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Biosystems Engineering

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ISSN (Print) 1537-5110 - ISSN (Online) 1537-5129
Published by Elsevier

[2564 journals]

Machine vision techniques for the evaluation of seedling quality based on leaf area
- Abstract: Publication date: Available online 21 May 2013
  Source:Biosystems Engineering
  Author(s): Jun H. Tong , Jiang B. Li , Huan Y. Jiang
  Highly efficient automated transplanters in greenhouses are of great convenience to growers. These tools perform various tasks, including the removal of bad plugs and the fixing of empty cells in plug trays. Leaf area of a seedling is an important indicator of its quality. Here, a vision system was used to measure the leaf area in each cell to distinguish “bad” and “good” plugs. Based on the principle of proportion in area, the procedures for processing top-view seedling images and a method for calculating each the leaf area of each seedling in the plug tray were investigated. Overlapping of the leaves across the surface of the cell resulted in failures in identification, which is a key point to be resolved. A decision method combining the region centre of cross-border leaves, and a methodology for the improved watershed segmentation for overlapping leaf (OL) images, were developed. Seedlings of tomato, cucumber, aubergine and pepper, at suitable transplanting stages, were used to test the efficacy of the quality evaluation program. Through the segmentation of 40 seedling images (10 for each vegetable seedling), the improved watershed segmentation lessened the initial partitions by 45–55% compared with the conventional watershed algorithm. The OLs were successfully segmented. The relative identification accuracy of seedling quality was 98.6%, 96.4%, 98.6% and 95.2% for tomato, cucumber, aubergine and pepper, respectively. The errors were mainly attributed to horticultural practices. The results showed that this system of identifying seedling quality was suitable for application in automated transplanters.
  Graphical abstract Highlights ► An imaging system evaluated seedling quality in plug tray based on leaf area. ► Grey-image processing method resolved the over-segmentation problem of watersheds. ► Improved watershed algorithm segmented overlapped leaves from neighbouring cells. ► A blob analyse algorithm calculated a cell's leaf area including extruding leaves.
  
  PubDate: 2013-05-22T23:05:53Z
Microwave dielectric method for the rapid, non-destructive determination of bulk density and moisture content of peanut hull pellets
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Samir Trabelsi , Ana M. Paz , Stuart O. Nelson
  A rapid dielectric-based method was used to non-destructively determine the moisture content and bulk density of peanut-hull pellets from free-space measurement of their dielectric properties at microwave frequencies. For moisture content determination, a permittivity-based function was used that permits moisture prediction independent of bulk density from measurement of the dielectric properties at microwave frequencies. For bulk density determination, an analytical expression was obtained from a representation of the dielectric properties in the complex plane. Results of moisture and density prediction from measurement of the dielectric properties are shown at 5, 10, and 15 GHz at 22 °C.
  
  PubDate: 2013-05-22T23:05:53Z
Improving the airflow distribution in a multi-belt conveyor dryer for spice plants by modifications based on computational fluid dynamics
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Martin Böhner , Isabel Barfuss , Albert Heindl , Joachim Müller
  The problem of uneven drying over the belt width in belt dryers is a consequence of inadequate air distribution leading to decreased throughput and high energy requirements. To achieve system optimisation, computational fluid flow simulations were conducted. A problem was discovered in the air distribution to both sides of the dryer, due to the incorrect angle of an adjustable distribution flap. When the angle was adjusted to 45°, the air mass flows from both sides were equal. Furthermore the air distribution across the belt width was inhomogeneous, studied by measurements of the air temperature and product moisture distribution. The simulation of the airflow led to the addition of air guiding plates. The influence of the guiding plates adjoining the drying chamber was confirmed by the fluid path length of the hot air. The study resulted in an optimised airflow over the drying area and uniform product moisture content.
  
  PubDate: 2013-05-22T23:05:53Z
An operative approach for designing and optimising a pipeline network for slurry collection from dairy farms across a wide geographical area
- Abstract: Publication date: Available online 22 May 2013
  Source:Biosystems Engineering
  Author(s): Marco Bietresato , Dario Friso , Luigi Sartori
  A pipeline network that collects and transports animal wastes to a treatment plant (e.g., a digester) is an interesting alternative to vehicles (no traffic increase, −61.31% CO2 emissions, −42.46% energy consumption in the case study presented here). However, pipeline networks require careful design to minimise installation costs, costs that depend on pipe length more than diameter. The optimisation can therefore be modelled as a “Euclidian Steiner minimum tree” problem that can be solved by using Kruskal's and Simpson's algorithms respectively to delineate a preliminary minimum-spanning-tree path and to optimise the paths by introducing new bifurcation points. The presented case study involved 32 dairy farms belonging to a milk consortium in a 1000-km2 area. The proposed procedure resulted in a network that extended 98.75 km. However, this was reduced to 97.47 km by introducing additional branching points (total length −1.30%, locally up to −8.54%). Another possibility for cost minimisation is to select farms based on their position. If only farms within 20 km from the centre were considered, the network length decreases to 69.25 km and was optimised to 67.97 km (−1.84%). Although the decreases achieved by optimisation were small, they fall within the estimated range (μ = 2.35%, σ = 1.24%) and correspond to 73 632 € and 76 696 € in investment savings. Economically speaking, selecting farms is more efficient with −30.15% of the investment and annual costs and −21.83% of the cost-per-mass-unit. The universality and versatility of the algorithms used makes the proposed approach suitable for designing piping networks in extended geographical areas.
  Highlights ► The cost of a pipe network for moving slurry depends mainly by its length and not by flow rate. ► Kruskal's and Simpson's algorithms were used to design and optimise a network. ► The study involves 32 dairy farms in a 1000-km2 area; the 1st network length was 98.7 km. ► The length was then reduced by 1.30% (range 2.35 ± 1.24%), the total cost by 76 696 €. ► Possibility for minimising annual/unit costs (−30%/−22%) by selecting farms within 20 km from the centre.
  
  PubDate: 2013-05-22T23:05:53Z
The effect of condensed distillers solubles on the physical and chemical properties of maize distillers dried grains with solubles (DDGS) using bench scale experiments
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Kyle V. Probst , Klein E. Ileleji , R.P. Kingsly Ambrose , Clairmont L. Clementson , Arnoldo A. Garcia , Cedric A. Ogden
  This study was undertaken to understand the effect of variable quantities of condensed distillers solubles (CDS) mixed with wet distillers grains (WDG) from maize on the physical and chemical characteristics of distillers dried grains with solubles (DDGS) using a bench-scale experiment. DDGS produced with 0, 10 and 20% CDS by percentage mass showed that particle size, particle size distribution, and particle density increased with CDS levels from 0 to 20%. DDGS with varying CDS levels had significantly different amounts of crude protein, crude fat, ash, total reducing sugars and amino acids. The chemical composition of DDGS in this study and a plant-scale study by Kingsly et al. (2010) were comparable, but not their physical characteristics. Therefore, caution should be taken when preparing DDGS samples for use in studying granular properties using bench-scale experiments which have been used by others in previous studies. An empirical model was developed to predict the chemical composition of DDGS based on the chemical composition of its two wet streams.
  Highlights ► Physical/chemical characteristics of DDGS from bench/plant-scale studies compared. ► Limitation of using bench-scale studies was in the physical properties. ► Chemical properties of DDGS were comparable across both bench and plant scales. ► DDGS add-back (recycle) important during DDGS drying at the plant scale. ► Model developed to predict chemical property of DDGS based on feedstock streams.
  
  PubDate: 2013-05-18T23:05:27Z
Tree stability in winds: Measurements of root plate tilt
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Ken James , Craig Hallam , Chris Spencer
  Tree stability in winds was evaluated by measuring the tilt of the root plate using newly developed instruments that attached to the trunk at ground level. During periods of high winds, tilt sensors recorded data on the dynamic flexure of a tree's root plate which was used to assess the anchorage strength of the tree in the ground. The root plate tilt of 250 trees at 30 sites in Victoria, Australia was measured under natural wind conditions from November 2010 to August 2012. The maximum root plate tilt values recorded were 0.90° on an Eucalyptus obliqua and 0.88° on an Eucalyptus rubida. These data were recorded during strong winds on 11 June 2011 for E. rubida and on 5 September 2012 for both trees. The majority of trees (96%) recorded tilt values below 0.50°, even in high winds. No trees failed during this study and 11 trees (4%) recorded maximum tilt values above 0.50°. Static pull tests on 10 trees were conducted to determine root plate tilt under controlled loading and to obtain tilt values for comparison to wind induced tilt data. Tilt data of tree root plates in winds is discussed in relation to anchorage strength in the ground and tree stability. No trees in this study failed even though several strong winds occurred during which tree failures were reported in nearby localities. Further work is needed to measure tilt values during tree failure in wind, in order to establish the limits of tilt that will define tree stability.
  Highlights ► Tilt of tree root plates in high winds to assess tree stability. ► Tilt values from trees subject to winds and static load tests. ► Experimental results from trees failing in winds has not yet been reported. ► Static load tests may not represent dynamic wind loading. ► Measuring root plate tilt is a useful method to assess tree stability in winds.
  
  PubDate: 2013-05-18T23:05:27Z
Modelling ventilation rate, balance temperature and supplemental heat need in alternative vs. conventional laying-hen housing systems
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Yang Zhao , Hongwei Xin , Timothy A. Shepherd , Morgan D. Hayes , John P. Stinn
  An Excel-based spreadsheet model has been developed to delineate ventilation rate (VR), supplemental heat need (H s), balance temperature (t bal, outdoor temperature below which H s is required to maintain the desired indoor temperature), energy use and cost for H s in alternative (aviary and enriched colony) vs. conventional cage laying-hen houses. The model was applied to the Midwestern U.S. housing characteristics (same land footprint) and winter weather conditions (−30°C to 5°C ambient temperature, and a constant relative humidity or RH of 70%). Effects of hen stocking density, target indoor temperature and RH (t i, RHi), building insulation, and light period vs. dark period on VR, t bal and H s were examined. For the housing characteristics considered and target indoor condition of 25°C and 60% RH, t bal for the alternative housing systems was found to be 2.0–2.6°C higher than that for the conventional cage counterpart. The supplemental heater capacity would need to be 20.5–22.0kW per 10,000 hens for the aviary houses (107,000-hen capacity) and 17.6kW per 10,000 hens for the enriched colony house (124,000-hen capacity). Annual H s was estimated to be 0.09 and 0.12MJ[kgegg]−1 for the enriched and aviary houses, respectively. The corresponding H s cost (in US dollars) would be, respectively, 0.11 and 0.15 US cent[kgegg]−1 at a wholesale liquid propane (LP) fuel price of $0.32l−1 ($1.21gal−1) or 0.26 and 0.35 US cent[kgegg]−1 at a retail LP fuel price of $0.75l−1 ($2.84gal−1). Among all the influencing factors considered, t i and RHi setpoints had more pronounced impacts on t bal and H s. The analysis indicated that H s energy cost for the alternative housing systems in the Midwestern USA is less than 0.3% of the total production cost. The simulation model was validated with measured heating energy use by a commercial aviary house in northern Iowa and the difference between the predicted and field-measured H s values was less than 5%. This interactive model can be readily used for analysis of other laying-hen housing, climatic conditions, and/or management scenarios.
  
  PubDate: 2013-05-18T23:05:27Z
Dual crop coefficients for maize in southern Brazil: Model testing for sprinkler and drip irrigation and mulched soil
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Juliano D. Martins , Gonçalo C. Rodrigues , Paula Paredes , Reimar Carlesso , Zanandra B. Oliveira , Alberto E. Knies , Mirta T. Petry , Luis S. Pereira
  The study sought to determine the appropriate basal crop coefficients for maize through the calibration and validation of the model SIMDualKc using various treatments of maize irrigated with sprinkler and drip methods under full and deficit irrigation and cropped with organic mulch. The model computes crop evapotranspiration (ETc) using the dual crop coefficient methodology, thus separating crop transpiration, T c, and soil evaporation, E s. Two experiments were carried out and the model was calibrated for one treatment of each experiment and validated with the remaining treatments. The corresponding results show good agreement between the simulated and observed available soil water through the season, with regression coefficients of 0.99–1.02, and the root mean square error ranging 2.0–3.3% of the total available water. The calibrated K cb for the initial and mid-season are respectively 0.20 and 1.12; the K cb at end season is 0.2 for grain maize and 0.8 for maize harvested for silage. Results show that the evaporation component of evapotranspiration is less than 9% of ETc for both sprinkler and drip experiments, thus indicating the suitability of using mulch for water conservation.
  
  PubDate: 2013-05-18T23:05:27Z
The influence of loading conditions on equine hoof capsule deflections and stored energy assessed by finite element analysis
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Glenn D. Ramsey , Peter J. Hunter , Martyn P. Nash
  The biomechanical effects on the hoof capsule of the location of the centre of pressure of the ground reaction force may be important to understand the functioning of the hoof capsule. This study investigated the effect of changes in loading and contact friction on hoof deflections and elastic energy storage by varying the boundary conditions applied to finite element models. For all cases a load of 10 N kg−1, typical of the peak load in the trot gait, was used. In one scenario the coefficient of contact friction was varied from 0 (frictionless) to 1, at a constant non-zero joint moment, to simulate the effects of restriction of the hoof at the ground surface. In the other scenario a varying joint moment, with contact friction set at 0, was used to move the centre of pressure (COP) forward. Both increasing the ground surface friction and moving the COP forward caused the hoof capsule deflections and stored elastic energy to decrease. Peak strain energy in the capsule occurred when the frictional coefficient was 0 and when the COP was below the centre of rotation of the distal interphalangeal joint. Minimum strain energy occurred when the frictional coefficient was 1.0 and when the COP location was 30 mm forward of the joint centre. Hoof expansion and elastic energy storage are considerably influenced by ground surface friction and centre of pressure location. Therefore model validation studies should account for these parameters. Maximising the energy absorption may explain why heel first landing is preferred.
  
  PubDate: 2013-05-18T23:05:27Z
A novel slow-release urea fertiliser: Physical and chemical analysis of its structure and study of its release mechanism
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Ni Xiaoyu , Wu Yuejin , Wu Zhengyan , Wu Lin , Qiu Guannan , Yu Lixiang
  Reducing the release rate of urea can increase its efficiency of use and reduce nitrogen pollution. A slow-release urea (S-urea) was produced using a new method; a bentonite and organic polymer (OP) were used to form a three-dimensional lattice structure by melting urea directly. The structure affected the recrystallisation of urea and increased its stacking density. The specific surface area of S-urea was 0.046 m2 g−1, much lower than that of common urea (1.698 m2 g−1). The static release experiment showed that 75% of 12 g sample of S-urea was released in 1 l water for about 14 h, much longer than that of common urea (<0.5 h). The kinetic simulation results showed that the release of S-urea was not based on Fickian diffusion but underwent anomalous diffusion with its release rate was mainly affected by the dissolving-eroding process of the medium which was controlled by the compactness of the lattice structure. This process may be strengthened by increasing the amount of bentonite.
  Graphical abstract
  
  PubDate: 2013-05-18T23:05:27Z
Limitations of single kernel near-infrared hyperspectral imaging of soft wheat for milling quality
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Stephen R. Delwiche , Edward J. Souza , Moon S. Kim
  Soft wheat milling quality assessment typically begins in the later stages of wheat breeding programmes and continues after cultivar release in commercial milling and processing operations. Near-infrared (NIR) hyperspectral (HS) image analysis, a technique that is gaining interest in food and pharmaceutical inspection research, was explored as an alternative procedure for milling quality evaluation. Three quality properties were studied, flour yield (the weight fraction of flour to whole grain), softness equivalent (a gauge of how easily flour is released from the kernel during break), and sucrose solvent retention capacity (SRC, related to arabinoxylans, which influence water absorption during dough mixing) because of their high degree of heritability and influence on soft wheat quality. NIR HS reflectance images (1000–1700 nm) of non-touching kernels were collected on more than 120 pure cultivars or advanced lines of soft red and white wheat. Five morphological properties (area, elliptical eccentricity and major and minor axis lengths, and ellipsoidal volume) and three spectral properties (principal component scores 1–3) were exhaustively examined in multiple linear regression models for each quality property and in nonparametric classification into low, medium, and high groups using texture properties (contrast, correlation, energy, and homogeneity) calculated from grey-level co-occurrence matrices of principal component scores images. Results indicated that softness equivalent exhibited the highest correlation with HS properties, while sucrose SRC had the lowest correlation. The combination of morphological and spectral properties produced better models than either property group alone. However, because of the inherent chemical and physical complexities of wheat, HS imaging will not be sufficient so as to replace actual pilot milling procedures.
  
  PubDate: 2013-05-18T23:05:27Z
Modified atmosphere container equipped with gas diffusion tube automatically controlled in response to real-time gas concentration
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Yun Hee Jo , Nam Yong Kim , Duck Soon An , Hyuek Jae Lee , Dong Sun Lee
  Fresh produce container system was constructed to have a gas diffusion tube or perforation aperture responding to real-time measured O2 and CO2 concentrations. Within the boundary of appropriate diameter and length of the diffusion tube, lower O2 and upper CO2 limits of optimal modified atmosphere could be used as criteria for control. From the mathematical simulation based on the mass balance of gases under controlled opening/closing, it was found that the atmosphere of appropriately designed container for blueberry, green pepper, king oyster mushroom and spinach is usually located on the borderline of the lower O2 limit or the upper CO2 limit without coming into zone of injurious gas concentration. This estimation was confirmed experimentally for a prototype container system of green pepper and spinach at 10 °C. The prototype system for spinach was effective in maintaining the beneficial modified atmosphere (8–9% O2 and 10% CO2) under both constant and varying temperature conditions, and thus contributed to quality preservation.
  
  PubDate: 2013-05-18T23:05:27Z
Evaluation of the root system resistance against failure of urban trees using principal component analysis
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): A. Szoradova , L. Praus , J. Kolarik
  The resistance against failure is an important topic of recent arboricultural research. Trees in urban environments are particularly of interest because of the damage they can cause. Root system anchorage stiffness is the variable that allows the resistance of the root–soil plate against failure to be quantified repetitively and non-destructively. This study uses principal component analysis (PCA) to evaluate tree mechanical state, when the input parameters are the load parameters and suitable root–soil plate stiffness parameter. The PCA method allows the similarity of surveyed trees within a control group with known mechanical state to be identified. Thus, the mechanical stability of surveyed trees can be evaluated.
  
  PubDate: 2013-05-18T23:05:27Z
Chemical methods for the remediation of ammonia in poultry rearing facilities: A review
- Abstract: Publication date: July 2013
  Source:Biosystems Engineering, Volume 115, Issue 3
  Author(s): Dorin Bejan , Thomas Graham , Nigel J. Bunce
  Possible chemical methods for the treatment of ammonia in the air of livestock holding facilities, with particular focus on poultry production, are reviewed in the context of eliminating ammonia by oxidation to elemental nitrogen. Gas phase catalytic oxidation processes are incompatible with the needs of the poultry industry on grounds of both capital cost and energy intensiveness. Most chemical oxidants convert ammonia principally to nitrate rather than N2. So-called advanced oxidation processes are unsuited to ammonia oxidation because the hydroxyl radicals that characterize these oxidations react poorly with both NH3 and NH4 +. One promising option is electrochemical oxidation, which does not require the purchase of stoichiometric amounts of chemical oxidants. Among possible electrochemical methods, we favour electrochemical hypochlorination, whereby the denitrification of ammonia to elemental nitrogen is mediated by hypochlorous acid, which is formed reversibly from chloride ion. This technique is compatible with currently available scrubbing technology, with the modification of using acidic brine as the scrubbing solution. Because electrochemical hypochlorination can be applied without costly and complicated pH adjustment of the scrubbed solution with chemical additives, it constitutes an example of best available technology.
  
  PubDate: 2013-05-18T23:05:27Z
Editorial Board
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  
  PubDate: 2013-05-06T23:07:07Z
Potential use of fibrous grass silage press-cake to minimise shrinkage cracking in low-strength building materials
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): C. King , M. Richardson , J. McEniry , P. O’Kiely
  The fibre-rich press-cake fraction produced by ‘green biorefineries’ may provide a sustainable solution for the control of restrained drying shrinkage cracking in stabilised soil blocks and cementitious mortars. Following determination of the tensile strength of selected grass species at different harvest dates, the effect of press-cake inclusion was assessed in controlling the shrinkage of clay and mortar specimens. The press-cake was found to be effective in controlling the onset of early-restrained drying shrinkage cracking in both clay and cementitious specimens. The addition of press-cake fraction to terracotta pottery clay had a pronounced beneficial effect on early-restrained shrinkage, increasing the time to first crack by over 5 h and reducing the crack width by 4.9 mm relative to the control. Inclusion of the press-cake fraction in mortar specimens (at a rate of 2.2 kg m−3) eliminated crack formation completely, compared with the unreinforced mortar specimens which cracked after 3 h. This positive influence on the consequences of restrained shrinkage occurred despite the fact that early-age free shrinkage rates were found to increase in proportion to press-cake inclusion rate. Furthermore, in cementitious specimens the performance of the press-cake compared well with polypropylene fibres in respect of mitigating the risk of cracking due to early-age restrained shrinkage in cementitious specimens.
  Highlights ► Tensile strength of grass was found to be suitable for use in building. ► Perennial ryegrass fibre identified as a potential sustainable material for use in building. ► Potential use in control of restrained shrinkage cracking demonstrated for clay and mortar specimens.
  
  PubDate: 2013-04-24T23:07:15Z
Airflow measurements in and around scale-model cattle barns in a wind tunnel: Effect of wind incidence angle
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): Merlijn De Paepe , Jan G. Pieters , Wim M. Cornelis , Donald Gabriels , Bart Merci , Peter Demeyer
  Indoor air quality in animal houses can be accomplished through natural ventilation, as often implemented in cattle barns. Besides wind speed, the largest contributor to efficient natural ventilation is the building orientation, since the angle of wind incidence strongly affects the pressure distribution around it. To acquire a better understanding of this process, air velocity measurements were carried out in two 1:60 scale models of a dairy cattle house placed in a wind tunnel, using a reference air velocity of 3.5ms−1. Five different wind incidence angles were simulated using a turntable, in order to quantify their effect on indoor air velocities. The responses in local air velocities could largely be attributed to the relative position of the end walls of the scale models orientated towards the wind. This crucial position allows the measured air velocity trends to be explained. The estimated airflow rates gradually decreased for larger wind incidence angles. Expressions that relate air velocity to wind incidence angle (for angles≤45°) are presented through linear regression. Additionally, the experimental model provides useful data for evaluating and possibly improving computational fluid dynamics (CFD) models.
  Highlights ► Air velocity values are presented in a quantitative manner for two scale models. ► The wind incidence angle clearly affects indoor air velocities in the models. ► Gradual rotation of the models leads to explainable changes in indoor air velocities. ► The quantitative results are useful for the evaluation and improvement of CFD models.
  
  PubDate: 2013-04-24T23:07:15Z
Fish processing wastewater as a platform of the microalgal biorefineries
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): Maria Isabel Queiroz , Márcio Oliveira Hornes , Adriana Gonçalves da Silva Manetti , Leila Queiroz Zepka , Eduardo Jacob-Lopes
  The aim was to develop a bioprocess for conversion of wastes of fish processing into single-cell oil and single-cell protein with parallel water reuse under the scope of a biorefinery. The wastes generated by the process were used to support the heterotrophic growth of microalgae simultaneously converting the organic matter, nitrogen, and phosphorus of the wastewater into biomass that is suitable for energy and nutrient production. Chemical treatment, based on coagulation–flocculation–sedimentation, was used to separate the biomass of the wastewater, and membrane microfiltration was used to reclaim water and permit reuse in industrial cooling systems.
  Highlights ► Prototype microalgae biorefinery has been assessed. ► Wastes generated by the fish processing wastewater were used to microalgal growth. ► Production of energy and nutrients was considered.
  
  PubDate: 2013-04-20T23:06:30Z
A computer vision-based system for the automatic detection of lying behaviour of dairy cows in free-stall barns
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): Simona M.C. Porto , Claudia Arcidiacono , Umberto Anguzza , Giovanni Cascone
  A computer vision-based system for the automatic detection of dairy cow lying behaviour in free-stall barns is proposed. The system is composed of a multi-camera video-recording system and a software component which executes a cow lying behaviour detector model using the Viola–Jones algorithm. A method to carry out the training, testing and validation phase of the modelled cow lying behaviour detector is described. The performance of the system was tested in an area of a head-to-head free-stall barn where a group of 15 Holstein dairy cows was housed. A multi-camera video-recording system was installed to obtain panoramic top-view images of the area under study. Since the Viola–Jones algorithm was not invariant to the rotation of the cow images, two classifiers were modelled, one for each row of stalls located in the barn. These two classifiers were implemented in the software component of the system in order to perform the lying behaviour detection. The system was validated by comparing its detection results with those generated from visual recognition. The ability of the system to detect cow lying behaviour was confirmed by the high value of its sensitivity, which was approximately 92%. Conversely, the value of the branching factor which was approximately 0.08 indicated that one false positive was detected for every 13 well detected cows. These results suggest that the system proposed in this study could be used for the calculation of the cow lying index which is widely used to investigate cow lying behaviour in free-stall barns.
  Highlights ► To model the cow lying behaviour detector image enhancement was not required. ► In the training phase FPRcas of the order of 10−7 and TPRcas of 0.90 were achieved. ► The testing phase proved detector ability even when noise affected camera images. ► The cow lying behaviour detector provided a sensitivity of 92% and a BF of 0.08. ► CVBS can be used to compute cow lying index.
  
  PubDate: 2013-04-20T23:06:30Z
Precision metering of Santalum spicatum (Australian Sandalwood) seeds
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): Dylan St Jack , Dianne C. Hesterman , Andrew L. Guzzomi
  The development of a seed metering device to mechanise the seed-sowing process for sandalwood is reported. Amongst the mass flow and precision type seed meters considered, the ‘vacuum disc’ type precision meter was deemed most suitable. A vSets vacuum disc seed meter was modified to accommodate seeds whose diameter ranged from 13.5 to 23.5 mm. Nine custom made discs were tested over three vacuum levels. The discs were analysed for their ability to achieve a seed spacing of 200 mm at a ground speed of 4 km h−1. Accuracy was measured using the performance indices from ISO 7256/1-1984(E) as well as a modified coefficient of precision (CP3) index. Tests of twenty seven unique configurations were conducted with a sample of three hundred seeds. It was found that more than half of the configurations could singulate the seeds to a singulation level of 94%. Discs with seven 10 mm or 12 mm diameter holes, run at 17 kPa were found to be the most accurate configurations for the conditions considered and demonstrate that mechanisation of sandalwood seed sowing is possible.
  Highlights ► Native Australian Sandalwood rehabilitation necessary for industry sustainability. ► Current rehabilitation methods limited due to reliance on intensive manual labour. ► Mechanisation of seed-sowing process limited due to lack of singulation technology. ► Custom discs were designed and tested for a vacuum type precision meter. ► A functional singulation device has been developed making mechanisation feasible.
  
  PubDate: 2013-04-20T23:06:30Z
Citrus yield estimation based on images processed by an Android mobile phone
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): Aiping Gong , Junlin Yu , Yong He , Zhenjun Qiu
  The advanced electronic technology makes the mobile phone suitable for citrus yield estimation with image processing techniques. This article proposes a new method to estimate the yield of citrus two weeks ahead of the harvesting season for an individual tree via image processing using an Android mobile phone (AMP). The procedure is essentially fruit-counting algorithm software developed in Java that uses AMP touch panel monitor to estimate citrus yield. The target photos were taken in natural conditions by the AMP. The image processing was used to choose colour, segment image, generate binarisation image, remove noise, and estimate fruit number. A modified 8-connectedness chain code to estimate the number of clustered citrus was introduced. The performance of the fruit-counting algorithm software was validated with 40 samples of citrus trees and the method achieved good precision and recognition ratio of 90%. The results indicated that the approach could be utilised to estimate the fruit yield of an individual tree which is valuable information to forecast yields, plan harvest schedules and generate prescription maps for site-specific management practices on an individual tree basis within the grove. Aided by the proposed approach, one can estimate the citrus yield without expensive equipment.
  
  PubDate: 2013-04-20T23:06:30Z
Prediction and classification of sugar content of sugarcane based on skin scanning using visible and shortwave near infrared
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): Nazmi Mat Nawi , Guangnan Chen , Troy Jensen , Saman Abdanan Mehdizadeh
  The potential application of a visible and shortwave near infrared (Vis/SWNIR) spectroscopic technique as a low cost alternative to predict sugar content based on skin scanning was evaluated. Two hundred and ninety one internode samples representing three different commercial sugarcane varieties were used. Each sample was scanned at four scanning points to obtain the spectra data which was later correlated with its °Brix (soluble solids content) values. Partial least square (PLS) model was developed and applied to both calibration and prediction samples. Using reflectance spectra data, the model had a coefficient of determination (R 2) of 0.91 and root means square error of predictions (RMSEP) of 0.721 °Brix. The artificial neural network (ANN) was also applied to classify spectra data into five °Brix categories. The ANN has yielded good classification performance, ranging from 50 to 100% accuracy with an average accuracy of 83.1%. These results demonstrated that the Vis/SWNIR spectroscopy technique could be applied to predict sugarcane °Brix in the field based skin scanning method.
  Highlights ► Application of Vis/SWNIR to predict sugar content based on skin scanning explored. ► Partial least square (PLS) model applied to calibration and prediction samples. ► Model R 2 of 0.91 and RMSEP of 0.721 °Brix. ► ANN used to classify spectra data into five °Brix categories yielded good classification. ► Vis/SWNIR field based skin scanning method can be applied to predict sugarcane °Brix.
  
  PubDate: 2013-04-20T23:06:30Z
Two-stage approach for detecting slightly overlapping strawberries using HOG descriptor
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): Yongwei Xu , Kenji Imou , Yutaka Kaizu , Kiyotaka Saga
  This article presents a new method for strawberry detection for use in a strawberry harvesting robot. The method is based on a histogram of oriented gradients (HOG) descriptor associated with a support vector machine (SVM) classifier. The detection involves two stages. First, strawberry-like regions are detected from HSV (hue, saturation, value) colour information. The HOG descriptor, calculated using five regions of interest (ROI), is input to an HOG/SVM classifier, which detects the strawberries. The performance of the model was verified by experiments. The vector sizes were effectively reduced and a higher detection speed was achieved without compromising accuracy (relative to conventional approaches). The proposed classifier achieves high detection accuracy (87%) in a reasonable run time, and can appropriately handle slightly overlapping strawberries.
  Highlights ► New method to detect strawberries for strawberry harvesting robot was presented. ► Two-stage approach combined the HSV colour information and HOG descriptor. ► Strawberry region divided into 5 ROI to deal with slightly overlapping fruit. ► Optimal parameters sped up detection process while maintaining comparably accuracy.
  
  PubDate: 2013-04-20T23:06:30Z
Cereal grain combustion in domestic boilers
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): Andrew Keppel , John Finnan , Bernard Rice , Philip Owende , Kevin MacDonnell
  The combustion characteristics and combustion behaviour of oats, barley, triticale and wheat are compared to that of wood pellets. Sustained grain combustion in domestic boilers was feasible but problematic, the main impediment being clinker formation with ash agglomeration. Clinker formation was lowest for oats which burned easily with fewer operational problems. Triticale displayed reasonably good combustion characteristics and also ignited easily. In contrast, barley and wheat proved difficult to ignite while barley combustion was prone to self-extinguish. Thermal and combustion efficiency and heat output were considerably higher at a grain moisture content of 15% compared to a moisture content of 20%. The efficiency of oat combustion was similar to that of wood pellets at a moisture content of 15%. Carbon monoxide (CO) emission from cereal grains increased with increasing moisture content, but was still below limit values. Oxides of nitrogen (NO x ) emissions from cereal combustion were high and would require reduction by limiting the quantity of nitrogen applied to the crop and/or the use of air staging. Oats proved superior to the other grains as a combustion feedstock with similar efficiencies to those of wood pellets but low moisture content is a prerequisite for efficient grain combustion.
  
  PubDate: 2013-04-20T23:06:30Z
Detecting maize inoculated with toxigenic and atoxigenic fungal strains with fluorescence hyperspectral imagery
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): Haibo Yao , Zuzana Hruska , Russell Kincaid , Robert L. Brown , Deepak Bhatnagar , Thomas E. Cleveland
  Naturally occurring Aspergillus flavus strains can be either toxigenic or atoxigenic, indicating their ability to produce aflatoxin or not. The objective was to assess, with the use of a hyperspectral sensor, the difference in fluorescence emission between maize kernels inoculated with toxigenic and atoxigenic inoculums of A. flavus. Maize ears were inoculated with AF13, a toxigenic strain of A. flavus, and AF38, an atoxigenic strain of A. flavus, at dough stage of development and harvested 8 weeks after inoculation. After harvest, single kernels were divided into three groups prior to imaging: control, adjacent, and glowing. Both sides of the kernel, germ and endosperm, were imaged separately using a fluorescence hyperspectral imaging system. After imaging each single kernel was processed with affinity column fluorimetry to determine aflatoxin level. Results from discriminant analysis of the imaging data found that the classification accuracies of the three visually designated groups were not promising. The separation of maize kernels based on different fungal inoculums yielded better results. The best results were achieved with the germ side of the maize kernels. The kernels were later grouped into ‘contaminated’ and ‘healthy’ with 20 ppb and 100 ppb thresholds. The contaminated kernels all had longer peak wavelength than did the healthy ones. Results from the discriminant analysis classification indicated overall higher classification accuracy for the 100 ppb threshold on the germ side (94.4%). The germ side was also more useful at discriminating healthy from contaminated kernels for the 20 ppb threshold.
  Highlights ► Used fluorescence hyperspectral imagery to study Aspergillus flavus inoculated maize. ► Toxigenic and atoxigenic strains of fungi were compared in the study. ► The actual aflatoxin of each maize kernel was chemically measured. ► The best results for separation were achieved with the germ side of the maize kernels. ► The study showed potential of imaging for aflatoxin contamination detection in maize.
  
  PubDate: 2013-04-20T23:06:30Z
Measurement and prediction of buffalo manure evaporation in the farmyard to improve farm management
- Abstract: Publication date: June 2013
  Source:Biosystems Engineering, Volume 115, Issue 2
  Author(s): Stefania Pindozzi , Salvatore Faugno , Collins Okello , Lorenzo Boccia
  In order to evaluate the performance of two empirical models for buffalo (Bubalus bubalis) manure evaporation, predictions were compared with measured data. The two models were developed by adapting the potential evapotranspiration (ETo) models of Tombesi–Lauciani and Hargreaves. The data used for assessing the manure evaporation in situ, were derived from the manure weights recorded using an experimental platform installed within the farmyard and equipped with load cells. The experiments were carried out in Serre (SA), in the South of Italy in the period from 23 June to 24 September 2011. The most efficient model, in terms of closeness between estimates and measures, was implemented from 2006 to 2010, allowing for annualised calculation of evaporation. On this basis, an optimal management strategy was established, which corresponds to maximising manure evaporation, minimising the use of the scraper from the 100th day of the year (DOY) to the 250th DOY. This leads to a potential reduction in weight of the manure by 650 kg m− 2 [yard] year−1, which corresponds to management cost reduction of about 30%.
  Highlights ► An experimental platform was installed in the paddock to assess buffalo manure weight. ► Measured data were used to compare two empirical models for manure evaporation. ► The more efficient model was implemented over a period of 5 years. ► An optimal management strategy was established minimizing the use of the scraper. ► Potential reduction in manure weight corresponds to cost reduction of about 30%.
  
  PubDate: 2013-04-20T23:06:30Z
Editorial Board
- Abstract: Publication date: May 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  PubDate: 2013-04-12T23:07:00Z
Novel image processing approach for solving the overlapping problem in agriculture
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  A general problem in computer vision is the detection of objects when they are partially occluded. This problem also extends to the identification of horticultural/agricultural products (e.g., plants and crops), where recognition can be very cumbersome due to the heavy overlapping situations that one can find. This paper presents a novel approach to solve the recognition of plantlets under such conditions. The methodology consists of two major steps: (1) The simplification of the complexity of leaf shapes by using ellipse approximation. (2) The clustering of the leaves (ellipses) found into plantlets using active shape models. Shape models of experimental plants with 2, 3 and 4 leaves were tested to analyse the ability of the method to overcome the overlapping problem. The results indicate that the presented technique is able to perform identification of individual plantlets under overlapping situations, by first decreasing the complexity of their form and then using these simplified characteristics in a statistical shape model.
  Highlights ► Identification of seedlings under overlapping situations is carried out. ► A simplification of the original shape using ellipses is performed. ► A new ellipse matching system to identify leaves is proposed. ► Plants are a set of landmarks extracted from the detected ellipses. ► Active shape models are use to cluster leaves to form plants.
  
  PubDate: 2013-03-28T00:06:09Z
Evaluation of watermelons texture using their vibration responses
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  Flesh texture quality is an important attribute for watermelons that can be used as a ripeness indicator for sorting fruits. A non-destructive method is employed here, based on vibrations response, to assess the consumer opinion about watermelon (Crimson Sweet) tissue. The responses of samples to vibration excitation were recorded by laser Doppler vibrometry (LDV). The amplitude and phase as two spectrums of frequency response function were extracted over a wide frequency range. Following non-destructive tests, the watermelons were sensory evaluated. The samples were graded in a range of ripeness by panel members in terms of texture acceptability. Stepwise multiple linear regression (SMLR) and partial least squares regression (PLSR) were applied to extracted vibration spectrums to construct prediction models of watermelon flesh quality. The results showed that performance of SMLR models on phase spectrum was better than others. The determination coefficients (R 2) of the calibration and cross validation models were 0.9998 and 0.9986 respectively. This study demonstrated the feasibility of mentioned method for predicting the quality of watermelons in industrial grading systems.
  Highlights ► Laser vibrometry rapidly and accurately detected quality indices of watermelon. ► Frequencies of phase shifts with highest contributions in prediction model selected by stepwise method. ► Comparisons between SMLR and PLS on phase spectrums of vibration response. ► Results could help for remote sensing of watermelon texture.
  
  PubDate: 2013-03-24T00:05:14Z
Energy audit of irrigation networks
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  The relationship between water and energy in water distribution systems (WDS) has been a growing concern among energy and water experts. Among the different strategies to improve water–energy efficiency in water distribution networks, energy audits are of paramount importance as they quantify water flow requirements, the amount of energy consumed to meet demand and leakage and friction losses. Previous work has presented the energy audit process for urban WDS and this energy audit is extended to irrigation networks here. This work analyses the most common types of irrigation emitters (sprinklers and pressure compensating and non-pressure compensating drippers), hydrant specifications, irrigation management systems (on-demand or rigid scheduled), and energy losses due to friction in pipes, control valves and irrigation hydrants. The energy audit does not assess whether management of the network is optimal, but analyses the energy consumption. Some of the performance indicators have already been defined for agricultural water networks, some are identical to those of urban WDS, but in addition, a new one is presented that disaggregates the energy dissipated into three terms, energy losses in pipelines, in hydraulic valves and in irrigation hydrants. These indicators show information necessary to better understand the performance of the irrigation network under study, to carry out a deep analysis of energy consumption and to allow for comparison with similar systems. The paper presents the analysis of a real case study conducted on the irrigation network of the garden of the Universidad Politécnica de Valencia.
  Highlights ► This report provides a tool to calculate the energy audit of an irrigation network. ► Energy losses through leakage and energy dissipated in pipes etc. are included. ► New set of indicators allow better understanding of irrigation network performance. ► Case study given on a sectored network under central control scheduled management.
  
  PubDate: 2013-03-24T00:05:14Z
Evaluation of common pre-processing approaches for visible (VIS) and shortwave near infrared (SWNIR) spectroscopy in soluble solids content (SSC) assessment
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  The number of visible (VIS) and shortwave near infrared (SWNIR) spectroscopic applications in fruit internal quality has grown rapidly in the last decade. Despite this widespread application, pre-processed spectral data used is often not well understood. The aims of this paper are (i) to compare the use of SWNIR and VIS–SWNIR spectral data, (ii) to investigate the effect of different Savitzky–Golay (SG) derivatives (i.e. zero order, first order and second order derivatives) with different filter length, and (iii) to evaluate the use of log (1/R) transformation in the soluble solids content (SSC) assessment via Monte Carlo cross-validation (MCCV). Findings indicate that a parsimonious principal component regression (PCR) with four principal components achieved the best accuracy (i.e. root mean square error of cross-validation (RMSECV) = 0.81 °Brix and r cv = 0.75) when (i) visible spectrum was excluded, (ii) second order SG derivative with the optimal filter length was used, and (iii) the log (1/R) transformation was avoided.
  Highlights ► VIS from 662 to 700 nm did not contain unique relevant information for SSC assessment. ► Absorption transformation did not help to improve the accuracy of PCR model. ► We examine changes in the filter length of SG derivative (zero, 1st and 2nd order). ► With optimal filter length, PCR with 2nd order SG derivative achieved best result.
  
  PubDate: 2013-03-24T00:05:14Z
Soil organic matter sensing with an on-the-go optical sensor
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  This research was conducted to develop an inexpensive on-the-go optical sensor for soil organic matter (OM) sensing. Diffuse reflectance for 86 soil samples from Kansas and Illinois was measured by a spectrometer in a laboratory. Stepwise multiple linear regression (SMLR) and B-matrix in partial least squares (PLS) were used to determine important wavelengths for soil OM measurement. The wavelengths of 660 and 940nm, identified by both SMLR and PLS, were used for an optical sensor. The developed optical sensor with dual wavelength was evaluated with dry and wet soils in the lab and the relationship between reflectance and OM showed a coefficient of determination (R 2) as high as 0.91. Gaps between soil and the sensor window reduced the ability to estimate soil organic matter, thus the sensor window should press firmly against soil. In field tests, all fields gave good results, with RPD (ratio of prediction to deviation=standard deviation/root mean square error) of 2 or greater for OM estimation. In comparison with a NIR spectrophotometer shank unit, the optical sensor showed similar results for OM mapping pattern with coefficient of determination as 0.86. The level of agreement between the two maps was 0.56 for overall accuracy and 0.34 for kappa coefficient. Further field tests need to be implemented to evaluate the soil organic matter estimation with the sensor over different types of soils in a wider set of locations.
  Highlights ► Optical sensor with 660 and 940nm LEDs to measure soil organic matter content (OM). ► Sensor evaluated with soils in the lab, reflectance and OM had R 2 of 0.91. ► Field tests showed ratio of prediction to deviation as high as 3.56 and R 2 of 0.91. ► Sensor comparable with NIR spectrophotometer for OM mapping pattern with R 2 of 0.86.
  
  PubDate: 2013-03-24T00:05:14Z
Detecting macronutrients content and distribution in oilseed rape leaves based on hyperspectral imaging
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  This study was carried out to investigate the potential of visible and near infrared (VIS–NIR) hyperspectral imaging system for rapid and non-destructive content determination and distribution estimation of nitrogen (N), phosphorus (P) and potassium (K) in oilseed rape leaves. Hyperspectral images of 140 leaf samples were acquired in the wavelength range of 380–1030 nm and their spectral data were extracted from the region of interest (ROI). Partial least square regression (PLSR) and least-squares support vector machines (LS-SVM) were applied to relate the nutrient content to the corresponding spectral data and reasonable estimation results were obtained. The regression coefficients of the resulted PLSR models with full range spectra were used to identify the effective wavelengths and reduce the high dimensionality of the hyperspectral data. LS-SVM model for N with R P of 0.882, LS-SVM model for P with R P of 0.710, and PLSR model for K with R P of 0.746 respectively got the best prediction performance for the determination of the content of these three macronutrients based on the effective wavelengths. Distribution maps of N, P and K content in rape leaves were generated by applying the optimal calibration models in each pixel of reduced hyperspectral images. The different colours represented indicated the change of nutrient content in the leaves under different fertiliser treatments. The results revealed that hyperspectral imaging is a promising technique to detect macronutrients within oilseed rape leaves non-destructively and could be applied to in situ detection in living plants.
  Graphical abstract Highlights ► N, P and K contents in oilseed rape leaves were determined by hyperspectral imaging. ► Quantitative models between spectra and N, P and K were established respectively. ► Optimal wavelengths mostly related to N, P and K were identified respectively. ► Distribution maps of N, P and K in oilseed rape leaves were generated at pixel level.
  
  PubDate: 2013-03-20T00:05:21Z
Emissions and efficiencies from the combustion of agricultural feedstock pellets using a small scale tilting grate boiler
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  Alternative biomass feedstocks will be required in order to meet renewable energy targets, yet it is imperative that the production of renewable energy from biomass must be environmentally benign. Thus, it is important that emissions from biomass combustion must be low. Pellets of six different biomass types; wood, willow, miscanthus, wheat straw, barley straw and rape straw, were combusted in a 35 kW tilting grate biomass boiler and carbon monoxide (CO), sulphur dioxide (SO2) and nitrogen oxides (NO x ) as well as total solid particulate (TSP) emissions were monitored. Emissions from wood combustion were relatively low (25, 142, 4.6, 28 mg Nm−3 for CO, NO x , SO2 and TSP respectively) whereas emission from the combustion of straw pellets was considerably higher. Rape straw pellets produced the highest levels of emissions (230, 339, 59.8 and 325 mg Nm−3 for CO, NO x , SO2 and TSP). There was a relationship between the magnitude of TSP, NO x and SO2 emissions and the concentrations of ash, nitrogen and sulphur in the fuel respectively. The combustion of pellets made from wood, willow or miscanthus would meet current emission standards but the use of cereal or rape straw pellets would require the employment of emissions abatement measures or more advanced boiler design in order to meet emission standards. The use of mitigation measures and/or advances in boiler design should allow pellets made from agricultural residues and energy crops to make a significant contribution to the generation of renewable energy.
  Highlights ► Emissions from wood pellets low compared to emissions from straw pellets. ► Emissions from energy crop pellets similar to wood, wheat, barley and rape straws. ► Levels of TSP, NO x and SO2 related to concentrations of ash, N and S in the fuel. ► Abatement measures should permit the use of straw and energy crops pellets.
  
  PubDate: 2013-03-20T00:05:21Z
Linear pressing analysis of Jatropha curcas L. seeds using different pressing vessel diameters and seed pressing heights
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  The mechanical properties of Jatropha curcas L. seeds of initial moisture content 10% (w.b.) were examined in a compression loading test using different pressing vessel diameters 40, 60, 80 & 100 mm and seed pressing heights 20, 30, 40, 50, 60, 70 & 80 mm. The maximum pressing force of 100 kN with a compression speed of 1 mm s−1 was used to record the force–deformation characteristics. Based on the dependency between the maximum pressing force and deformation of the varying seed pressing heights; parameters including the maximum deformation (mm), deformation energy (J), seed hardness (N mm−1) and amount of oil in seed (g) were determined. The results showed that for all pressing vessel diameters, increasing the seed pressing heights directly increased the deformation, deformation energy and the amount of oil. However, the relationship between deformation and pressing vessel diameter, in relation to the seed pressing heights, showed a negative correlation whilst that of deformation energy and pressing vessel diameter showed a positive correlation. The seed hardness for all pressing vessel diameters decreased with respect to seed pressing heights where polynomial function best described the relationship. A linear regression equation was determined for the seed deformation, seed deformation energy and amount of oil as a function of seed pressing heights and pressing vessel diameter.
  Highlights ► Linear models suitable for describing Jatropha seeds under compression loading. ► Deformation, energy & oil produced linear function of pressing height & vessel diameter. ► Seed deformation of smaller pressing diameters > bigger. ► Deformation energy and oil produced in the bigger diameter > smaller diameters. ► Statistical analysis significant at p = 0.05 with >90% correlation efficiencies.
  
  PubDate: 2013-03-20T00:05:21Z
Estimation of leaf area index in onion (Allium cepa L.) using an unmanned aerial vehicle
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  Leaf area index (LAI) is one of the most common indices in agronomy, being a parameter associated with physiological processes. Canopy cover and structure are related to LAI and they have effects on the interaction between crops and the environment. The aim was to evaluate a non-destructive method to measure canopy cover in an onion crop using an unmanned aerial vehicle (UAV). A field experiment was conducted in a commercial onion plot irrigated with a centre pivot system during the 2010 irrigation season. Several data sampling events were carried out in order to determine leaf area in eight experimental plots. In each one of these plots, aerial photographs were taken using a vertical take-off and landing (VTOL) quadrotor aircraft. Canopy cover (CC) was obtained by means of software developed for this study. The maximum value of LAI represents a CC of 56%, which is high for the characteristics of this crop. Three models were used to analyse the relationship between leaf area index and canopy cover. According to the results, a more linear relationship was found between both parameters during early growth stages than during more advanced stages. For the linear model, which best fitted all growth stages; the slope that relates CC with LAI was 2.877 with a coefficient of determination of 0.837.
  Highlights ► A non-destructive method was evaluated to measure canopy cover in an onion crop. ► Aerial digital photography from unmanned aerial vehicles was used. ► A software tool was developed to determine canopy cover. ► Relationship between canopy cover and leaf area index found using an automatic IR imaging system.
  
  PubDate: 2013-03-20T00:05:21Z
The development of a hyperspectral imaging method for the detection of Fusarium-damaged, yellow berry and vitreous Italian durum wheat kernels
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  The possibility of using hyperspectral imaging (HSI) techniques to classify different types of wheat kernels, vitreous, yellow berry and Fusarium-damaged, was investigated. Conventional optical techniques adopted by industry for wheat grain sorting usually have too high misclassification errors. Reflectance spectra of selected wheat kernels of the three types were acquired by a laboratory device equipped with an HSI system working in near infrared field (1000–1700 nm). The hypercubes were analysed applying different chemometric techniques, such as principal component analysis (PCA) for explorative purposes, partial least squares discriminant analysis (PLS-DA) for classification of the three wheat types and interval PLS-DA (iPLS-DA) for the selection of a reduced set of effective wavelength intervals. The study demonstrated that good classification results were obtained not only considering the entire investigated wavelength range, but also selecting only three narrow intervals of four wavelengths (1209–1230 nm, 1489–1510 nm and 1601–1622 nm) out of 121. The procedures developed could be utilised at industrial level for quality control purposes or for the definition of innovative sorting logics for wheat kernels after an extensive classification campaign, both at laboratory and industrial level, applied to a large wheat sample sets.
  Graphical abstract Highlights ► Classification of vitreous, yellow berry and Fusarium-damaged wheat by NIR-HSI. ► Different chemometric strategies applied to classify wheat kernels typologies. ► The different types of wheat kernels were correctly identified in the prediction images. ► 3 effective wavelength intervals were identified to speed up the classification procedure. ► The HSI-based procedure is useful for wheat quality control and on-line sorting strategies.
  
  PubDate: 2013-03-20T00:05:21Z
LiDAR simulation in modelled orchards to optimise the use of terrestrial laser scanners and derived vegetative measures
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  Light detection and ranging (LiDAR) technology is beginning to have an impact on agriculture. Canopy volume and/or fruit tree leaf area can be estimated using terrestrial laser sensors based on this technology. However, the use of these devices may have different options depending on the resolution and scanning mode. As a consequence, data accuracy and LiDAR derived parameters are affected by sensor configuration, and may vary according to vegetative characteristics of tree crops. Given this scenario, users and suppliers of these devices need to know how to use the sensor in each case. This paper presents a computer program to determine the best configuration, allowing simulation and evaluation of different LiDAR configurations in various tree structures (or training systems). The ultimate goal is to optimise the use of laser scanners in field operations. The software presented generates a virtual orchard, and then allows the scanning simulation with a laser sensor. Trees are created using a hidden Markov tree (HMT) model. Varying the foliar structure of the orchard the LiDAR simulation was applied to twenty different artificially created orchards with or without leaves from two positions (lateral and zenith). To validate the laser sensor configuration, leaf surface of simulated trees was compared with the parameters obtained by LiDAR measurements: the impacted leaf area, the impacted total area (leaves and wood), and the impacted area in the three outer layers of leaves.
  Highlights ► A virtual orchard was modelled using a hidden Markov tree (HMT) model. ► A terrestrial laser sensor (LIDAR) was simulated. ► Impacted leaf area, total area, and area of three outer layers of leaves calculated. ► A good correlation was found between these parameters.
  
  PubDate: 2013-03-20T00:05:21Z
Ultrasound-assisted enzymatic hydrolysis of cassava waste to obtain fermentable sugars
- Abstract: May 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 115, Issue 1
  
  This work evaluates ultrasound-assisted enzymatic hydrolysis of cassava waste using α-amylase and amyloglucosidase to obtain fermentable sugars. The influence of solid to liquid ratio and the concentrations of α-amylase and amyloglucosidase on the amount of fermentable sugars released was assessed in the presence and absence of ultrasound irradiation by means of a central composite rotational design. The results showed that the concentration of fermentable sugars released ranged from 21.3 to 83.1 g l−1 and from 32.8 to 116.1 g l−1, in the absence and presence of ultrasound, respectively. The specific total reducing sugar (TRS) production (expressed as g of TRS per g of dry cassava waste) ranged from 0.18 to 0.27 for hydrolysis in the water bath and from 0.26 to 0.36 g g−1 in the ultrasound bath. The TRS concentration obtained using ultrasound for a sample with solid to liquid ratio of 0.16 was around 80 g l−1, and without ultrasound the similar concentration was only obtained for solid to liquid ratios higher than 0.34. This demonstrates that ultrasound technology can be useful for process intensification due to its positive effects on sugar yield.
  Highlights ► Ultrasound-assisted enzymatic hydrolysis improved the performance of process. ► Gain of yield up to 65% using ultrasound. ► High yield of fermentable sugar at the same enzymes concentration using ultrasound. ► Promising procedure to be applied industrially to improve the activity of enzymes.
  
  PubDate: 2013-03-20T00:05:21Z
Estimating olive leaf nitrogen concentration using visible and near-infrared spectral reflectance
- Abstract: April 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 114, Issue 4
  
  VIS-NIR spectroscopy for estimation of Nitrogen (N) content in olive leaves was studied as a tool for efficient fertilisation in olive (Olea europaea) orchards. Olive leaf samples (cv. Barnea) were taken from orchards which had been fertilised with a wide range of N levels. Dried ground leaves, fresh ground leaves and intact leaves were tested. Reflectance measurements were taken using three spectrometers: USB-2000 for VIS-NIR (450–1000 nm) and a LIGA, and a Luminar-5030 for SWIR (1100–1700 nm). Nitrogen concentrations of the same samples were measured analytically as a reference for the spectral analyses, which were conducted by means of partial least square regression (PLSR). The best predictive model for comprehensive in-season and between-season samples (160 samples from three seasons, taken on 18 separate days) was obtained using the Luminar spectrometer using thoroughly ground dried leaves (R 2 = 0.91). Classification into three N levels was evaluated and gave an overall accuracy of 0.83 with a kappa of 0.75 (substantial). Intact leaves yielded non-sufficient correlations. The results showed that leaf dehydration improves the model performance significantly and that VIS-NIR spectroscopy might be used for decision-making in fertilisation procedures. Finally, a protocol is suggested for laboratory spectral measurements.
  Highlights ► Robust spectral prediction model to evaluate N in olive leaves was developed. ► Best prediction model obtained using a dual-beam spectrometer and well-ground dry leaves. ► Water content conceals part of N effect on the spectral reflectance. ► Optimal evaluation of N level achieved by laboratory spectral measurements protocol.
  
  PubDate: 2013-03-08T00:06:01Z
Estimating evapotranspiration from processing tomato using the surface renewal technique
- Abstract: April 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 114, Issue 4
  
  The use of the surface renewal (SR) technique for evapotranspiration (ET) estimates of processing tomato crop was examined. The objective was to study the effects of sampling rate, in the range 1–10 Hz, and measurement height, on the SR method performance. Measurements were carried out in a processing tomato crop at the Hula Valley of Northern Israel. Eddy covariance and surface renewal systems were deployed simultaneously for a period of 11 days on August 2010. Data from the first 6 measurement days was used for calibration and data of the rest 5 days for verification of ET data. Three parameters were chosen for optimising the performance of the SR technique: the sampling rate, the SR analysis time lag and sensor height. Results showed that during calibration the best combination of coefficient of determination (R 2 = 0.86) and root mean square error (RMSE = 29.57 W m−2) between EC and SR half-hourly sensible heat fluxes was obtained for temperature fluctuations measured at the level of the canopy top, using a 0.25 s analysis time lag and 10 Hz sampling rate. For these operational conditions, and using the corresponding calibration coefficient α = 2.47, mean ratio between daily estimated (by SR) and deduced (from EC) ET during the verification period was 1.03 ± 0.02. Data analyses at lower sampling rates of 1, 2 and 5 Hz and for the same measurement height also provided good agreement between estimated and measured daily ET.
  Highlights ► Processing tomato evapotranspiration was estimated by the Surface Renewal method. ► The method was successfully calibrated for the study conditions. ► Best performance was at 10 Hz sampling rate and measurements at canopy height. ► During validation, estimated values were in good agreement with measured ones. ► Method's performance was almost insensitive to sampling rates between 1 and 10 Hz.
  
  PubDate: 2013-03-08T00:06:01Z
Examination of the Bowen ratio energy balance technique for evapotranspiration estimates in screenhouses
- Abstract: April 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 114, Issue 4
  
  For the first time, the applicability of the Bowen ratio energy balance technique to evapotranspiration estimates in screenhouses was investigated. Measurements were conducted at the centre of a large banana screenhouse in northern Israel. Data of eddy covariance flux measurements and vertical temperature and humidity gradients were used to estimate the ratio between the turbulent transport coefficients of heat and water vapour. Data from 8 days were used for calibration, and those from an additional 4 days for validation of the method. Calibration results showed that the ratio between the turbulent transport coefficients was close to unity during most daytime hours, indicating that the method is applicable in the screenhouse environment. The Bowen ratio was nearly constant during most daytime hours, with an average of 0.41 ± 0.07. During the validation period, very good agreement was obtained between the latent heat flux as estimated with the Bowen ratio method and that deduced from EC measurements.
  Highlights ► The Bowen ratio technique was examined in a large banana screenhouse. ► The ratio between transport coefficients of heat and water vapour was close to unity. ► The Bowen ratio was nearly constant during most daylight hours, averaged about 0.4.
  
  PubDate: 2013-03-08T00:06:01Z
Twenty five years of remote sensing in precision agriculture: Key advances and remaining knowledge gaps
- Abstract: April 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 114, Issue 4
  
  Precision agriculture dates back to the middle of the 1980's. Remote sensing applications in precision agriculture began with sensors for soil organic matter, and have quickly diversified to include satellite, aerial, and hand held or tractor mounted sensors. Wavelengths of electromagnetic radiation initially focused on a few key visible or near infrared bands. Today, electromagnetic wavelengths in use range from the ultraviolet to microwave portions of the spectrum, enabling advanced applications such as light detection and ranging (LiDAR), fluorescence spectroscopy, and thermal spectroscopy, along with more traditional applications in the visible and near infrared portions of the spectrum. Spectral bandwidth has decreased dramatically with the advent of hyperspectral remote sensing, allowing improved analysis of specific compounds, molecular interactions, crop stress, and crop biophysical or biochemical characteristics. A variety of spectral indices now exist for various precision agriculture applications, rather than a focus on only normalised difference vegetation indices. Spatial resolution of aerial and satellite remote sensing imagery has improved from 100's of m to sub-metre accuracy, allowing evaluation of soil and crop properties at fine spatial resolution at the expense of increased data storage and processing requirements. Temporal frequency of remote sensing imagery has also improved dramatically. At present there is considerable interest in collecting remote sensing data at multiple times in order to conduct near real time soil, crop and pest management.
  Highlights ► Rapid advances in remote sensing for precision agriculture have occurred. ► Satellite imagery has improved in spatial resolution, return visit frequency and spectral resolution. ► Aerial hyperspectral imagery has revolutionized precision agriculture. ► Ground based sensors have been developed for on-the-go monitoring of crop and soil characteristics. ► The future challenge is to develop approaches that provide customized management for individual plants.
  
  PubDate: 2013-03-08T00:06:01Z
Editorial Board
- Abstract: April 2013
  Publication year: 2013
  Source:Biosystems Engineering, Volume 114, Issue 4
  
  PubDate: 2013-03-08T00:06:01Z
Field partition by proximal and remote sensing data fusion
- Abstract: Available online 23 February 2013
  Publication year: 2013
  Source:Biosystems Engineering
  
  There is a growing interest in the application of remote and proximal sensing technologies to precision agriculture for the estimation of soil and crop variability. The objective of this research was to jointly analyse data from proximal and remote sensors through geostatistics and a non-parametric clustering approach to delineate homogenous zones. The study was carried out on tomato crop in an experimental field in southern Italy. The field was split into two blocks in order to differentiate the two irrigation treatments: Optimal water supply conditions (OP), Deficit irrigation conditions. The collected multi-sensor data were: 1) bulk electrical conductivity from electromagnetic induction (EMI) sensor, 2) vegetation indices (normalised difference vegetation index, R NIR/R Green index and normalised difference red edge) calculated from two remote sensing images of WorldView-2 satellite; 3) radiance data from one GeoEye satellite image. Multivariate geostatistics and a clustering approach were applied to the overall multi-sensor dataset reported in the above points 1 and 2, whereas the data of the point 3 were clustered to validate the field delineation. The approach allowed us to integrate the data of the different sensors and to identify three homogenous sub-field areas related to the intrinsic properties of soil and the crop response. The comparison between the previous delineation and the one obtained with GeoEye data, after water treatment differentiation, showed that the plant response was more affected by water management than soil properties. The approach has the potential to define prescription maps in precision agriculture.
  Highlights ► Data from proximal and remote sensors were jointly analysed. ► A tomato field was split in two irrigation blocks. ► Multivariate geostatistics and a clustering approach were applied to the data. ► Three homogenous zones were delineated. ► The approach has the potential for defining prescription maps in PA.
  
  PubDate: 2013-02-24T00:02:36Z
Special issue on sensors in agriculture
- Abstract: Available online 19 February 2013
  Publication year: 2013
  Source:Biosystems Engineering
  
  PubDate: 2013-02-20T00:02:11Z
Spatial–spectral processing strategies for detection of salinity effects in cauliflower, aubergine and kohlrabi
- Abstract: Available online 1 February 2013
  Publication year: 2013
  Source:Biosystems Engineering
  
  Hyperspectral images and spectroradiometer measurements were taken from cauliflower (Brassica oleracea, Botrytis group), aubergine (Solanum melongena) and kohlrabi (Brassica oleracea, Gongylodes group) plants in a controlled experiment. Plants were grown in media with sodium chloride (NaCl) concentrations between 30 and 150 mmol. Spectral and spatial processing techniques were developed to assess the ability to distinguish between plants exposed to various levels of salinity stress. Local autocorrelation analysis was used to detect the spatial patterns that characterise the effects of salinity on crop canopy. This analysis was applied on a vegetation index in the spectral range of 435–554 nm, the green indigo ratio (GIR) index. The processing strategies that were developed were able to distinguish three levels of salinity effects. The strategy based on a combined spatial–spectral index yielded the most consistent results with average total accuracy of 62%, whereas accuracies obtained with known spectral vegetation indices were 29%. The presented method may be implemented in other cases of vegetation stresses where symptoms are characterised by patchiness and can be imaged, not necessarily in the visible spectral range (400–750 nm).
  Highlights ► The effect of salinity in three crops was detected using hyper spectral images. ►Spatial–spectral indices were extracted from hyperspectral images. ► Local autocorrelation analysis revealed spatial patterns of salinity on crop canopy. ► The salinity effect was expressed in the spatial distribution of index fluctuations.
  
  PubDate: 2013-02-04T00:02:31Z
Nonlinear methods for estimation of maturity stage, total chlorophyll, and carotenoid content in intact bell peppers
- Abstract: Available online 18 January 2013
  Publication year: 2013
  Source:Biosystems Engineering
  
  The objective of the present study was to develop a fast, non-destructive method to measure the bell pepper chlorophyll content, which is one of the major maturity indices for determining harvesting time. The research is based on visible–near-infrared (VIS–NIR) and short-wave infrared (SWIR) spectrometry. Red, green and yellow varieties were examined: ‘Celica’, ‘Ever Green’ and ‘No.117’, respectively. Peppers were marked at the flowering stage, and 20 samples of each variety were collected weekly during nine weeks until full growth. Disc samples of the fruit flesh were analysed destructively, the spectrometry data were analysed chemometrically, and a nonlinear-kernel algorithm was developed for spectral data analysis. Comparisons were made between the linear and nonlinear regression analyses of the raw reflectance spectra (R), on one hand, and the preprocessed spectra such as the first derivative of R (D 1 R), log(1/R), D 1(log(1/R)) and D 2(log(1/R)), on the other hand. For further evaluation of the regression models a standardised weighted sum (SWS) index was developed, based on criterion weighting. The developed kernel algorithm, partial least squares (PLSR), and support vector machine (SVM) regression models were able to predict total chlorophyll and carotenoid contents for all three tested bell pepper cultivars, with average cross-validation errors of 0.007 and 0.01 mg g−1, respectively. The kernel nonlinear analysis of the spectral data yielded the most promising regression models for all three cultivars.
  Highlights ► An evaluation method is suggested for objective comparison among regression models. ► Kernel method efficiently predicted total chlorophyll and carotenoid content. ► Efficient maturity stage prediction was achieved by fusion of constituents. ► The best fused constituents' prediction was achieved by nonlinear regression.
  
  PubDate: 2013-01-19T09:02:49Z
Ground-based remote sensing system for irrigation scheduling
- Abstract: Available online 5 January 2013
  Publication year: 2013
  Source:Biosystems Engineering
  
  The Penman–Monteith (PM) equation is the best-known approach to estimate evapotranspiration from meteorological data on a daily basis. Limited information is available on an hourly basis, mostly because of the requirement for the parameterization of aerodynamic and canopy resistance (ra and rc, respectively), which are difficult to estimate. The objectives of this study were a) to develop a new remote sensing approach to estimate rc and ra from the output of an infrared radiometric system; b) to include rc and ra in the PM equation to calculate evapotranspiration (ET) for irrigation scheduling; and c) to formulate a numerical model that solves the changes in soil water profile with time using a one-dimensional Richards' equation (RE). The integration of the time-dependent changes in the soil water profile provided the effect of irrigation on soil water balance. Infrared radiometers and a conventional meteorological system were stationed on top of a linear move irrigation system. The output signals were collected remotely in a personal computer (PC) that was equipped with specific code to solve the PM equation for ra and rc, which were then used to calculate the water requirement of the plants. The software used the actual ET as a boundary condition for the instantaneous calculations of the soil water balance components based on the hydraulic properties of the soil in Western Negev, Israel. Currently, all components that are required to improve irrigation management are controlled remotely, including the automatic data collection, models, hardware and software.
  Highlights ► Combination of measurements with IR radiometers and mathematical solution of Richards' equation. ► Sensors mounted on a linear moving irrigation system provided evapotranspiration data. ► ET data used as boundary conditions for the calculations of soil water transport. ► Results were used to estimate instantaneous water requirements for potato.
  
  PubDate: 2013-01-11T09:03:52Z
Combining spectral and spatial information from aerial hyperspectral images for delineating homogenous management zones
- Abstract: Available online 8 December 2012
  Publication year: 2012
  Source:Biosystems Engineering
  
  Most available hyperspectral image processing algorithms analyse the data based on the spectral information exclusively and do not treat the data as an image. Methods that use spatial and spectral information mostly perform a two-step processing technique, i.e. the spatial analysis is used as a retrospective smoothing. In this paper a recently developed method, which is based on the beamlet analysis, is presented. This method, which uses spectral and spatial information simultaneously, was adjusted in this study to multi- and hyperspectral images. The results of the new methodology, called the recursive dyadic partitioning=beamlet decorated (RDP-BD), were compared to fuzzy C-means spectral classification and to spatially coherent regions classification. These methods were used to classify nitrogen levels in an experimental potato plot, which was grown under different nitrogen treatments. The image was classified by these three methods based on the combination of two spectral indexes: transformed chlorophyll absorption reflectance index (TCARI) and optimized soil-adjust vegetation index (OSAVI), the first three principal components of the image and the complete 210 bands of the hyperspectral image. Although the spatial analysis slightly improved the classification (from 71% to 78%), the most pronounced contribution was its ability to divide the experimental plot into zones that fit the treatments borders. In addition, it was shown that the principle components and the whole spectra out-performed the spectral index. These methods should assist with testing the efficiency of variable rate nitrogen fertilisation as they utilise the informative spectral data to properly classify nitrogen level in the pixel scale and delineate management zones at the field scale.
  Highlights ► Three different classification methods were examined. ► The methods use spatial and spectral information differently. ► Different data sets were examined: index, PCA and HS. ► Combining spatial and spectra information is superior. ► Using the whole spectra out-performed the spectral index.
  
  PubDate: 2012-12-18T08:02:55Z