Study of force distribution in the citrus tree canopy during harvest using a continuous canopy shaker

Mechanical harvesting is increasingly being employed in the citrus industry of Florida because of the faster and efficient harvesting it provides with comparatively lower cost when compared to manual harvesting. Continuous canopy shakers are the only mechanical harvesters commercially used in Florida. The main concerns regarding the use of these machines are damage to tree and detrimental effect on next year yield. Because of these concerns, only a very low percentage (6-7%) of the acreage is being harvested mechanically. To improve these machines and address the growers’ concerns, experiments were conducted to study the force and acceleration distribution on the tree branches and fruits. The acceleration was measured at different locations in the canopy using tri-axis accelerometers attached to the branch and data was recorded using ZigBee^® transceivers. The distribution of force and acceleration along an individual branch in trees of two different sizes were studied at three different tine angles and frequencies of the shaker. Both distributions were modeled using the Curve Fitting Toolbox™ of Matlab^®. The results suggested that the force was higher for the fruits inside the canopy than the ones at the edges. It was also observed that the maximum force required to remove the fruit mechanically was only 18% of the traditionally measured fruit detachment force. The force along the branch was found to be Gaussian in nature and the acceleration along the branch was found to be exponential.     

Data acquisition system for soil-tire interface stress measurement

In today’s production agriculture industry, a renewed interest has been placed on input costs and energy efficiency. The fact that the soil-tire interface of a tractive vehicle is inherently inefficient is widely known but not widely understood. To support evaluation of the soil-tire interface a measurement system was created to sense the normal stress at the interface of the tire and soil. To acquire and log the data from this sensor array, a unique data acquisition system was developed and is presented in this paper. The system utilized a microcontroller to process and write data to a compact flash card from a total of 56 analog channels. It also used a two-dimensional accelerometer to determine the angular position of the vehicle tire and the attached sensors. Custom data acquisition software was developed to log the data to the compact flash card in an efficient, organized manner. Results confirmed that the data acquisition system was capable of operating at 887 Hz per-channel analog sampling frequency. Data from field testing illustrated the capability of the accelerometer to determine wheel angular rotation and associate the applied normal stress with that angular rotation. Results also confirmed the capability of the data acquisition system to estimate the rotational angle of contact of the tire while engaging soil.     

Relationship between the timing of insemination based on estrus detected by the automatic activity monitoring system and conception rates using sex-sorted semen in Holstein dairy cattle

We investigated the optimal timing of artificial insemination (AI) for achieving pregnancy according to the onset/end of estrus detected by an accelerometer system in Holstein cattle. The conception rates of conventional semen were used as a reference. The conception rate from AI of sex-sorted semen was higher at −4 to 4 h (57.1%) from the end of estrus than those at −12 to −4 h (37.7%) and 12–20 h (30.3%), whereas AI at 4–12 h showed an intermediate conception rate (47.4%). Conversely, conception rates were similar in AI performed between 0 and 32 h from the onset of estrus. Regarding conventional semen, the interval from the onset and end of estrus did not affect conception rates. The present results suggest that the time of the end of estrus is the better indicator of optimal AI timing for sex-sorted semen than the onset of estrus.     

Development of the Berry Impact Recording Device sensing system: Hardware design and calibration

Bruising caused by the impact damage occurs frequently during mechanical harvest process for highbush blueberries. The overall goal of this study was to develop a miniature and low-cost sensor prototype to quantitatively measure the impact forces endured by blueberries during the mechanical harvest process, which could be used to reduce blueberry bruising through improved harvester design. The sensing system developed in this study had three essential components: the sensor, the interface box, and the computer software program. The round circuit board of sensor is less than one inch (19.4 mm), including three accelerometers with ±500 g sensing range in each orthogonal axis, one eight-bit microcontroller, one 128 KB memory chip, and other electronic components with low power consumption. The sensor board and rechargeable battery were cast into a one inch (25.4 mm) sphere using silicone rubber. The interface box serves as the intermediate communication platform to connect the sensor and the computer. The PC-software retrieves data from the sensor via the I²C communication and downloads data to a computer for further analysis via the RS232 communication. The sensor was calibrated using a centrifuge. The accuracy of the sensor output was 0.53% (2.60 g maximum deviation) and −0.33% (−1.26 g maximum deviation), with precision error of 0.63% (3.21 g) in the output span. This miniature and low-cost sensor prototype provides the opportunity to understand how the berry (or other small fruits) interacts with different machine parts within the harvester and to identify critical control points that cause the most mechanical impacts, which was not achievable in the past.     

Development of the Berry Impact Recording Device sensing system: Software

This paper reports a complete impact data acquisition, processing, and analyzing software system that applies on the hardware platform of the Berry Impact Recording Device (BIRD). The software has three major sections that correspond to the hardware: The BIRD sensor program, the interface box program, and the computer software i-BIRD. The sensor program samples acceleration data from three axes and records them as single impacts with a maximum sampling rate of 3.0 kHz. Users can configure the sensor via the i-BIRD computer software, with different options of sampling frequencies (682-3050 Hz) and thresholds (0-205 g, where g is the gravitational acceleration). The data recorded can be downloaded, processed and graphically displayed on the computer. A real time clock was created using the interrupt service routine provided by the microcontroller. The accuracy of the sensor’s clock was calibrated with an error of 0.073%, which was adequate to record impact data in this application. The shape of impact curves recorded by the BIRD sensor at three sampling frequencies (682, 998, and 1480 Hz) matched well with the curves recorded by a high frequency (10 kHz) data logger with the maximum root mean squared error of 4.4 g. The velocity change had a relative error less than 5%. With confirmation of all those performances, the software system enabled the BIRD to be a useful tool to collect impact data during small fruit (such as blueberry) mechanical harvest.     

Sows’ activity classification device using acceleration data - A resource constrained approach

This paper discusses the main architectural alternatives and design decisions in order to implement a sows’ activity classification model on electronic devices. The different possibilities are analyzed in practical and technical aspects, focusing on the implementation metrics, like cost, performance, complexity and reliability. The target architectures are divided into: server based, where the main processing element is a central computer; and embedded based, where the processing is distributed on devices attached to the animals. The initial classification model identifies the activities performed by the sows using a multi-process Kalman filter having, as input, 3-axes data from accelerometers. However, the power demanding hardware resources to run the filters require frequent battery recharges, making its use unsuitable in the current state-of-the-art. It motivated the development of a heuristic classification approach, focusing on the resource constrained characteristics of embedded systems. The new approach classifies the activities performed by the sows with accuracy close to 90%. It was implemented as a hardware module that can easily be instantiated to provide preprocessed information to models in order to detect important situations in the sows’ life, e.g. the onset of farrowing.     

加速度计质量和安装位置对木材材料常数测试值的影响分析北大核心

为考察加速计质量和安装位置对木材测试频率的影响,设计了用自由梁和悬臂梁测试一阶弯曲频率以及用自由板测试一阶扭转频率的试验方案。根据能量法和振型推导出适用于计入加速计质量和安装位置影响的弹性模量和自由梁、悬臂梁的一阶弯曲频率的修正关系式以及剪切模量和自由板一阶扭转频率的修正关系式。应用加速度计为传感器实测了西加云杉梁、板和定向刨花板(OSB)沿其长度方向的一阶弯曲频率和一阶扭转频率,验证了导出的修正关系式应用于测试材料弹性模量和剪切模量的有效性,并以加速度计质量m和试件质量M之比m/M为参数,探讨了上述导出的修正关系式的适用范围。