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    Optimized Deep Learning Model as a Basis for Fast UAV Mapping of Weed Species in Winter Wheat Crops
    (Basel : MDPI AG, 2021) de Camargo, Tibor; Schirrmann, Michael; Landwehr, Niels; Dammer, Karl-Heinz; Pflanz, Michael
    Weed maps should be available quickly, reliably, and with high detail to be useful for site-specific management in crop protection and to promote more sustainable agriculture by reducing pesticide use. Here, the optimization of a deep residual convolutional neural network (ResNet-18) for the classification of weed and crop plants in UAV imagery is proposed. The target was to reach sufficient performance on an embedded system by maintaining the same features of the ResNet-18 model as a basis for fast UAV mapping. This would enable online recognition and subsequent mapping of weeds during UAV flying operation. Optimization was achieved mainly by avoiding redundant computations that arise when a classification model is applied on overlapping tiles in a larger input image. The model was trained and tested with imagery obtained from a UAV flight campaign at low altitude over a winter wheat field, and classification was performed on species level with the weed species Matricaria chamomilla L., Papaver rhoeas L., Veronica hederifolia L., and Viola arvensis ssp. arvensis observed in that field. The ResNet-18 model with the optimized image-level prediction pipeline reached a performance of 2.2 frames per second with an NVIDIA Jetson AGX Xavier on the full resolution UAV image, which would amount to about 1.78 ha h−1 area output for continuous field mapping. The overall accuracy for determining crop, soil, and weed species was 94%. There were some limitations in the detection of species unknown to the model. When shifting from 16-bit to 32-bit model precision, no improvement in classification accuracy was observed, but a strong decline in speed performance, especially when a higher number of filters was used in the ResNet-18 model. Future work should be directed towards the integration of the mapping process on UAV platforms, guiding UAVs autonomously for mapping purpose, and ensuring the transferability of the models to other crop fields.
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    Impact of process parameters and bulk properties on quality of dried hops
    (Basel : MDPI AG, 2020) Raut, Sharvari; Gersdorff, Gardis J.E. von; Münsterer, Jakob; Kammhuber, Klaus; Hensel, Oliver; Sturm, Barbara
    Hops are critical to the brewing industry. In commercial hop drying, a large bulk of hops is dried in multistage kilns for several hours. This affects the drying behavior and alters the amount and chemical composition of the hop oils. To understand these changes, hops of the var. Hallertauer Tradition were dried in bulks of 15, 25 and 35 kg/m2 at 60◦C and 0.35 m/s. Additionally, bulks of 25 kg/m2 were also dried at 65◦C and 0.45 m/s to assess the effect of change in temperature and velocity, respectively. The results obtained show that bulk weights significantly influence the drying behavior. Classification based on the cone size reveals 45.4% medium cones, 41.2% small cones and 8.6% large cones. The highest ∆E value of 6.3 and specific energy consumption (113,476 kJ/kgH2O) were observed for the 15 kg/m2 bulk. Increasing the temperature from 60◦C to 65◦C increased the oil yield losses by about 7% and myrcene losses by 22%. The results obtained show that it is important to define and consider optimum bulk and process parameters, to optimize the hop drying process to improve the process efficiency as well the product quality. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.
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    Sensor-based detection of the severity of hyperkeratosis in the teats of dairy cows
    (Basel : MDPI AG, 2018) Demba, S.; Hoffmann, G.; Ammon, C.; Rose-Meierhöfer, S.
    The aim of this study was to evaluate whether the severity of hyperkeratosis (HK) in the teats of dairy cows can be assessed by a dielectric measurement. The study focused on surveying the occurrence of hyperkeratosis in a total of 241 teats of lactating dairy cows. A scoring system consisting of four categories was used to macroscopically assess the severity of HK. Additionally, the dielectric constant (DC) of all teats with milkability was measured in a double iteration with the MoistureMeterD (Delfin Technologies, Kuopio, Finland) on four different days. The Spearman rank correlation coefficient revealed a negative correlation between the DC and HK score (rs = −0.55 to −0.36). The results of the regression analysis showed that the DC values differed significantly between healthy teat ends (≤2) and teat ends with HK (≥3). Thus, the non-invasive measurement of DC provides a promising method of objectively assessing the occurrence and severity of HK.
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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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    Effects of the COVID-19 Pandemic on Food Security and Agriculture in Iran: A Survey
    (Basel : MDPI AG, 2021) Rad, Abdullah Kaviani; Shamshiri, Redmond R.; Azarm, Hassan; Balasundram, Siva K.; Sultan, Muhammad
    The consequences of COVID-19 on the economy and agriculture have raised many concerns about global food security, especially in developing countries. Given that food security is a critical component that is affected by global crises, beside the limited studies carried out on the macro-impacts of COVID-19 on food security in Iran, this paper is an attempt to address the dynamic impacts of COVID-19 on food security along with economic and environmental challenges in Iran. For this purpose, a survey was conducted with the hypothesis that COVID-19 has not affected food security in Iran. To address this fundamental hypothesis, we applied the systematic review method to obtain the evidence. Various evidences, including indices and statistics, were collected from national databases, scientific reports, field observations, and interviews. Preliminary results revealed that COVID-19 exerts its effects on the economy, agriculture, and food security of Iran through six major mechanisms, corresponding to a 30% decrease in the purchasing power parity in 2020 beside a significant increase in food prices compared to 2019. On the other hand, the expanding environmental constraints in Iran reduce the capacity of the agricultural sector to play a crucial role in the economy and ensure food security, and in this regard, COVID-19 forces the national programs and budget to combat rising ecological limitations. Accordingly, our study rejects the hypothesis that COVID-19 has not affected food security in Iran.
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    Farm water productivity in conventional and organic farming: Case studies of cow-calf farming systems in North Germany
    (Basel : MDPI AG, 2018) Vellenga, L.; Qualitz, G.; Drastig, K.
    The increase of organic agriculture in Germany raises the question of how water productivity differs from conventional agriculture. On three organic and two conventionally farming systems in Germany, water flows and water related indicators were quantified. Farm water productivity (FWP), farm water productivity of cow-calf production (FWPlivestock), and farm water productivity of food crop production (FWPfood crops) were calculated using the modeling software AgroHyd Farmmodel. The FWP was calculated on a mass and monetary basis. FWPlivestock showed the highest productivity on a mass basis occurring on a conventional farm with 0.09 kg m-3Winput, whereas one organic farm and one conventional farm showed the same results. On a monetary basis, organic cow-calf farming systems showed the highest FWPlivestock, with 0.28 € m-3Winput. Since the productivity of the farm depends strongly on the individual cultivated plants, FWPfood crops was compared at the level of the single crop. The results show furthermore that even with a precise examination of farm water productivity, a high bandwidth of temporal and local values are revealed on different farms: generic FWP for food crops and livestock are not within reach.
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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.
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    Effect of In Vitro Digestion on the Antioxidant and Angiotensin-Converting Enzyme Inhibitory Potential of Buffalo Milk Processed Cheddar Cheese
    (Basel : MDPI AG, 2021) Shaukat, Amal; Nadeem, Muhammad; Qureshi, Tahir Mahmood; Kanwal, Rabia; Sultan, Muhammad; Kashongwe, Olivier Basole; Shamshiri, Redmond R.; Murtaza, Mian Anjum
    The purpose of this study was to develop an in-vitro digestion protocol to evaluate the antioxidant potential of the peptides found in processed cheddar cheese using digestion enzymes. We first studied antioxidant and angiotensin-converting enzyme (ACE) inhibition and antioxidant activities of processed cheddar cheese with the addition of spices e.g., cumin, clove, and black pepper made from buffalo milk and ripened for 9 months. Then we conducted an in vitro digestion of processed cheddar cheese by gastric and duodenal enzymes. Freeze-dried water (WSE) and ethanol-soluble fractions (ESE) of processed cheddar cheese were also monitored for their ACE inhibition activity and antioxidant activities. In our preliminary experiments, different levels of spices (cumin, clove, and black pepper) were tested into a cheese matrix and only one level 0.2 g/100 g (0.2%) based on cheese weight was considered good after sensory evaluation. Findings of the present study revealed that ACE-inhibitory potential was the highest in processed cheese made from buffalo milk with the addition of 0.2% cumin, clove, and black pepper. A significant increase in ACE-inhibition (%) of processed cheddar cheese, as well as its WSE and ESE, was obtained. Lower IC50 values were found after duodenal phase digestion compared to oral phase digestion.
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    Effects of Pre-Processing Hot-Water Treatment on Aroma Relevant VOCs of Fresh-Cut Apple Slices Stored in Sugar Syrup
    (Basel : MDPI AG, 2020) Rux, Guido; Efe, Efecan; Ulrichs, Christian; Huyskens-Keil, Susanne; Hassenberg, Karin; Herppich, Werner B.
    In practice, fresh-cut fruit and fruit salads are currently stored submerged in sugar syrup (approx. 20%) to prevent browning, to slow down physiological processes and to extend shelf life. To minimize browning and microbial spoilage, slices may also be dipped in a citric acid/ascorbic acid solution for 5 min before storage in sugar syrup. To prevent the use of chemicals in organic production, short-term (30 s) hot-water treatment (sHWT) may be an alternative for gentle sanitation. Currently, profound knowledge on the impact of both sugar solution and sHWT on aroma and physiological properties of immersed fresh-cuts is lacking. Aroma is a very important aspect of fruit quality and generated by a great variety of volatile organic compounds (VOCs). Thus, potential interactive effects of sHWT and sugar syrup storage on quality of fresh-cut apple slices were evaluated, focusing on processing-induced changes in VOCs profiles. Intact ’Braeburn’ apples were sHW-treated at 55 °C and 65 °C for 30 s, sliced, partially treated with a commercial ascorbic/citric acid solution and slices stored in sugar syrup at 4 °C up to 13 days. Volatile emission, respiration and ethylene release were measured on storage days 5, 10 and 13. The impact of sHWT on VOCs was low while immersion and storage in sugar syrup had a much higher influence on aroma. sHWT did not negatively affect aroma quality of products and may replace acid dipping.
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    Evaluating Soil-Borne Causes of Biomass Variability in Grassland by Remote and Proximal Sensing
    (Basel : MDPI AG, 2019) Vogel, Sebastian; Gebbers, Robin; Oertel, Marcel; Kramer, Eckart
    On a grassland field with sandy soils in Northeast Germany (Brandenburg), vegetation indices from multi-spectral UAV-based remote sensing were used to predict grassland biomass productivity. These data were combined with soil pH value and apparent electrical conductivity (ECa) from on-the-go proximal sensing serving as indicators for soil-borne causes of grassland biomass variation. The field internal magnitude of spatial variability and hidden correlations between the variables of investigation were analyzed by means of geostatistics and boundary-line analysis to elucidate the influence of soil pH and ECa on the spatial distribution of biomass. Biomass and pH showed high spatial variability, which necessitates high resolution data acquisition of soil and plant properties. Moreover, boundary-line analysis showed grassland biomass maxima at pH values between 5.3 and 7.2 and ECa values between 3.5 and 17.5 mS m−1. After calibrating ECa to soil moisture, the ECa optimum was translated to a range of optimum soil moisture from 7% to 13%. This matches well with to the plant-available water content of the predominantly sandy soil as derived from its water retention curve. These results can be used in site-specific management decisions to improve grassland biomass productivity in low-yield regions of the field due to soil acidity or texture-related water scarcity.