Jianfeng Zhou

Effect of catching surface and tilt angle on bruise damage of sweet cherry due to mechanical impact

Mechanical impact force of fruits is determined by drop height and catching surface.Sufficient sickness of cushion material is required to reduce bruise damage.Fruit bruise damage area is affected heavily by drop height and catching surface.Tilt angle of catching surfaces reduces fruit bruise damage substantially. Fruit bruise damage induced by mechanical impact is the most critical obstacle for the application of mechanical harvesting on fresh-market sweet cherries. One of main sources of fruit bruise is the mechanical impact by fruit catching surfaces occurring in fruit collection during mechanical harvesting. The goal of this research was to investigate the effect of cushion material, fruit drop height, and tilt angle of catching surface on fruit bruise damage. Three catching surfaces with five tilt angles from 0? to 60? were used to catch fruits freely dropped from heights of 0.3-2.1m. The impact force and deformation of cushion materials was measured by a force sensing unit and a high speed camera, respectively. Results showed that maximum impact force increased linearly with drop height and was reduced by cushion materials with sufficient thickness. The fruit damage percentages of cushion material 1 and 2 were 25.0-89.0% and 72.0-100.0% less than that of non-cushion material at drop height of 0.3-2.1m at 0? tilt angle, respectively. Results also shown catching surfaces with tilt angle reduced bruise damage substantially. Damage percentage of catching surfaces at 60? tilt angle was around 75.0% less than that at 0? non-cushion and cushion material when fruit were dropped from 1.5m. The results show that catching surfaces with cushion materials at a tilt angle of 60? might be a promise for mechanical harvesting of fruits with low fruit bruise damage.

Evaluation of water-use efficiency in foxtail millet (Setaria italica) using visible-near infrared and thermal spectral sensing techniques

Water limitations decrease stomatal conductance (g(s)) and, in turn, photosynthetic rate (A(net)), resulting in decreased crop productivity. The current techniques for evaluating these physiological responses are limited to leaf-level measures acquired by measuring leaf-level gas exchange. In this regard, proximal sensing techniques can be a useful tool in studying plant biology as they can be used to acquire plant-level measures in a high-throughput manner. However, to confidently utilize the proximal sensing technique for high-throughput physiological monitoring, it is important to assess the relationship between plant physiological parameters and the sensor data. Therefore, in this study, the application of rapid sensing techniques based on thermal imaging and visual-near infrared spectroscopy for assessing water-use efficiency (WUE) in foxtail millet (Setaria italica (L.) P. Beauv) was evaluated. The visible-near infrared spectral reflectance (350-2500 nm) and thermal (7.5-14 µm) data were collected at regular intervals from well-watered and drought-stressed plants in combination with other leaf physiological parameters (transpiration rate-E, A(net), g(s), leaf carbon isotopic signature-δ(13)C(leaf), WUE). Partial least squares regression (PLSR) analysis was used to predict leaf physiological measures based on the spectral data. The PLSR modeling on the hyperspectral data yielded accurate and precise estimates of leaf E, gs, δ(13)C(leaf), and WUE with coefficient of determination in a range of 0.85-0.91. Additionally, significant differences in average leaf temperatures (~1°C) measured with a thermal camera were observed between well-watered plants and drought-stressed plants. In summary, the visible-near infrared reflectance data, and thermal images can be used as a potential rapid technique for evaluating plant physiological responses such as WUE.

Efficacy of unmanned helicopter in rainwater removal from cherry canopies

Developed was an in-field sensing system to monitor cherry canopy micro-climate.Unmanned helicopter was evaluated for canopy rainwater removal.Effect of flight altitude and payloads on rainwater removal was quantified. Rain-induced fruit cracking causes significant economic loss for fresh market sweet cherry growers annually. To prevent cherry cracking, timely removal of rainwater from fruit is the key. This study evaluated the efficacy of an unmanned middle-size helicopter to remove rainwater from Y-trellised cherry canopies. Helicopter downwash in hover at four altitudes, with and without a payload, was quantified with six anemometers deployed in tree canopies. Results showed that payload and altitude significantly affected hover downwash, which was greater at higher altitude of 7.6m above ground level (AGL) than lower altitude of 4.9m AGL with payload. In the absence of payload, hover downwash peaked at the altitude of 6.1m AGL. In the efficacy study, 5.0-mm rainwater was applied to cherry canopies by a rainfall simulation system, followed by the helicopter flying over canopies at three altitudes (4.9, 5.5 and 6.1m AGL), two travel speeds (1.3 and 2.7ms-1) and with or without payload. Rainwater removal at bottom (1.1m), middle (1.9m) and top (2.7m) of the canopies was calculated based on the change of leaf wetness of target canopies in 10min after rain. Overall, helicopter with payload flying 2.7ms-1 at 6.1m AGL removed significantly more rainwater (96.3%) from top section of canopies than groups without treatment (71.2%) and compared to other payload and travel speed conditions. Results also confirmed that the unmanned helicopter could provide sufficient downwash to remove rainwater effectively from bottom and middle canopy sections.

Aerial multispectral imaging for crop hail damage assessment in potato

Aerial multispectral imaging is capable to assess crop hail damage in potato crops.Vegetation indices have potential to predict crop yield losses.Imaging within 10days after hail damage assists in quantifying damage levels.Hail damage during different growth stages can affect the recovery of potato crops. Crop loss assessment after an event of hailstorm can be inaccurate, subjective, and time consuming with the conventional method. Low-altitude, high-resolution aerial imaging using an unmanned aerial vehicle can be utilized for rapid assessment of target crops in a large scale, which can potentially improve the evaluation procedure. The goal of this study was to evaluate the feasibility of rapid and accurate assessment of crop damage due to simulated hailstorms using aerial multispectral imaging. Field experiments were conducted during two seasons in two potato varieties (Russet Norkotah, Ranger Russet) with three levels of mechanical defoliation (33%, 66%, and 99%) at three growth stages (tuber initiation, early bulk, and late bulk). All defoliation treatments were compared to the non-treated control plots (0% defoliation). Aerial multispectral images were collected between 77 and 108days after planting (0-60days after damage). Vegetation indices such as green normalized difference vegetation index (GNDVI), normalized difference vegetation index, and soil-adjusted vegetation index were calculated from replicate plots of different treatments. Results from two seasons showed similar trends in GNDVI values, with maximum effect of hail damage observed in early bulk stages. The mean GNDVI value was significantly lower in crops with the severe damage (99% defoliation) than others upon hail damage at the early bulk stage, with imaging after 10days after damage. The difference in GNDVI for crops with 33-66% damage could be detected within 10days after damage, and crop regrowth after that time period removed the effects of defoliation. The 99% defoliation damage at the early bulk stage also affected the crop yield significantly. Correlation analysis between vegetation indices and yield data indicated a strong relationship (r=0.77-0.90) for damage at the early bulk stage than other stages.

Dynamic Response of Sweet Cherry Tree to the Vibration of a Limb Shaker

To identify optimal vibration frequencies of a limb shaker for harvesting sweet cherry and the responding accelerations distributed on different limbs of a tree, a series of dynamic response tests were conducted on sweet cherry trees in orchard environment. Three varieties of cherry trees with different structures, including Bing with Y-trellis (Y-Bing), Skeena with Y-trellis (Y-Skeena) and Selah with upright fruiting offshoot (UFO-Selah), were tested in this investigation. Four to six limbs, including one being vibrated and the rests adjacent to the vibration limb, on each testing tree were selected as sample limbs. Three accelerometers were mounted at different locations on each limb to measure the acceleration responses to the vibration. The resonant frequencies were identified using frequency response function method. Obtained results showed that the resonant frequencies of Y-Skeena and UFO-Selah cherry trees had similar average values of 10.4, 15.7 and 22.6 Hz, while that of Y-Bing tree were higher at 12.4, 18.1 and 23.0 Hz. Analysis of acceleration generated under different vibration frequencies showed that the acceleration of shaker was only dependent on the input frequency. The ratios of average acceleration responses on the excited limbs and on its adjacent limbs were averaged at 6.6, 2.9 and 3.7 from Y-Bing, Y-Skeena and UFO-Selah cherry trees, respectively. This indicated that Y-Skeena trees with big diameter of limb were easier to get a whole tree vibration, while only little vibration could be obtained on the adjacent limbs of small size Y-Bing trees. The analysis of displacement showed that the peaks occurred near the resonant frequencies identified above. It also could be observed that small size tree generated large displacement.

Shaking Energy Delivery on Sweet Cherry Trees in Different Excitation Modes

To evaluate energy consumption and delivery patterns on fruit tree of a newly designed limb shaker for sweet cherry harvest, a set of dynamic tests were conducted on Y-trellis sweet cherry trees in orchard environment under different excitation modes. The energy consumption of the shaker was calculated based on the input power of the hydraulic motor. To understand the energy delivery patterns, a group of accelerometers were fixed on tested trees to obtain response information under different excitation modes. Each branch was divided into three ‘response zones’ according to its locations. Maximum kinetic energy of each ‘response zone’ of branches was calculated to study the tree energy response. Filed tests were conducted at excitation frequencies of 6, 10, 14 and 18 Hz with three excitation modes of Clamp, Impact[1] (with 1.3 cm clearance between branch and shaker), and Impact[2] (with 2.5 cm clearance between branch and shaker), respectively. Meanwhile, three locations (Low, Middle and High) in the excitation branch were chosen as the excitation points in these tests. Test results indicated that the excitation branch could obtain majority of the delivered kinetic energy in high excitation frequency. The excitation of Clamp could deliver largest amount of maximum kinetic energy to the tested trees in most conditions, while the percentage of that delivered to the excitation branch was the lowest and energy consumption of the shaker was the highest. At the excitation frequency of 14 Hz, the tested tree could obtain the total maximum kinetic energy of 2.14, 2.07 and 1.50 J, with 84.27%, 93.55%, and 93.93% of energy delivered to the excitation branch, and energy consumption of the shaker was 0.83, 0.79 or 0.74 kW, in excitation modes of Clamp, Impact[1], and Impact[2] respectively. Test results also indicated that the tested trees could obtain the highest maximum kinetic energy at Low point excitation, while the percentage of that delivered to the excitation branch was lower than that at the Middle point excitation, and the energy consumption of the shaker was the highest.

High-throughput field phenotyping in dry bean using small unmanned aerial vehicle based multispectral imagery

Abstract Phenotyping traits in large field crop trials with numerous breeding lines is an arduous task. Unmanned aerial vehicle (UAV) based remote sensing is currently being investigated for high-throughput agricultural field phenotyping applications. The system is conducive for rapid assessment of crop response to the environment, at a desired spatio-temporal resolution. Therefore, objective of this study was to evaluate such technology towards monitoring responses of dry bean lines to drought and low nitrogen stress (i.e., two trials and two seasons) under field conditions. A semi-automated image processing protocol was developed to extract features such as: (i) average green normalized difference vegetation index (GNDVI); and (ii) canopy area (total number of plant pixels) from individual plots. The data were acquired at mid-pod fill and late-pod fill growth stages in 2014 season, and at flowering, mid-pod fill, and late-pod fill growth stages in 2015 season. The relationships between remotely sensed image features with that of crop response variables such as seed yield, days to flowering, days to harvest maturity, days to seed fill, and biomass rating (for drought trial only) were assessed temporally. Overall, in drought experiment, both average GNDVI and canopy area were significantly correlated with seed yield in all trials at 5% level of significance. The average GNDVI and canopy area at flowering growth stages and average GNDVI at mid-pod fill stage were consistently highly correlated (r > 0.73) with seed yield. The average GNDVI at flowering (r of −0.54 to −0.73) and mid-pod fill (r of −0.52 to −0.73) stages was highly correlated with biomass rating. Thus, average GNDVI could possibly be used as a viable phenotype for capturing biomass differences as well. A pilot thermal imaging of the sample breeding plots in drought trials also indicated its potential in capturing the temperature differences resulting from stress. For the nitrogen stress experiment, the correlations between remotely sensed image features and response variables were lower than in the drought experiment. The nitrogen from vegetative growth did not effeciently partition into seed production, which could have resulted in low correlations.

A string twining robot for high trellis hop production

A full function multi-actuator prototype robot for high trellis hop twining was investigated.The prototype integrated three end-effectors, each of whose performance was evaluated separately.Function and reliability tests were conducted and their results reported. The hop plant is usually trained to grow on strings in commercial production. String twining is a labor intensive task in high trellis hop fields, and there is a high demand from industry to have the operation mechanized. In this study, an innovative string twining robot, comprising end-effectors for knot tying, string feeding, and trellis wire capturing was designed to perform this task autonomously. A laboratory-scale, proof of concept prototype, was fabricated to validate the performance and effectiveness of this robotic device and associated control algorithms. Functionality assessment tests verified that the string feeding end-effector could feed 6m length of string with acceptable variation. The trellis wire capturing end-effector could functionally achieve the required procedure for continuous twining. The comprehensive twining test proved that the integrated twining robot took approximately 11.2s to coordinate all three end-effectors to complete one string twining cycle with a moving forward speed of the mobile platform at 0.19ms-1. At this speed, the developed prototype robot achieved 97% of successful rate. The laboratory test results indicated that the developed prototype robot has the potential to be implemented for high trellis hop twining task.