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- ItemEstimating 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, ManuelaData 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.
- ItemRapid determination of lime requirement by mid-infrared spectroscopy: A promising approach for precision agriculture(Weinheim : Wiley-VCH, 2019) Leenen, Matthias; Welp, Gerhard; Gebbers, Robin; Pätzold, StefanMid-infrared spectroscopy (MIRS) has proven to be a cost-effective, high throughput measurement technique for soil analysis. After multivariate calibration mid-infrared spectra can be used to predict various soil properties, some of which are related to lime requirement (LR). The objective of this study was to test the performance of MIRS for recommending variable rate liming on typical Central European soils in view of precision agriculture applications. In Germany, LR of arable topsoils is commonly derived from the parameters organic matter content (SOM), clay content, and soil pH (CaCl2) as recommended by the Association of German Agricultural Analytical and Research Institutes (VDLUFA). We analysed a total of 458 samples from six locations across Germany, which all revealed large within-field soil heterogeneity. Calcareous topsoils were observed at some positions of three locations (79 samples). To exclude such samples from LR determination, peak height at 2513 cm−1 of the MIR spectrum was used for identification. Spectra-based identification was accurate for carbonate contents > 0.5%. Subsequent LR derivation (LRSPP) from MIRS-PLSR predictions of SOM, clay, and pH (CaCl2) for non-calcareous soil samples using the VDLUFA look-up tables was successful for all locations (R2 = 0.54–0.82; RMSE = 857–1414 kg CaO ha−1). Alternatively, we tested direct LR prediction (LRDP) by MIRS-PLSR and also achieved satisfactory performance (R2 = 0.52–0.77; RMSE = 811–1420 kg CaO ha−1; RPD = 1.44–2.08). Further improvement was achieved by refining the VDLUFA tables towards a stepless algorithm. It can be concluded that MIRS provides a promising approach for precise LR estimation on heterogeneous arable fields. Large sample numbers can be processed with low effort which is an essential prerequisite for variable rate liming in precision agriculture. © 2019 The Authors. Journal of Plant Nutrition and Soil Science published by WILEY-VCH Verlag GmbH & Co. KGaA
- ItemMethane prediction based on individual or groups of milk fatty acids for dairy cows fed rations with or without linseed(New York, NY [u.a.] : Elsevier, 2019) Engelke, Stefanie W.; Daş, Gürbüz; Derno, Michael; Tuchscherer, Armin; Wimmers, Klaus; Rychlik, Michael; Kienberger, Hermine; Berg, Werner; Kuhla, Björn; Metges, Cornelia C.Milk fatty acids (MFA) are a proxy for the prediction of CH4 emission from cows, and prediction differs with diet. Our objectives were (1) to compare the effect of diets on the relation between MFA profile and measured CH4 production, (2) to predict CH4 production based on 6 data sets differing in the number and type of MFA, and (3) to test whether additional inclusion of energy-corrected milk (ECM) yield or dry matter intake (DMI) as explanatory variables improves predictions. Twenty dairy cows were used. Four diets were used based on corn silage (CS) or grass silage (GS) without (L0) or with linseed (LS) supplementation. Ten cows were fed CS-L0 and CS-LS and the other 10 cows were fed GS-L0 and GS-LS in random order. In feeding wk 5 of each diet, CH4 production (L/d) was measured in respiration chambers for 48 h and milk was analyzed for MFA concentrations by gas chromatography. Specific CH4 prediction equations were obtained for L0-, LS-, GS-, and CS-based diets and for all 4 diets collectively and validated by an internal cross-validation. Models were developed containing either 43 identified MFA or a reduced set of 7 groups of biochemically related MFA plus C16:0 and C18:0. The CS and LS diets reduced CH4 production compared with GS and L0 diets, respectively. Methane yield (L/kg of DMI) reduction by LS was higher with CS than GS diets. The concentrations of C18:1 trans and n-3 MFA differed among GS and CS diets. The LS diets resulted in a higher proportion of unsaturated MFA at the expense of saturated MFA. When using the data set of 43 individual MFA to predict CH4 production (L/d), the cross-validation coefficient of determination (R2 CV) ranged from 0.47 to 0.92. When using groups of MFA variables, the R2 CV ranged from 0.31 to 0.84. The fit parameters of the latter models were improved by inclusion of ECM or DMI, but not when added to the data set of 43 MFA for all diets pooled. Models based on GS diets always had a lower prediction potential (R2 CV = 0.31 to 0.71) compared with data from CS diets (R2 CV = 0.56 to 0.92). Models based on LS diets produced lower prediction with data sets with reduced MFA variables (R2 CV = 0.62 to 0.68) compared with L0 diets (R2 CV = 0.67 to 0.80). The MFA C18:1 cis-9 and C24:0 and the monounsaturated FA occurred most often in models. In conclusion, models with a reduced number of MFA variables and ECM or DMI are suitable for CH4 prediction, and CH4 prediction equations based on diets containing linseed resulted in lower prediction accuracy. © 2019 American Dairy Science Association
- ItemThe physiological and productivity effects of heat stress in cattle : a review(Warsaw : De Gruyter Open, 2019) Herbut, Piotr; Angrecka, Sabina; Godyń, Dorota; Hoffmann, GundulaA trend of global warming has been observed over the last few years and it has often been dis-cussed whether there is an effect on livestock. numerous studies have been published about heat stress in cattle and its influence on the physiology and productivity of animals. Preventing the negative effects of heat stress on cattle is essential to ensure animal welfare, health and produc-tivity. Monitoring and analysis of physiological parameters lead to a better understanding of the adaptation processes. This can help to determine the risk of climate change and its effects on performance characteristics, e.g. milk yield and reproduction. This, in turn, makes it possible to develop effective measures to mitigate the impact of heat load on animals. The aim of this article is to provide an overview of the current literature. studies especially about the physiological and productive changes due to heat stress in cattle have been summarised in this review. The direction of future research into the aspect of heat stress in cattle is also indicated
- ItemEffect of two cooling frequencies on respiration rate in lactating dairy cows under hot and humid climate conditions(Warsaw : De Gruyter Open, 2019) Pinto, Severino; Hoffmann, Gundula; Ammon, Christian; Heuwieser, Wolfgang; Levit, Harel; Halachmi, Ilan; Amon, ThomasThe aim of this study was to evaluate the effects of evaporative cooling at two different frequen-cies per day on the respiration rate (rr) of lactating dairy cows, considering cow-related factors. twenty multiparous israeli holstein dairy cows housed in a naturally ventilated cowshed were di-vided randomly into two treatment groups. the cows of both groups were exposed to 3 or 8 cooling sessions per day (3xcool vs. 8xcool, respectively). the rr was observed hourly, with a maximum of 12 measurements per day. Body posture (standing vs. lying) was simultaneously documented. milk yield was recorded daily. coat color was determined from a digital photograph. the rr of standing and lying cows was lower in the 8xcool group (60.2 and 51.6 breaths per min (bpm), re-spectively) than in the 3xcool group (73.1 and 65.6 bpm, respectively). For each increment of five kilograms of milk produced, rr increased by one bpm, and the rr of cows in early days in milk (dim) was 12.3 bpm higher than that of cows in late dim. in conclusion, eight cooling sessions per day instead of three lead to a rr abatement in heat-stressed cows under hot conditions, and cow-related factors directly impact the rr during heat stress assessment
- ItemOpinion paper : Measuring livestock robustness and resilience : are we on the right track?(Amsterdam : Elsevier, 2019) Llonch, P.; Hoffmann, G.; Bodas, R.; Mirbach, D.; Verwer, C.; Haskell, M.J.[No abstract available]
- ItemRecent advances in d-lactic acid production from renewable resources: Case studies on agro-industrial waste streams(Zagreb : Faculty of Food Technology and Biotechnology, University of Zagreb, 2019) Alexandri, Maria; Schneider, Roland; Mehlmann, Kerstin; Venus, JoachimThe production of biodegradable polymers as alternatives to petroleum-based plastics has gained significant attention in the past years. To this end, polylactic acid (PLA) constitutes a promising alternative, finding various applications from food packaging to pharmaceuticals. Recent studies have shown that d-lactic acid plays a vital role in the production of heat-resistant PLA. At the same time, the utilization of renewable resources is imperative in order to decrease the production cost. This review aims to provide a synopsis of the current state of the art regarding d-lactic acid production via fermentation, focusing on the exploitation of waste and byproduct streams. An overview of potential downstream separation schemes is also given. Additionally, three case studies are presented and discussed, reporting the obtained results utilizing acid whey, coffee mucilage and hydrolysate from rice husks as alternative feedstocks for d-lactic acid production. © 2019, University of Zagreb.
- ItemExtraction of phenolic compounds from palm oil processing residues and their application as antioxidants(Zagreb : Faculty of Food Technology and Biotechnology, University of Zagreb, 2019) Tsouko, Erminda; Alexandri, Maria; Fernandes, Keysson Vieira; Freire, Denise Maria Guimarães; Mallouchos, Athanasios; Koutinas, Apostolis A.The side streams derived from the palm oil production process, namely palm kernel cake, palm pressed fibre, palm kernel shells and empty fruit bunches, were evaluated as sources of phenolic compounds. Among these streams, kernel cake had the highest total phenolic content (in mg of gallic acid equivalents (GAE) per g of dry sample) with a value of 5.19, whereas the empty fruit bunches had the lowest value (1.79). The extraction time and liquid-to-solid ratio were investigated to optimize the phenolic extraction. Kernel cake exhibited the highest total phenolic content (5.35 mg/g) with a liquid-to-solid ratio of 40:1 during 20 min of extraction. The main phenolic compounds of the extracts deriving from all byproduct streams were also identified and quantified with HPLC-DAD. Pyrogallol, 4-hydroxybenzoic acid, gallic acid and ferulic acid were the main compounds found in kernel cake extracts. Empty fruit bunch and pressed fibre extracts were also rich in 4-hydroxybenzoic acid, while pyrogallol was the predominant compound in kernel shell extracts. All extracts showed antioxidant activity as it was indicated from the results of DPPH analysis and subsequently tested in sunflower oil aiming to prolong its shelf life. The addition of 0.8 % kernel cake extract increased the induction time of sunflower oil more than 50 %. According to the results obtained in this study, kernel cake extracts could be considered as a value-added co-product with a potential application as antioxidants in the food industry. © 2018 University of Zagreb.
- ItemPrediction of the biogas production using GA and ACO input features selection method for ANN model(Amsterdam [u.a.] : Elsevier, 2019) Beltramo, Tanja; Klocke, Michael; Hitzmann, BerndThis paper presents a fast and reliable approach to analyze the biogas production process with respect to the biogas production rate. The experimental data used for the developed models included 15 process variables measured at an agricultural biogas plant in Germany. In this context, the concentration of volatile fatty acids, total solids, volatile solids acid detergent fibre, acid detergent lignin, neutral detergent fibre, ammonium nitrogen, hydraulic retention time, and organic loading rate were used. Artificial neural networks (ANN) were established to predict the biogas production rate. An ant colony optimization and genetic algorithms were implemented to perform the variable selection. They identified the significant process variables, reduced the model dimension and improved the prediction capacity of the ANN models. The best prediction of the biogas production rate was obtained with an error of prediction of 6.24% and a coefficient of determination of R2 = 0.9.
- ItemEffects of Pre-Processing Short-Term Hot-Water Treatments on Quality and Shelf Life of Fresh-Cut Apple Slices(Basel : MDPI AG, 2019) Rux, Guido; Efe, Efecan; Ulrichs, Christian; Huyskens-Keil, Susanne; Hassenberg, Karin; Herppich, Werner B.Processing, especially cutting, reduces the shelf life of fruits. In practice, fresh-cut fruit salads are, therefore, often sold immersed in sugar syrups to increase shelf life. Pre-processing short-term hot-water treatments (sHWT) may further extend the shelf life of fresh-cuts by effectively reducing microbial contaminations before cutting. In this study, fresh-cut ‘Braeburn’ apples, a major component of fruit salads, were short-term (30 s) hot water-treated (55 °C or 65 °C), partially treated with a commercial anti-browning solution (ascorbic/citric acid) after cutting and, thereafter, stored immersed in sugar syrup. To, for the first time, comprehensively and comparatively evaluate the currently unexplored positive or negative effects of these treatments on fruit quality and shelf life, relevant parameters were analyzed at defined intervals during storage at 4 °C for up to 13 days. Compared to acid pre-treated controls, sHWT significantly reduced the microbial loads of apple slices but did not affect their quality during the 5 day-standard shelf life period of fresh-cuts. Yeasts were most critical for shelf life of fresh-cut apples immersed in sugar syrup. The combination of sHWT and post-processing acid treatment did not further improve quality or extend shelf life. Although sHWT could not extend potential maximum shelf life beyond 10 d, results highlighted the potentials of this technique to replace pre-processing chemical treatments and, thus, to save valuable resources.