2.2. Research ApproachThe research approach in this study consisted of terjemahan - 2.2. Research ApproachThe research approach in this study consisted of Bahasa Indonesia Bagaimana mengatakan

2.2. Research ApproachThe research

2.2. Research Approach
The research approach in this study consisted of five main steps. These are (i) identification of hydrophysical parameters which are inputs of MMF model, (ii) field surveys and informal discussions in order to identify representative soil sampling zones within the study catchment for soil sampling and analysis and also the corresponding vegetation cover conditions, (iii) application of empirical relations which are described by Morgan et al. to calculate intermediate MMF model inputs, (iv) application of geostatistic interpolation technique for spatial model inputs development, and (v) application of MMF model in GIS environment while estimating spatially distributed erosion outputs such as total overland transport capacity and soil detachment rate.
2.3. MMF Model Inputs Preparation
Input data for MMF model include rainfall (mm), land use, digital elevation model (DEM) for slope map derivation, soil texture, soil moisture content at field capacity (%w w−1), soil detachability index (g J−1), bulk density of soil (Mg m−3), cohesion of soil surface (KPa), soil moisture storage capacity (), effective hydrological top soil depth (EHD), and ratio of actual to potential evapotranspiration (/). Input data were collected from different sources such as field and laboratory determination, empirical relations, and the literature. Meteorological data such as rainfall and data were obtained from the meteorology station near the study area in 2009. Slope was derived from DEM developed from the topographic-map available at the Ethiopian Mapping Agency for Aksum area. The map was scanned, and contours and spot heights were digitized and tagged with elevation values in a GIS environment. The vector elevation map was converted to raster and projected using the Universal Transverse Mercator 37 North (UTM-37N) reference system.
Crop and soil parameters were collected from 117 plots scattered throughout the catchment considering major land use and cover types (bush land, protected area, cultivated, abandoned fields, grazing land, mixed-forest, and residential). Supervised classification and visual interpretation of the land satellite image of November 2009 was carried out for general land use and cover mapping. In addition to this, crop covers for the different crop types and their corresponding geographic coordinates were collected using field survey in September 2009. Data related to rainfall such as rainfall intensity, number of rainy days, and total rainfall were assumed to be similar in the study catchment. The reason for having only one weather station in the study catchment is that the Office of Meteorology Agency believed that rainfall variability is negligible within such a small area regardless of the differences in elevation. Rainfall intensity was assumed at 25 mm h−1 which is erosive for tropical climates such as Mai-Neguse catchment because no actual intensity data was found for the study catchment. Soil detachability index () (g J−1) was determined from the literature that corresponds to the soil texture observed in the study catchment.
2.4. Soil Sampling Zones and Sample Collection
In order to prepare MMF model soil related inputs, soil sampling that considered soil variability in the study catchment was executed. Sampling approaches that divided a field into small units (zone sampling) can capture variability and provide more information about soil-test levels compared with one composite sample collected from an entire large sampling area. To reduce the number of samples and sampling costs zone sampling is suggested to provide a way to group the spatial variability of soils while maintaining acceptable information about soil properties. Sampling by zone assumes that sampling areas are likely to remain temporally stable.
In this study, the zone sampling technique (divide a field into homogenous units that allow capturing variability and provide more information) was used to collect soil samples based on previous and existing knowledge of the soil and land use systems in the entire study catchment. The natural and management factors across the landscape that influenced soil properties spatial variability were considered while identifying the soil sampling zones. Three soil sampling zones that represented the soil quality (SQ) categories, long-term land use and soil management systems, and different erosion status sites in the catchment were identified using farmers’ opinions and researcher and extension experts’ judgment. The data that divided the catchment into the soil sampling zones was derived during the field reconnaissance surveys in June 2009. The SQ sampling zone was entirely used for arable land in the catchment whereas the other two sampling zones belonged to all the land use systems in the catchment. The sampling zones were further subdivided into different subsampling zones considering the variability within each zone and analytical costs.
The SQ sampling zone was divided into three subzones as high, medium, and low SQ based on farmers’ knowledge. They used indicators such as yield and yield component, soil depth, colour, and fertility conditions to divide into these subzones. The details on how local farmers’ classified soil into different SQ categories in the study catchment can be found in Tesfahunegn et al..
Eight representative long-term land use system sampling zones were identified based on farmers’ historical and present information acquired in the catchment. These are (i) natural forest; (ii) plantation of protected area; (iii) grazed land; (iv) teff (Eragrostis tef)-faba bean (Vicia faba) rotation; (v) teff-wheat (Triticum vulgare)/barley(Hordeum vulgare) rotation; (vi) teff monocropping; (vii) maize (Zea mays) monocropping; and (vii) uncultivated marginal land. The age of the systems varied from 5-6 years for teff monocropping and 20–30 years of maize monocropping system. Average age of the other systems was about 10 years except for the plantation, grazed land, and uncultivated marginal land systems with more than 15 years.
The erosion status-based sampling zone was divided into three subzones as stable, eroded, and deposition (aggrading) sites. Information from the local farmers, extension agents, and researcher’s (first author) observation on the level of topsoil depth (A-horizon), deposition, rills, pedestals, root and subsoil exposure, and gullies indicators were considered while identifying the three erosion-status sampling subzones. Those areas having A-horizon and minimum erosion indicators were considered as stable sites and the reverse of this as eroded sites. Depositional sites were also easily identified as they are mainly located in depression and flat areas with evidences of recent sediment deposition. In total, there were 14 subsampling zones across the erosion-status sites in the catchment for the soil samples collection. After doing all this identification and division, the soil sampling points in each subzone were located at the centre, considering soils in that point best represent the samples. Each sampling point was georeferenced as their distribution in the catchment is shown in Figure 2. The sampling distance was not regular, ranging from 40 to 180 m.

Figure 2: The distribution of soil sampling and vegetation cover points in the study catchment.
Soil samples were collected in June 2009. A total of 51 soil samples (3 subzones × 17 samples) were collected from the SQ based sampling zone. From the long-term land use systems, a total of 24 soil samples (8 subzones × 3 samples) were collected. It was also collected 42 soil/sediment samples (3 subzones × 12 samples in the catchment and 6 sampling points in the reservoir) from the erosion-status sites. The grand total of the composite samples collected across the sampling subzones was 117. Each composite soil sample was collected using 5–8 samples from each representative subsampling zone depending on the size and homogeneity of the sampling area (100–300 m2). All the composite soil samples were collected at the soil depth of 0–20 cm (the plough depth) since this is where most changes are expected to occur due to erosion, long-term land use, and soil management practices. The composite soil samples were pooled into a bucket and mixed thoroughly to homogenize it. Finally, a subsample of 500 g from the pooled composite samples was taken and soil samples were air dried and sieved to pass 2 mm mesh sieves before analysis for soil textures. On the other hand, two undisturbed soil samples were collected from each soil sampling point for bulk density and soil moisture determination. In addition, field level observation and measurement for parameters such as effective hydrological top soil depth (m), ground cover, and cover factor were carried out from the sampling points and georeferenced.
2.5. Soil Analysis
The soil samples collected in the soil sampling zones were determined for soil texture using the Bouyoucos hydrometer method, soil bulk density (BD) by the core method, and soil moisture content at field capacity (w w−1) by equilibrating the soil with water through capillary action in KR box.
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2.2. penelitian pendekatan
pendekatan penelitian dalam studi ini terdiri dari lima langkah utama. Ini adalah (i) identifikasi hydrophysical parameter yang input dari model MMF, (ii) survei lapangan dan diskusi-diskusi informal untuk mengidentifikasi zona sampling tanah perwakilan dalam tangkapan studi untuk sampling tanah dan analisis dan vegetasi penutup kondisi yang sesuai, (iii) aplikasi hubungan empiris yang dijelaskan oleh Morgan et al. menghitung menengah MMF model input, (iv) aplikasi interpolasi geostatistic teknik untuk pengembangan input model spasial, dan (v) aplikasi MMF model dalam lingkungan GIS sementara memperkirakan spasial didistribusikan erosi output seperti transportasi darat total kapasitas dan tanah detasemen harga.
2.3. MMF Model input persiapan
Input data untuk MMF model termasuk curah hujan (mm), penggunaan lahan, model elevasi digital (DEM) untuk lereng peta derivasi, tekstur tanah, kandungan kelembaban tanah di bidang kapasitas (%w w−1), tanah detachability indeks (g J−1), kepadatan massal tanah (Mg m−3), kohesi permukaan tanah (KPa), tanah kelembaban penyimpanan (kapasitas), kedalaman efektif hidrologis atas tanah (EHD), dan rasio sebenarnya untuk potensi evapotranspiration (/). Input data yang dikumpulkan dari sumber yang berbeda seperti lapangan dan penentuan laboratorium, hubungan empiris dan literatur. Meteorologi data seperti curah hujan dan data Diperoleh dari Stasiun Meteorologi di dekat daerah studi tahun 2009. Lereng berasal dari DEM dikembangkan dari topografi-peta tersedia di badan pemetaan Ethiopia Area Aksum. Peta dipindai, dan kontur dan tempat ketinggian digital dan tagged dengan nilai-nilai ketinggian di lingkungan GIS. Peta elevasi vektor dikonversi ke raster dan diproyeksikan dengan menggunakan sistem referensi Universal Transverse Mercator 37 North (UTM-37N).
Parameter tanaman dan tanah dikumpulkan dari 117 plot yang tersebar di seluruh dalam tangkapan mempertimbangkan tanah utama penggunaan dan penutup jenis (bush tanah, kawasan lindung, dibudidayakan, bidang ditinggalkan, merumput tanah, hutan dicampur, dan perumahan). Klasifikasi diawasi dan interpretasi visual citra satelit tanah November 2009 dilaksanakan untuk penggunaan umum lahan dan penutup pemetaan ini. Selain itu, mencakup panen untuk jenis tanaman yang berbeda dan Koordinat geografis mereka sesuai dikumpulkan menggunakan survei lapangan pada bulan September 2009. Data yang terkait dengan curah hujan seperti intensitas curah hujan, jumlah hari hujan, dan curah hujan yang diasumsikan sama di dalam tangkapan studi. Alasan untuk memiliki hanya satu stasiun cuaca di dalam tangkapan studi adalah bahwa kantor Badan Meteorologi percaya curah hujan variabilitas diabaikan dalam seperti area kecil tanpa melihat perbedaan ketinggian. Intensitas curah hujan yang diasumsikan di h−1 25 mm yang erosi untuk iklim tropis seperti tangkapan Mai-Neguse karena tidak ada data aktual intensitas ditemukan dalam studi tangkapan. Tanah detachability (indeks) (g J−1) ditentukan dari literatur yang berkaitan dengan tekstur tanah yang diamati dalam studi tangkapan
2.4. Zona Sampling tanah dan pengambilan sampel
Untuk mempersiapkan MMF model tanah terkait masukan, tanah sampling tanah dianggap variabilitas dalam tangkapan studi dihukum. Sampling pendekatan yang terbagi Lapangan unit kecil (zona sampling) dapat menangkap variabilitas dan menyediakan informasi mengenai tingkat uji tanah dibandingkan dengan satu komposit sampel dikumpulkan dari seluruh besar sampling luas. Untuk mengurangi jumlah sampel dan sampel biaya zona sampling disarankan untuk menyediakan cara untuk grup variabilitas spasial dari tanah sambil mempertahankan diterima informasi tentang sifat-sifat tanah. Sampling zona mengasumsikan bahwa sampling daerah mungkin untuk tetap temporal stabil.
dalam studi ini, teknik sampling zona (membagi bidang menjadi unit-unit homogen yang memungkinkan menangkap variabilitas dan memberikan informasi lebih lanjut) digunakan untuk mengumpulkan sampel tanah yang didasarkan pada pengetahuan sebelumnya dan yang ada dari tanah dan tanah menggunakan sistem di dalam tangkapan seluruh studi. Faktor-faktor alam dan manajemen di lanskap yang mempengaruhi tanah properti spasial variabilitas dianggap sementara mengidentifikasi zona sampling tanah. Tiga zona sampling tanah yang mewakili tanah kualitas (SQ) kategori, jangka panjang pemanfaatan lahan dan tanah sistem manajemen, dan erosi berbeda status situs di dalam tangkapan telah diidentifikasi menggunakan pendapat petani dan peneliti dan ekstensi ahli penghakiman. Data yang dibagi dalam tangkapan ke zona sampling tanah berasal selama survei Lapangan pengintaian pada bulan Juni 2009. SQ sampling zona sepenuhnya digunakan untuk lahan yang subur di dalam tangkapan sedangkan Zona sampling dua lainnya milik semua sistem pemanfaatan lahan di dalam tangkapan. Zona sampling lebih lanjut dibagi menjadi zona subsampling yang berbeda, mengingat variabilitas dalam setiap zona dan analisis biaya.
The SQ sampling zona dibagi menjadi tiga subzones sebagai tinggi, menengah, dan rendah SQ berdasarkan pengetahuan petani. Mereka menggunakan indikator seperti hasil dan komponen hasil, kedalaman tanah, warna, dan kondisi kesuburan untuk membagi menjadi subzones ini. Rincian pada petani bagaimana lokal tanah diklasifikasikan ke SQ berbeda kategori di dalam tangkapan studi dapat ditemukan di Tesfahunegn et al...
Delapan zona tanah penggunaan sistem sampling jangka panjang perwakilan diidentifikasi berdasarkan petani sejarah dan hadir informasi yang diperoleh di dalam tangkapan. Ini adalah (i) hutan alam; (ii) perkebunan kawasan lindung; (iii) menyerempet tanah; (iv) teff (Eragrostis tef)-faba kacang (Vicia faba) rotasi; (v) teff-gandum (Triticum vulgare) / rotasi jelai (Hordeum vulgare); (vi) teff monocropping; (vii) monocropping jagung (Zea mays); dan (vii) tanah diolah marjinal. Usia sistem bervariasi dari 5-6 tahun untuk teff monocropping dan 20-30 tahun jagung monocropping sistem. Usia rata-rata sistem yang lain adalah sekitar 10 tahun kecuali perkebunan, menyerempet tanah, dan tanah diolah marjinal sistem dengan lebih dari 15 tahun.
Erosi sampling berbasis status zona dibagi menjadi tiga subzones sebagai stabil, mengikis, dan pengendapan (aggrading) situs. Informasi dari petani lokal, perluasan agen, dan peneliti (pertama penulis) pengamatan pada tingkat sebagai humus kedalaman (A-horizon), rills, umpak pengendapan, akar dan lapisan tanah sebelah bawah eksposur, dan indikator selokan dianggap sementara mengidentifikasi subzones sampling erosi-status tiga. Bidang-bidang yang memiliki A-horizon dan erosi minimal indikator dianggap sebagai situs stabil dan kebalikan dari ini sebagai situs yang terkikis. Situs pengendapan juga mudah dikenali sebagai mereka terutama terletak di depresi dan bidang datar dengan hari sedimen pengendapan. Secara total, Ada 14 zona subsampling di situs erosi-status di dalam tangkapan untuk koleksi sampel tanah. Setelah melakukan semua ini identifikasi dan divisi, sampling tanah poin di setiap subzone berada di pusat, mengingat tanah yang terbaik titik mewakili sampel. Setiap titik sampling adalah rujukan geografis seperti distribusi mereka di dalam tangkapan yang ditunjukkan pada gambar 2. Sampling jarak itu tidak biasa, mulai dari 40 hingga 180 m.

gambar 2: distribusi tanah sampling dan vegetasi poin cover dalam studi tangkapan
sampel tanah dikumpulkan pada bulan Juni 2009. Total 51 tanah (3 subzones × 17 sampel) sampel dikumpulkan dari SQ berdasarkan zona sampling. Dari tanah jangka panjang menggunakan sistem, total 24 sampel tanah (8 subzones × 3 sampel) dikumpulkan. Itu juga dikumpulkan 42 tanah/sampel sedimen (3 subzones × 12 sampel di dalam tangkapan) dan 6 poin sampling di reservoir dari erosi-status situs. Grand total komposit sampel dikumpulkan di seluruh sampling subzones adalah 117. Setiap sampel tanah komposit dikumpulkan menggunakan sampel 5 – 8 dari setiap zona subsampling perwakilan tergantung ukuran dan keseragaman sampling luas (100-300 m2). Semua sampel tanah komposit dikumpulkan di kedalaman tanah 0 – 20 cm (plough kedalaman) karena ini adalah tempat sebagian besar perubahan yang diharapkan terjadi karena erosi, jangka panjang penggunaan lahan dan praktik-praktik pengelolaan tanah. Sampel tanah komposit menggenang dalam ember dan dicampur secara menyeluruh untuk menyeragamkan itu. Akhirnya, subsample 500 g dari terkumpul komposit sampel diambil dan sampel tanah itu udara kering dan disaring untuk lulus 2 mm saringan mesh sebelum analisis untuk tekstur tanah. Dilain pihak dua sampel tanah tidak terganggu yang dikumpulkan dari masing-masing tanah sampling titik untuk penentuan kelembaban kepadatan dan tanah massal. Selain itu, tingkat lapangan pengamatan dan pengukuran parameter seperti efektif hidrologis atas tanah kedalaman (meter), penutup tanah, dan penutup faktor dilakukan dari sampling poin dan rujukan geografis.
2.5. Tanah analisis
Sampel tanah yang dikumpulkan dalam sampling tanah zona bertekad untuk tekstur tanah yang menggunakan Bouyoucos metode hydrometer, tanah kepadatan massal (BD) dengan metode inti, dan tanah kadar air pada bidang kapasitas (w w−1) oleh equilibrating tanah dengan air melalui kapiler tindakan dalam kotak KR.
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Hasil (Bahasa Indonesia) 2:[Salinan]
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2.2. Research Approach
The research approach in this study consisted of five main steps. These are (i) identification of hydrophysical parameters which are inputs of MMF model, (ii) field surveys and informal discussions in order to identify representative soil sampling zones within the study catchment for soil sampling and analysis and also the corresponding vegetation cover conditions, (iii) application of empirical relations which are described by Morgan et al. to calculate intermediate MMF model inputs, (iv) application of geostatistic interpolation technique for spatial model inputs development, and (v) application of MMF model in GIS environment while estimating spatially distributed erosion outputs such as total overland transport capacity and soil detachment rate.
2.3. MMF Model Inputs Preparation
Input data for MMF model include rainfall (mm), land use, digital elevation model (DEM) for slope map derivation, soil texture, soil moisture content at field capacity (%w w−1), soil detachability index (g J−1), bulk density of soil (Mg m−3), cohesion of soil surface (KPa), soil moisture storage capacity (), effective hydrological top soil depth (EHD), and ratio of actual to potential evapotranspiration (/). Input data were collected from different sources such as field and laboratory determination, empirical relations, and the literature. Meteorological data such as rainfall and data were obtained from the meteorology station near the study area in 2009. Slope was derived from DEM developed from the topographic-map available at the Ethiopian Mapping Agency for Aksum area. The map was scanned, and contours and spot heights were digitized and tagged with elevation values in a GIS environment. The vector elevation map was converted to raster and projected using the Universal Transverse Mercator 37 North (UTM-37N) reference system.
Crop and soil parameters were collected from 117 plots scattered throughout the catchment considering major land use and cover types (bush land, protected area, cultivated, abandoned fields, grazing land, mixed-forest, and residential). Supervised classification and visual interpretation of the land satellite image of November 2009 was carried out for general land use and cover mapping. In addition to this, crop covers for the different crop types and their corresponding geographic coordinates were collected using field survey in September 2009. Data related to rainfall such as rainfall intensity, number of rainy days, and total rainfall were assumed to be similar in the study catchment. The reason for having only one weather station in the study catchment is that the Office of Meteorology Agency believed that rainfall variability is negligible within such a small area regardless of the differences in elevation. Rainfall intensity was assumed at 25 mm h−1 which is erosive for tropical climates such as Mai-Neguse catchment because no actual intensity data was found for the study catchment. Soil detachability index () (g J−1) was determined from the literature that corresponds to the soil texture observed in the study catchment.
2.4. Soil Sampling Zones and Sample Collection
In order to prepare MMF model soil related inputs, soil sampling that considered soil variability in the study catchment was executed. Sampling approaches that divided a field into small units (zone sampling) can capture variability and provide more information about soil-test levels compared with one composite sample collected from an entire large sampling area. To reduce the number of samples and sampling costs zone sampling is suggested to provide a way to group the spatial variability of soils while maintaining acceptable information about soil properties. Sampling by zone assumes that sampling areas are likely to remain temporally stable.
In this study, the zone sampling technique (divide a field into homogenous units that allow capturing variability and provide more information) was used to collect soil samples based on previous and existing knowledge of the soil and land use systems in the entire study catchment. The natural and management factors across the landscape that influenced soil properties spatial variability were considered while identifying the soil sampling zones. Three soil sampling zones that represented the soil quality (SQ) categories, long-term land use and soil management systems, and different erosion status sites in the catchment were identified using farmers’ opinions and researcher and extension experts’ judgment. The data that divided the catchment into the soil sampling zones was derived during the field reconnaissance surveys in June 2009. The SQ sampling zone was entirely used for arable land in the catchment whereas the other two sampling zones belonged to all the land use systems in the catchment. The sampling zones were further subdivided into different subsampling zones considering the variability within each zone and analytical costs.
The SQ sampling zone was divided into three subzones as high, medium, and low SQ based on farmers’ knowledge. They used indicators such as yield and yield component, soil depth, colour, and fertility conditions to divide into these subzones. The details on how local farmers’ classified soil into different SQ categories in the study catchment can be found in Tesfahunegn et al..
Eight representative long-term land use system sampling zones were identified based on farmers’ historical and present information acquired in the catchment. These are (i) natural forest; (ii) plantation of protected area; (iii) grazed land; (iv) teff (Eragrostis tef)-faba bean (Vicia faba) rotation; (v) teff-wheat (Triticum vulgare)/barley(Hordeum vulgare) rotation; (vi) teff monocropping; (vii) maize (Zea mays) monocropping; and (vii) uncultivated marginal land. The age of the systems varied from 5-6 years for teff monocropping and 20–30 years of maize monocropping system. Average age of the other systems was about 10 years except for the plantation, grazed land, and uncultivated marginal land systems with more than 15 years.
The erosion status-based sampling zone was divided into three subzones as stable, eroded, and deposition (aggrading) sites. Information from the local farmers, extension agents, and researcher’s (first author) observation on the level of topsoil depth (A-horizon), deposition, rills, pedestals, root and subsoil exposure, and gullies indicators were considered while identifying the three erosion-status sampling subzones. Those areas having A-horizon and minimum erosion indicators were considered as stable sites and the reverse of this as eroded sites. Depositional sites were also easily identified as they are mainly located in depression and flat areas with evidences of recent sediment deposition. In total, there were 14 subsampling zones across the erosion-status sites in the catchment for the soil samples collection. After doing all this identification and division, the soil sampling points in each subzone were located at the centre, considering soils in that point best represent the samples. Each sampling point was georeferenced as their distribution in the catchment is shown in Figure 2. The sampling distance was not regular, ranging from 40 to 180 m.

Figure 2: The distribution of soil sampling and vegetation cover points in the study catchment.
Soil samples were collected in June 2009. A total of 51 soil samples (3 subzones × 17 samples) were collected from the SQ based sampling zone. From the long-term land use systems, a total of 24 soil samples (8 subzones × 3 samples) were collected. It was also collected 42 soil/sediment samples (3 subzones × 12 samples in the catchment and 6 sampling points in the reservoir) from the erosion-status sites. The grand total of the composite samples collected across the sampling subzones was 117. Each composite soil sample was collected using 5–8 samples from each representative subsampling zone depending on the size and homogeneity of the sampling area (100–300 m2). All the composite soil samples were collected at the soil depth of 0–20 cm (the plough depth) since this is where most changes are expected to occur due to erosion, long-term land use, and soil management practices. The composite soil samples were pooled into a bucket and mixed thoroughly to homogenize it. Finally, a subsample of 500 g from the pooled composite samples was taken and soil samples were air dried and sieved to pass 2 mm mesh sieves before analysis for soil textures. On the other hand, two undisturbed soil samples were collected from each soil sampling point for bulk density and soil moisture determination. In addition, field level observation and measurement for parameters such as effective hydrological top soil depth (m), ground cover, and cover factor were carried out from the sampling points and georeferenced.
2.5. Soil Analysis
The soil samples collected in the soil sampling zones were determined for soil texture using the Bouyoucos hydrometer method, soil bulk density (BD) by the core method, and soil moisture content at field capacity (w w−1) by equilibrating the soil with water through capillary action in KR box.
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