The present application provides a method and system for dynamically predicting a deoxynivalenol content of wheat at harvest, including: on the basis of historical data, screening out by particle swarm optimization algorithm combined factors suitable for establishing a prediction model, and establishing the prediction model by using the combined factors; on the basis of data of a current year, predicting a second flowering date and a second harvest date of wheat in the current year by an agricultural model; then obtaining a weather forecast on the basis of the second flowering date and the second harvest date, and combining the weather forecast and geographic data into correlated factors; and finally predicting the deoxynivalenol content of wheat at harvest by means of the prediction model and the correlated factors. Compared with the prior art, statistical items in the prediction model are more comprehensive, and growth period data of the current year can be dynamically predicted on the basis of growth period indexes model, thus continuously adjusting and establishing the prediction model. In addition, an overhead time for screening multi-dimensional large-batch data by the particle swarm optimization algorithm has more advantages, and the prediction model established by a multiple linear regression algorithm has higher precision.

The present application provides a method and system for dynamically predicting a deoxynivalenol content of wheat at harvest, including: on the basis of historical data, screening out by particle swarm optimization algorithm combined factors suitable for establishing a prediction model, and establishing the prediction model by using the combined factors; on the basis of data of a current year, predicting a second flowering date and a second harvest date of wheat in the current year by an agricultural model; then obtaining a weather forecast on the basis of the second flowering date and the second harvest date, and combining the weather forecast and geographic data into correlated factors; and finally predicting the deoxynivalenol content of wheat at harvest by means of the prediction model and the correlated factors. Compared with the prior art, statistical items in the prediction model are more comprehensive, and growth period data of the current year can be dynamically predicted on the basis of growth period indexes model, thus continuously adjusting and establishing the prediction model. In addition, an overhead time for screening multi-dimensional large-batch data by the particle swarm optimization algorithm has more advantages, and the prediction model established by a multiple linear regression algorithm has higher precision.

Apparatus and associated methods relate to presenting for selection services comprising at least one bundled set of healthcare services to be performed separately by respective providers, determining a bundle price for the at least one bundled set of healthcare services, and in response to receiving payment in an amount of the bundle price, generating a purchase data record selectively redeemable to receive each of the at least one bundled set of healthcare services, and transmitting a unique confirmation number generated for the purchase data record. One or more service of the bundled set may be a dental or veterinary service. The bundle price may be based on a location or time at which at least one service will be performed and may be determined using a user's remaining insurance deductible. Payment may be disbursed to multiple providers of the bundled set of healthcare services. A payment may be virtual funds.

A method, apparatus and system is provided for assessing risk for well completion, comprising: obtaining, using an input interface, a Below Rotary Table hours and a plurality of well-field parameters for one or more planned runs, determining, using at least one processor, one or more non-productive time values that correspond to the one or more planned runs based upon the well-field parameters, developing, using at least one processor, a non-productive time distribution and a Below Rotary Table distribution via one or more Monte Carlo trials; and outputting, using a graphic display, a risk transfer model results based on a total BRT hours from the Below Rotary Table and the non-productive time distribution produced from the one or more Monte Carlo trials.

A method, apparatus and system is provided for assessing risk for well completion, comprising: obtaining, using an input interface, a Below Rotary Table hours and a plurality of well-field parameters for one or more planned runs, determining, using at least one processor, one or more non-productive time values that correspond to the one or more planned runs based upon the well-field parameters, developing, using at least one processor, a non-productive time distribution and a Below Rotary Table distribution via one or more Monte Carlo trials; and outputting, using a graphic display, a risk transfer model results based on a total BRT hours from the Below Rotary Table and the non-productive time distribution produced from the one or more Monte Carlo trials.

A work vehicle includes a cutter device for cutting plant in a field, a storage section for storing plant cut by the cutter device, an inclination angle sensor for detecting an inclination angle ((θd)) of the vehicle body, a display device for displaying the inclination angle detected by the inclination angle sensor, and a reporting device for reporting the inclination angle exceeding a permissible inclination angle ((θa)).

A work vehicle includes a cutter device for cutting plant in a field, a storage section for storing plant cut by the cutter device, an inclination angle sensor for detecting an inclination angle ((θd)) of the vehicle body, a display device for displaying the inclination angle detected by the inclination angle sensor, and a reporting device for reporting the inclination angle exceeding a permissible inclination angle ((θa)).

Techniques are provided for generating target success group of hybrid seeds for target fields include a server receiving agricultural data records that represent crop seed data describing seed and yield properties of hybrid seeds and first field geo-location data for agricultural fields where the hybrid seeds were planted. The server receives second geo-locations data for target fields where hybrid seeds are to be planted. The server generates a dataset of hybrid seed properties that include yield values and environmental classifications for hybrid seeds and then a dataset of success probability scores that describe the probability of a successful yield on the target fields based on the dataset of hybrid seed properties and the second geo-location data. The server generates target success yield group of hybrid seeds and probability of success values based on success probability scores and a yield threshold. The server causes display of the target success yield group.

Techniques are provided for generating target success group of hybrid seeds for target fields include a server receiving agricultural data records that represent crop seed data describing seed and yield properties of hybrid seeds and first field geo-location data for agricultural fields where the hybrid seeds were planted. The server receives second geo-locations data for target fields where hybrid seeds are to be planted. The server generates a dataset of hybrid seed properties that include yield values and environmental classifications for hybrid seeds and then a dataset of success probability scores that describe the probability of a successful yield on the target fields based on the dataset of hybrid seed properties and the second geo-location data. The server generates target success yield group of hybrid seeds and probability of success values based on success probability scores and a yield threshold. The server causes display of the target success yield group.

An agriculture support device includes a traveling creator to create a scheduled traveling route of an agricultural machine in an agricultural field, a display controller to display on an external terminal a virtual traveling status of the agricultural machine to travel on the scheduled traveling route created by the traveling creator, and a correction permitting controller to permit correction of the scheduled traveling route created by the traveling creator when the external terminal requests the correction. The display controller displays, on the external terminal, the virtual traveling status and a result traveling status of the agricultural machine that has traveled on the scheduled traveling route.