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Now showing 1 - 10 of 11
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    Estimating Canopy Parameters Based on the Stem Position in Apple Trees Using a 2D LiDAR
    (Basel : MDPI AG, 2019) Tsoulias, Nikos; Paraforos, Dimitrios S.; Fountas, Spyros; Zude-Sasse, Manuela
    Data of canopy morphology are crucial for cultivation tasks within orchards. In this study, a 2D light detection and range (LiDAR) laser scanner system was mounted on a tractor, tested on a box with known dimensions (1.81 m × 0.6 m × 0.6 m), and applied in an apple orchard to obtain the 3D structural parameters of the trees (n = 224). The analysis of a metal box which considered the height of four sides resulted in a mean absolute error (MAE) of 8.18 mm with a bias (MBE) of 2.75 mm, representing a root mean square error (RMSE) of 1.63% due to gaps in the point cloud and increased incident angle with enhanced distance between laser aperture and the object. A methodology based on a bivariate point density histogram is proposed to estimate the stem position of each tree. The cylindrical boundary was projected around the estimated stem positions to segment each individual tree. Subsequently, height, stem diameter, and volume of the segmented tree point clouds were estimated and compared with manual measurements. The estimated stem position of each tree was defined using a real time kinematic global navigation satellite system, (RTK-GNSS) resulting in an MAE and MBE of 33.7 mm and 36.5 mm, respectively. The coefficient of determination (R2) considering manual measurements and estimated data from the segmented point clouds appeared high with, respectively, R2 and RMSE of 0.87 and 5.71% for height, 0.88 and 2.23% for stem diameter, as well as 0.77 and 4.64% for canopy volume. Since a certain error for the height and volume measured manually can be assumed, the LiDAR approach provides an alternative to manual readings with the advantage of getting tree individual data of the entire orchard.
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    Carbon consumption of developing fruit and the fruit bearing capacity of individual RoHo 3615 and Pinova apple trees
    (Lublin : IA PAS, 2020) Penzel, Martin; Lakso, Alan Neil; Tsoulias, Nikos; Zude-Sasse, Manuela
    This paper describes an approach to estimate the photosynthetic capacity and derive the optimum fruit number for each individual tree, in order to achieve a defined fruit size, which is named as the fruit bearing capacity of the tree. The estimation of fruit bearing capacity was carried out considering the total leaf area per tree as measured with a 2-D LiDAR laser scanner, LALiDAR, and key carbon-related variables of the trees including leaf gas exchange, fruit growth and respiration, in two commercial apple orchards. The range between minLALiDAR and maxLALiDAR was found to be 2.4 m on Pinova and 4.3 m on RoHo 3615 at fully developed canopy. The daily C requirement of the growing fruit and the associated leaf area demand, necessary to meet the average daily fruit C requirements showed seasonal variation, with maximum values in the middle of the growing period. The estimated fruit bearing capacity ranged from 33-95 fruit tree-1 and 45-121 fruit tree-1 on the trees of Pinova and RoHo 3615, respectively. This finding demonstrates sub-optimal crop load at harvest time in both orchards, above or below the fruit bearing capacity for individual trees. In conclusion, the LiDAR measurements of the leaf area combined with a carbon balance model allows for the estimation of fruit bearing capacity for individual trees for precise crop load management. © 2020 Polish Academy of Sciences. All rights reserved.
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    Estimation of Vegetative Growth in Strawberry Plants Using Mobile LiDAR Laser Scanner
    (Basel : MDPI, 2022) Saha, Kowshik Kumar; Tsoulias, Nikos; Weltzien, Cornelia; Zude-Sasse, Manuela
    Monitoring of plant vegetative growth can provide the basis for precise crop manage-ment. In this study, a 2D light detection and ranging (LiDAR) laser scanner, mounted on a linear conveyor, was used to acquire multi-temporal three-dimensional (3D) data from strawberry plants (‘Honeoye’ and ‘Malling Centenary’) 14–77 days after planting (DAP). Canopy geometrical variables, i.e., points per plant, height, ground projected area, and canopy volume profile, were extracted from 3D point cloud. The manually measured leaf area exhibited a linear relationship with LiDAR-derived parameters (R2 = 0.98, 0.90, 0.93, and 0.96 with number of points per plant, volume, height, and projected canopy area, respectively). However, the measuring uncertainty was high in the dense canopies. Particularly, the canopy volume estimation was adapted to the plant habitus to remove gaps and empty spaces in the canopy point cloud. The parametric values for maximum point to point distance (Dmax) = 0.15 cm and slice height (S) = 0.10 cm resulted in R2 = 0.80 and RMSPE = 26.93% for strawberry plant volume estimation considering actual volume measured by water displacement. The vertical volume profiling provided growth data for cultivars ‘Honeoye’ and ‘Malling Centenary’ being 51.36 cm3 at 77 DAP and 42.18 cm3 at 70 DAP, respectively. The results contribute an approach for estimating plant geometrical features and particularly strawberry canopy volume profile based on LiDAR point cloud for tracking plant growth.
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    Seasonal changes in dendrometer-derived stem variation in apple trees grown in temperate climate
    (Lublin : IA PAS, 2022) Rezaei, Yousef; Zude-Sasse, Manuela; Herppich, Werner
    Studies of daily changes in tree trunk diameter provide valuable information concerning growth patterns and their relationships with varying environmental conditions. To date, very few experiments with fruit trees evaluated the effects of climate variation on trunk shrinkage and the duration of the contraction and recovery phases and of growth. In this study, electronic dendrometers continuously monitored trunk diameter and trunk water storage dynamics of drip-irrigated ‘Gala’ apple trees (Malus x domestica Borkh.) during three growing seasons, which differed significantly in temperature, precipitation, air humidity and solar irradiation. It was found that trunk diameter and meteorological variables were closely related, even when excluding the effects of soil water limitations. During each growing season, the durations of the daily contraction phase began to increase with increasing water vapour partial pressure deficit, and decreased again in autumn, when vapour partial pressure decreased. Throughout the season, the duration of the growth phase tended to change inversely to that of both contraction and recovery phase. The relationship between maximum trunk shrinkage and vapour partial pressure was higher post than pre harvest for all years studied. The duration of contraction, recovery, and growth phases may provide valuable information concerning seasonal changes and environmental drivers of water storage dynamics in apple trees.
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    Modeling of Individual Fruit-Bearing Capacity of Trees Is Aimed at Optimizing Fruit Quality of Malus x domestica Borkh. 'Gala'
    (Lausanne : Frontiers Media, 2021) Penzel, Martin; Herppich, Werner B.; Weltzien, Cornelia; Tsoulias, Nikos; Zude-Sasse, Manuela
    The capacity of apple trees to produce fruit of a desired diameter, i.e., fruit-bearing capacity (FBC), was investigated by considering the inter-tree variability of leaf area (LA). The LA of 996 trees in a commercial apple orchard was measured by using a terrestrial two-dimensional (2D) light detection and ranging (LiDAR) laser scanner for two consecutive years. The FBC of the trees was simulated in a carbon balance model by utilizing the LiDAR-scanned total LA of the trees, seasonal records of fruit and leaf gas exchanges, fruit growth rates, and weather data. The FBC was compared to the actual fruit size measured in a sorting line on each individual tree. The variance of FBC was similar in both years, whereas each individual tree showed different FBC in both seasons as indicated in the spatially resolved data of FBC. Considering a target mean fruit diameter of 65 mm, FBC ranged from 84 to 168 fruit per tree in 2018 and from 55 to 179 fruit per tree in 2019 depending on the total LA of the trees. The simulated FBC to produce the mean harvest fruit diameter of 65 mm and the actual number of the harvested fruit >65 mm per tree were in good agreement. Fruit quality, indicated by fruit's size and soluble solids content (SSC), showed enhanced percentages of the desired fruit quality according to the seasonally total absorbed photosynthetic energy (TAPE) of the tree per fruit. To achieve a target fruit diameter and reduce the variance in SSC at harvest, the FBC should be considered in crop load management practices. However, achieving this purpose requires annual spatial monitoring of the individual FBC of trees.
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    Respiratory patterns of European pear (Pyrus communis L. ‘Conference’) throughout pre- and post-harvest fruit development
    (London [u.a.] : Elsevier, 2019) Brandes, Nicole; Zude-Sasse, Manuela
    Information on the developmental stage of pear pre-harvest and in shelf-life is crucial to determine the optimum timing of harvest, post-harvest treatment, and time of consumption ensuring high eating quality. In the present study, CO2 emission and fruit quality of European pear (Pyrus communis L.) ‘Conference’ were analysed pre- and post-harvest with emphasis on shelf life for three years. Additionally, cytochrome and cyanide-resistant O2 consumption were analysed in the last year of experiments. The respiration rate of pear showed typical climacteric rise of CO2 emission in two years only, despite daily measurements. However, in each year the fruit quality in shelf life was closely linked to harvest date suggesting climacteric fruit response. Thus, the developmental stage of ‘Conference’ pear should be analysed by additional methods. Particularly, the cytochrome and cyanide-resistant O2 consumption showed an encouraging potential to obtain data on characteristic respiratory patterns. © 2019
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    Application of Absorption and Scattering Properties Obtained through Image Pre-Classification Method Using a Laser Backscattering Imaging System to Detect Kiwifruit Chilling Injury
    (Basel : MDPI AG, 2021) Yang, Zhuo; Li, Mo; East, Andrew R.; Zude-Sasse, Manuela
    Kiwifruit chilling injury (CI) damage occurs after long-term exposure to low temperature. A non-destructive approach to detect CI injury was tested in the present study, using a laser backscattering image (LBI) technique calibrated with 56 liquid phantoms for providing absorption coefficient (µa) and reduced scattering coefficient (µs’). Calibration of LBI resulted in a true-positive (TP) classification of 91.5% and 65.6% of predicted µs’ and µa, respectively. The optical properties of ‘SunGold™’and ‘Hayward’ kiwifruit were analysed at 520 nm with a two-step protocol capturing pre-classification according to the LBI parameters used in the calibration and estimation with the Farrell equation. Severely injured kiwifruit showed white corky tissue and water soaking, reduced soluble solids content and firmness measured destructively. Non-destructive classification results for ‘SunGold™’ showed a high percentage of TP for severe CI of 92% and 75% using LBI parameters directly and predicted µa and µs’ after pre-classification, respectively. The classification accuracy for severe CI ‘Hayward’ kiwifruit with LBI parameter was low (58%) and with µa and µs’ decreased further (35%), which was assumed to be due to interference caused by the long trichomes on the fruit surface.
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    Validation study for measuring absorption and reduced scattering coefficients by means of laser-induced backscattering imaging
    (Amsterdam [u.a.] : Elsevier Science, 2019) Zude-Sasse, Manuela; Hashim, Norhashila; Hass, Roland; Polley, Nabarun; Regen, Christian
    Decoupling of optical properties appears challenging, but vital to get better insight of the relationship between light and fruit attributes. In this study, nine solid phantoms capturing the ranges of absorption (μa) and reduced scattering (μs’) coefficients in fruit were analysed non-destructively using laser-induced backscattering imaging (LLBI) at 1060 nm. Data analysis of LLBI was carried out on the diffuse reflectance, attenuation profile obtained by means of Farrell's diffusion theory either calculating μa [cm−1] and μs’ [cm−1] in one fitting step or fitting only one optical variable and providing the other one from a destructive analysis. The nondestructive approach was approved when calculating one unknown coefficient non-destructively, while no ability of the method was found to analysis both, μa and μs’, non-destructively. Setting μs’ according to destructive photon density wave (PDW) spectroscopy and fitting μa resulted in root mean square error (rmse) of 18.7% in comparison to fitting μs’ resulting in rmse of 2.6%, pointing to decreased measuring uncertainty, when the highly variable μa was known. The approach was tested on European pear, utilizing destructive PDW spectroscopy for setting one variable, while LLBI was applied for calculating the remaining coefficient. Results indicated that the optical properties of pear obtained from PDW spectroscopy as well as LLBI changed concurrently in correspondence to water content mainly. A destructive batch-wise analysis of μs’ and online analysis of μa may be considered in future developments for improved fruit sorting results, when considering fruit with high variability of μs’. © 2019 The Authors
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    Visible-NIR ‘point’ spectroscopy in postharvest fruit and vegetable assessment: The science behind three decades of commercial use
    (Amsterdam [u.a.] : Elsevier Science, 2020) Walsh, Kerry B.; Blasco, José; Zude-Sasse, Manuela; Sun, Xudong
    The application of visible (Vis; 400–750 nm) and near infrared red (NIR; 750–2500 nm) region spectroscopy to assess fruit and vegetables is reviewed in context of ‘point’ spectroscopy, as opposed to multi- or hyperspectral imaging. Vis spectroscopy targets colour assessment and pigment analysis, while NIR spectroscopy has been applied to assessment of macro constituents (principally water) in fresh produce in commercial practice, and a wide range of attributes in the scientific literature. This review focusses to key issues relevant to the widespread implementation of Vis-NIR technology in the fruit sector. A background to the concepts and technology involved in the use of Vis-NIR spectroscopy is provided and instrumentation for in-field and in-line applications, which has been available for two and three decades, respectively, is described. A review of scientific effort is made for the period 2015 - February 2020, in terms of the application areas, instrumentation, chemometric methods and validation procedures, and this work is critiqued through comparison to techniques in commercial use, with focus to wavelength region, optical geometry, experimental design, and validation procedures. Recommendations for future research activity in this area are made, e.g., application development with consideration of the distribution of the attribute of interest in the product and the matching of optically sampled and reference method sampled volume; instrumentation comparisons with consideration of repeatability, optimum optical geometry and wavelength range). Recommendations are also made for reporting requirements, viz. description of the application, the reference method, the composition of calibration and test populations, chemometric reporting and benchmarking to a known instrument/method, with the aim of maximising useful conclusions from the extensive work being done around the world.
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    Tree Water Status in Apple Orchards Measured by Means of Land Surface Temperature and Vegetation Index (LST–NDVI) Trapezoidal Space Derived from Landsat 8 Satellite Images
    (Basel : MDPI AG, 2020) Zare, Mohammad; Drastig, Katrin; Zude-Sasse, Manuela
    In this study, the split window (SW) method was applied for land surface temperature (LST) retrieval using Landsat 8 in two apple orchards (Glindow, Altlandsberg). Four images were acquired during high demand of irrigation water from July to August 2018. After pre-processing images, the normalized difference vegetation index (NDVI) and LST were calculated by red, NIR, and thermal bands. The results were validated by interpolated infrared thermometer (IRT) measurements using the inverse distance weighting (IDW) method. In the next step, the temperature vegetation index (TVDI) was calculated based on the trapezoidal NDVI/LST space to determine the water status of apple trees in the case studies. Results show good agreement between interpolated LST using IRT measurements and remotely sensed LST calculation using SW in all satellite overpasses, where the absolute mean error was between 0.08 to 4.00 K and root mean square error (RMSE) values ranged between 0.71 and 4.23 K. The TVDI spatial distribution indicated that the trees suffered from water stress on 7 and 23 July and 8 August 2018 in Glindow apple orchard with the mean value of 0.69, 0.57, and 0.73, whereas in the Altlandsberg orchard on 17 August, the irrigation system compensated the water deficit as indicated by the TVDI value of 0.34. Moreover, a negative correlation between TVDI and vegetation water content (VWC) with correlation coefficient (r) of −0.81 was observed. The corresponding r for LST and VWC was equal to −0.89, which shows the inverse relation between water status and temperature-based indices. The results indicate that the LST and/or TVDI calculation using the proposed methods can be effectively applied for monitoring tree water status and support irrigation management in orchards using Landsat 8 satellite images without requiring ground measurements.