral travels around the pivot point individual sprinklers can be controlled in groups based on field position not on system plumbing.
At Position A, the same sprinklers included in blocks shown in figure 2a may be controlled as a block of individual sprinklers in figure 2b.
At Position B, a completely different sets of sprinklers can be combined together to match the zone contour at that location as precisely as was obtained at Position A.
The use of block or individual sprinkler types of control leads to areas of transition parallel and perpendicular to the travel direction of the irrigation machine.
The area impacted by the transition from one management zone to another is directly related to the wetted radius of the sprinklers installed on the system and the distance from the pivot point.
Although, several adjacent sprinklers may contribute to the application pattern and this may result is some application irregularities at various points of overlap, transition zones are more likely to conform to gradual changes in
Figure 2.
Schematic drawings of a soil survey map showing the implementation of the sprinkler block and individual sprinkler control approach to SS-VRI.
field conditions such as soil texture, topography, or soil physical properties.
Consequently, implementation of management zones and the evaluation of the impact of changes in application must be undertaken with the knowledge that the change is not instantaneous in space but rather a gradual transition from one zone to another.
The potential impacts of implementing these two approaches has yet to be documented in the field and likely will depend on the level of variation exhibited within management zones.
However, if the desire is to precisely match variable-sized and shaped management zones, the approach with the maximum amount of flexibility in sprinkler control would be best able to capitalize on the field-based information used in developing the management zone map.
With sprinkler spacing ranging from 2 to 6 m, the magnitude of the difference in terms of crop area depends on the distance from the pivot point.
Further, it is anticipated that individual sprinkler controls will require additional components that will potentially increase maintenance requirements in the long run.
One of the largest factors limiting the use of SS-VRI is cost, often ranging from $2000 for a system monitor to over $20,000 for control of individual sprinklers along the entire system length.
In some cases, producers are treating symptoms of low crop production such as leaf yellowing, leaf curling, and stunted plants by substituting SS-VRI technology when improved management of other inputs might be more beneficial in improving crop production and water use efficiency at a lower overall cost.
DISTRIBUTED NETWORKS AND COMMUNICATION PROTOCOLS
Site-specific variable-rate irrigation management allows producers to maximize their productivity while conserving water.
However, the seamless integration of sensors, data interface, software design, and communications for SS-VRI control using wireless sensorbased irrigation systems can be challenging (King et al.,
2000).
Researchers have addressed the issues of interfacing sensors and irrigation control using several approaches.
Shock et al.
used radio transmission for soil water data from in-field data loggers to a central data management site where decisions were made and manually changed by the operator.
Miranda et al.
used a closed-loop control system and determined irrigation amount based on distributed soil water measurements.
Wall and King explored various designs for smart soil water sensors and sprinkler valve controllers for implementing "plug-and-play" technology, and proposed architectures for distributed sensor networks for SS-VRI irrigation automation.
They concluded that the coordination of control and instrumentation data is most effectively managed using data networks and low-cost microcontrollers.
Adopting a standard interface for sensors and actuators allows reuse of common hardware and communication protocols such as communication interface and control algorithm software.
Instrumentation and control standards for RS232 serial and RS485 communication protocols have been widely applied and well documented for integrating sensors and actuators, particularly in industrial applications.
However, these systems require direct wire connections to transmit data between the control panel or microprocessor and the sensors or actuators.
The need for direct connection between the control and data acquisition systems poses a problem when applied to pivot irrigation systems due to the potential for damage and the cost of installation.
Wireless network systems are an alternative to hardwired systems for data transport and have been used for infield sensor network systems.
Two wireless protocols that eliminate the need for direct wire connections are Bluetooth and ZigBee .
Bluetooth and ZigBee are designed for radiofrequency telemetry applications that support a relatively low data rate, and provide solutions for long battery life and good network security.
ZigBee is a low-cost,
nonproprietary wireless mesh networking standard, which allows longer life with smaller batteries, and the directsequence spread spectrum mesh networking provides high reliability.
Bluetooth is a faster but more expensive standard than ZigBee and uses spread spectrum modulation technology called frequency hopping to avoid interference and ensure data integrity.
ZigBee has lower power needs than Bluetooth, but it also transmits effectively over less distance.
Enhanced Bluetooth transmitters are available that can transmit up to 1 km.
Bluetooth wireless technology has been adapted in sensing and control of agricultural systems.
Zhang evaluated Bluetooth radio in different agricultural environments, power consumption levels, and data transmission rates.
He observed 1.4 m as an optimal radio height for maximum 44-m radio range and reported limitations of significant signal loss after 8 h of continuous battery operation and 2 to 3 S of transmission latency with the increase of communication range.
Oksanen et al.
used a PDA with Bluetooth to connect a GPS receiver for their open, generic, and configurable automation platform for agricultural machinery.
Lee et al.
explored an application of Bluetooth wireless data transportation of moisture content of harvested silage and reported a limitation of 10-m short range.
However, the limitations of Bluetooth applications in agricultural systems can be solved or minimized by system design optimization.
The power shortage can be solved by using solar power that recharges the battery.
The radio range and transmission latency can also be extensively improved by using an upgraded power class and antenna.
These same techniques can be applied to Zigbee-based systems.
Drawbacks in using wireless sensors and wireless sensor networks include provision for ample bandwidth, existing inefficiencies in routing protocols, electromagnetic interference, interference by vegetation, radio range, sensor battery life , and synchronous data collection.
An immediate limiting factor in selfpowered wireless sensor network operation is battery life, which can be addressed to some degree by decreasing the duty cycle of the sensor nodes, which is typically a significant method for improving battery longevity.
Power needs are often mitigated by using solar panels.
Other identified challenges specific to WSNs and agriculture include interference with radio propagation due to crop canopy height.
Signal obstruction issues relating to crop height and in-field equipment are inherently reduced when the moving sprinkler is used as the sensor platform; but infield sensors require manual adjustment above crop canopy.
In row crop production systems, the need to install and retrieve the sensors, data loggers, and radio transmission equipment from each measurement site on an annual basis requires trained labor to ensure the equipment is handled, installed and removed properly.
Few producers possess the knowledge base necessary and rarely hire personnel who could perform these tasks reliably.
Consequently, future developments in wireless technology will need to include the semi-permanent and below-ground installation of
sensors and transmission equipment.
The addition of this requirement will require the development of WSNs with extended communication range and battery life sufficient to limit the replacement frequency to the level required to gain acceptance by center pivot managers.
SENSORS AND INTEGRATED DATA MANAGEMENT SCHEMES
One of the earliest and basic uses of sensors on a center pivot for management purposes was to determine alignment and lateral position.
Until recently, control systems based on the digital angle resolver typically had an accuracy of +0.5 to 1.5 of the first tower position.
Peters and Evett found that resolver-determined position errors could be as great as 5 or over 30 m on a 390-m system.
Consequently, many center pivot sprinkler manufacturers now employ a Wide-Area Augmentation System enabled GPS antenna option to identify the position of the end tower to an accuracy of less than 3 m.
With the WAAS enabled GPS antenna, accuracy of the outside tower position of less than 1 m can often be obtained because the long duration start-stop cycles of the system allow further buffering of GPS errors.
The net effect of being able to accurately determine the lateral location is that management zone size can be reduced without increasing the potential for a misapplication of water, nutrients, or pesticides.
Recent innovations in communication technologies combined with advances in internet technologies offer tremendous opportunities for development and application of real-time management systems for agriculture.
It is anticipated that DSS will increasingly rely on WSNs for real-time, automated recording of micro-meteorological instrumentation, or other sensors that are strategically distributed to provide continuous feedback of field conditions to center pivot control panels and field managers.
Sensors mounted on the irrigation lateral also can be used to provide real-time feedback for decision support as the system moves across a field.
Field-based data may also be integrated with various remotely sensed data to help differentiate between biotic and abiotic stresses.
Integrated data sources and networks provide needed information to recalibrate and check various simulation model parameters for on-the-go irrigation scheduling and adjustments.
Integration of these technologies into DSS can help determine when, where, and how much water to apply in real time, enabling implementation of advanced water conservation measures that can simultaneously address economic viability, crop production with limited water supplies, energy conservation, and enhanced environmental benefits.
Satellite and aerial imagery, GIS mapping services, and GPS are becoming commonplace throughout the agricultural industry around the world.
Remotely sensed information can be photometric , thermal, or multispectral and can be acquired by aircraft and satellites in a variety of formats and resolutions.
Multispectral data can be used to enhance water and energy conservation by helping to determine the causes of the non-uniform crop appearance and yield.
Advanced pattern-recognition software and other tools for multispectral or other remotely sensed data can be used to detect many problems in agriculture.
However, two barriers to the widespread adoption and use of these integrated technologies are the present cost of these services and the difficulty for producers to understand and use the output in a timely manner.
The timeliness of this type of information is critical to producers because it is much better for their farm profitability if they can make adjustments as the problems develop, not after the fact.
New analysis tools and interpretation aids as part of comprehensive DSS are needed for producers to take full advantage of these technologies.
Spectral and thermal ground-based remote sensors mounted on mechanical-move irrigation systems are capable of providing information to farmers in a timelier manner than aircraft or satellite sources.
Infrared thermocouple thermometers mounted on a moving lateral can provide radiometric temperature measurements of in-field crop canopies.
Software to control mechanical-move sprinkler systems has been integrated with this plant-feedback information and the Time-Temperature-Threshold algorithm, patented as the Biologically Identified Optimal Temperature Interactive Console for managing irrigation by the USDA under Patent No.
5539637.
Briefly, the TTT technique can be described as comparing the accumulated time that the crop canopy temperature is greater than a cropspecific temperature threshold with a specified critical time developed for a well-watered crop in the same region.
The TTT technique has been used in automatic irrigation scheduling and control of plant water use efficiency for corn in drip irrigated plots, and soybean and cotton in LEPA irrigated plots.
Peters and Evett demonstrated that remote canopy temperatures could be predicted from a contemporaneous reference temperature and a pre-dawn temperature measurement.
Infrared canopy temperature measurements made from a mechanical-move sprinkler system can then be used to develop spatial and temporal temperature maps that correspond to in-field water stress levels of crops.
Many electromagnetic soil water sensors based on soil bulk dielectric permittivity are available and can be incorporated into DSS for center pivot sprinkler irrigation systems.
Many resistance-based sensors are also available and could also be used with DSS.
Recent discussions of these types of sensors, their
accuracy and suitability for specific conditions have been provided by Evett et al.
and Chvez et al..
Integration of information collected at varying frequencies and spatial scales into DSS will be necessary to utilize all sources of information available for making improved irrigation management decisions.
The VARIwise model developed by McCarthy et al.
is a recent example of how data collected from a variety of sources can be incorporated into a DSS to manage center pivot water applications.
The Smart Crop system developed by Mahan et al.
is a recent commercial example of an in-field wireless system for canopy temperature monitoring.
Further development of this kind of management tool will be critical to the commercialization of DSS in the future.

Figure 2b presents the same map as in figure 2a.

The difference is that as the lateral travels around the pivot point individual sprinklers can be controlled in groups based on field position not on system plumbing.

At Position A, the same sprinklers included in blocks shown in figure 2a may be controlled as a block of individual sprinklers in figure 2b.

At Position B, a completely different sets of sprinklers can be combined together to match the zone contour at that location as precisely as was obtained at Position A.

The use of block or individual sprinkler types of control leads to areas of transition parallel and perpendicular to the travel direction of the irrigation machine.

The area impacted by the transition from one management zone to another is directly related to the wetted radius of the sprinklers installed on the system and the distance from the pivot point.

Although, several adjacent sprinklers may contribute to the application pattern and this may result is some application irregularities at various points of overlap, transition zones are more likely to conform to gradual changes in

Figure 2.

Schematic drawings of a soil survey map showing the implementation of the sprinkler block and individual sprinkler control approach to SS-VRI.

field conditions such as soil texture, topography, or soil physical properties.

Consequently, implementation of management zones and the evaluation of the impact of changes in application must be undertaken with the knowledge that the change is not instantaneous in space but rather a gradual transition from one zone to another.

The potential impacts of implementing these two approaches has yet to be documented in the field and likely will depend on the level of variation exhibited within management zones.

However, if the desire is to precisely match variable-sized and shaped management zones, the approach with the maximum amount of flexibility in sprinkler control would be best able to capitalize on the field-based information used in developing the management zone map.

With sprinkler spacing ranging from 2 to 6 m, the magnitude of the difference in terms of crop area depends on the distance from the pivot point.

Further, it is anticipated that individual sprinkler controls will require additional components that will potentially increase maintenance requirements in the long run.

One of the largest factors limiting the use of SS-VRI is cost, often ranging from $2000 for a system monitor to over $20,000 for control of individual sprinklers along the entire system length.

In some cases, producers are treating symptoms of low crop production such as leaf yellowing, leaf curling, and stunted plants by substituting SS-VRI technology when improved management of other inputs might be more beneficial in improving crop production and water use efficiency at a lower overall cost.

DISTRIBUTED NETWORKS AND COMMUNICATION PROTOCOLS

Site-specific variable-rate irrigation management allows producers to maximize their productivity while conserving water.

However, the seamless integration of sensors, data interface, software design, and communications for SS-VRI control using wireless sensorbased irrigation systems can be challenging (King et al.,

2000).

Researchers have addressed the issues of interfacing sensors and irrigation control using several approaches.

Shock et al.

used radio transmission for soil water data from in-field data loggers to a central data management site where decisions were made and manually changed by the operator.

Miranda et al.

used a closed-loop control system and determined irrigation amount based on distributed soil water measurements.

Wall and King explored various designs for smart soil water sensors and sprinkler valve controllers for implementing "plug-and-play" technology, and proposed architectures for distributed sensor networks for SS-VRI irrigation automation.

They concluded that the coordination of control and instrumentation data is most effectively managed using data networks and low-cost microcontrollers.

Adopting a standard interface for sensors and actuators allows reuse of common hardware and communication protocols such as communication interface and control algorithm software.

Instrumentation and control standards for RS232 serial and RS485 communication protocols have been widely applied and well documented for integrating sensors and actuators, particularly in industrial applications.

However, these systems require direct wire connections to transmit data between the control panel or microprocessor and the sensors or actuators.

The need for direct connection between the control and data acquisition systems poses a problem when applied to pivot irrigation systems due to the potential for damage and the cost of installation.

Wireless network systems are an alternative to hardwired systems for data transport and have been used for infield sensor network systems.

Two wireless protocols that eliminate the need for direct wire connections are Bluetooth and ZigBee .

Bluetooth and ZigBee are designed for radiofrequency telemetry applications that support a relatively low data rate, and provide solutions for long battery life and good network security.

ZigBee is a low-cost,

nonproprietary wireless mesh networking standard, which allows longer life with smaller batteries, and the directsequence spread spectrum mesh networking provides high reliability.

Bluetooth is a faster but more expensive standard than ZigBee and uses spread spectrum modulation technology called frequency hopping to avoid interference and ensure data integrity.

ZigBee has lower power needs than Bluetooth, but it also transmits effectively over less distance.

Enhanced Bluetooth transmitters are available that can transmit up to 1 km.

Bluetooth wireless technology has been adapted in sensing and control of agricultural systems.

Zhang evaluated Bluetooth radio in different agricultural environments, power consumption levels, and data transmission rates.

He observed 1.4 m as an optimal radio height for maximum 44-m radio range and reported limitations of significant signal loss after 8 h of continuous battery operation and 2 to 3 S of transmission latency with the increase of communication range.

Oksanen et al.

used a PDA with Bluetooth to connect a GPS receiver for their open, generic, and configurable automation platform for agricultural machinery.

Lee et al.

explored an application of Bluetooth wireless data transportation of moisture content of harvested silage and reported a limitation of 10-m short range.

However, the limitations of Bluetooth applications in agricultural systems can be solved or minimized by system design optimization.

The power shortage can be solved by using solar power that recharges the battery.

The radio range and transmission latency can also be extensively improved by using an upgraded power class and antenna.

These same techniques can be applied to Zigbee-based systems.

Drawbacks in using wireless sensors and wireless sensor networks include provision for ample bandwidth, existing inefficiencies in routing protocols, electromagnetic interference, interference by vegetation, radio range, sensor battery life , and synchronous data collection.

An immediate limiting factor in selfpowered wireless sensor network operation is battery life, which can be addressed to some degree by decreasing the duty cycle of the sensor nodes, which is typically a significant method for improving battery longevity.

Power needs are often mitigated by using solar panels.

Other identified challenges specific to WSNs and agriculture include interference with radio propagation due to crop canopy height.

Signal obstruction issues relating to crop height and in-field equipment are inherently reduced when the moving sprinkler is used as the sensor platform; but infield sensors require manual adjustment above crop canopy.

In row crop production systems, the need to install and retrieve the sensors, data loggers, and radio transmission equipment from each measurement site on an annual basis requires trained labor to ensure the equipment is handled, installed and removed properly.

Few producers possess the knowledge base necessary and rarely hire personnel who could perform these tasks reliably.

Consequently, future developments in wireless technology will need to include the semi-permanent and below-ground installation of

sensors and transmission equipment.

The addition of this requirement will require the development of WSNs with extended communication range and battery life sufficient to limit the replacement frequency to the level required to gain acceptance by center pivot managers.

SENSORS AND INTEGRATED DATA MANAGEMENT SCHEMES

One of the earliest and basic uses of sensors on a center pivot for management purposes was to determine alignment and lateral position.

Until recently, control systems based on the digital angle resolver typically had an accuracy of +0.5 to 1.5 of the first tower position.

Peters and Evett found that resolver-determined position errors could be as great as 5 or over 30 m on a 390-m system.

Consequently, many center pivot sprinkler manufacturers now employ a Wide-Area Augmentation System enabled GPS antenna option to identify the position of the end tower to an accuracy of less than 3 m.

With the WAAS enabled GPS antenna, accuracy of the outside tower position of less than 1 m can often be obtained because the long duration start-stop cycles of the system allow further buffering of GPS errors.

The net effect of being able to accurately determine the lateral location is that management zone size can be reduced without increasing the potential for a misapplication of water, nutrients, or pesticides.

Recent innovations in communication technologies combined with advances in internet technologies offer tremendous opportunities for development and application of real-time management systems for agriculture.

It is anticipated that DSS will increasingly rely on WSNs for real-time, automated recording of micro-meteorological instrumentation, or other sensors that are strategically distributed to provide continuous feedback of field conditions to center pivot control panels and field managers.

Sensors mounted on the irrigation lateral also can be used to provide real-time feedback for decision support as the system moves across a field.

Field-based data may also be integrated with various remotely sensed data to help differentiate between biotic and abiotic stresses.

Integrated data sources and networks provide needed information to recalibrate and check various simulation model parameters for on-the-go irrigation scheduling and adjustments.

Integration of these technologies into DSS can help determine when, where, and how much water to apply in real time, enabling implementation of advanced water conservation measures that can simultaneously address economic viability, crop production with limited water supplies, energy conservation, and enhanced environmental benefits.

Satellite and aerial imagery, GIS mapping services, and GPS are becoming commonplace throughout the agricultural industry around the world.

Remotely sensed information can be photometric , thermal, or multispectral and can be acquired by aircraft and satellites in a variety of formats and resolutions.

Multispectral data can be used to enhance water and energy conservation by helping to determine the causes of the non-uniform crop appearance and yield.

Advanced pattern-recognition software and other tools for multispectral or other remotely sensed data can be used to detect many problems in agriculture.

However, two barriers to the widespread adoption and use of these integrated technologies are the present cost of these services and the difficulty for producers to understand and use the output in a timely manner.

The timeliness of this type of information is critical to producers because it is much better for their farm profitability if they can make adjustments as the problems develop, not after the fact.

New analysis tools and interpretation aids as part of comprehensive DSS are needed for producers to take full advantage of these technologies.

Spectral and thermal ground-based remote sensors mounted on mechanical-move irrigation systems are capable of providing information to farmers in a timelier manner than aircraft or satellite sources.

Infrared thermocouple thermometers mounted on a moving lateral can provide radiometric temperature measurements of in-field crop canopies.

Software to control mechanical-move sprinkler systems has been integrated with this plant-feedback information and the Time-Temperature-Threshold algorithm, patented as the Biologically Identified Optimal Temperature Interactive Console for managing irrigation by the USDA under Patent No.

5539637.

Briefly, the TTT technique can be described as comparing the accumulated time that the crop canopy temperature is greater than a cropspecific temperature threshold with a specified critical time developed for a well-watered crop in the same region.

The TTT technique has been used in automatic irrigation scheduling and control of plant water use efficiency for corn in drip irrigated plots, and soybean and cotton in LEPA irrigated plots.

Peters and Evett demonstrated that remote canopy temperatures could be predicted from a contemporaneous reference temperature and a pre-dawn temperature measurement.

Infrared canopy temperature measurements made from a mechanical-move sprinkler system can then be used to develop spatial and temporal temperature maps that correspond to in-field water stress levels of crops.

Many electromagnetic soil water sensors based on soil bulk dielectric permittivity are available and can be incorporated into DSS for center pivot sprinkler irrigation systems.

Many resistance-based sensors are also available and could also be used with DSS.

Recent discussions of these types of sensors, their

accuracy and suitability for specific conditions have been provided by Evett et al.

and Chvez et al..

Integration of information collected at varying frequencies and spatial scales into DSS will be necessary to utilize all sources of information available for making improved irrigation management decisions.

The VARIwise model developed by McCarthy et al.

is a recent example of how data collected from a variety of sources can be incorporated into a DSS to manage center pivot water applications.

The Smart Crop system developed by Mahan et al.

is a recent commercial example of an in-field wireless system for canopy temperature monitoring.

Further development of this kind of management tool will be critical to the commercialization of DSS in the future.