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 ผลงานตีพิมพ์ในวารสารวิชาการThe impacts of tillage, soil conditioners, and chemical fertilizer on yield of cassava in Yasothon Soil Series (Typic Paleustult), relationship between nutrient concentration and cassava yield components, and soil propertyผู้แต่ง: พิลาสลักษณ์ ลุ่นลิ่ว,  Dr.Somchai Anusontpornperm, Associate Professor , Dr.Suphicha Thanachit, Associate Professor , Mr.Irb Kheoruenromne, Emeritus Professor , วารสาร: |
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ผลงานตีพิมพ์ในวารสารวิชาการEffect of bentonite and cassava tails and stalk on cassava planted in an upland Grossarenic Grossarenic Paleustult and soil property changesผู้แต่ง:Ketkhao, P., Dr.Somchai Anusontpornperm, Associate Professor, Dr.Suphicha Thanachit, Associate Professor, Mr.Irb Kheoruenromne, Emeritus Professor, Dr.Mutchima Phun-Iam, Lecturer , วารสาร: 
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 หัวเรื่อง:ไม่มีชื่อไทย (ชื่ออังกฤษ : Relationship between Soil Property and the Aggregation of Tropical Forest Soils in Thailand) ผู้เขียน:Wanrapee Suwanprapa, ดร.สมชัย อนุสนธิ์พรเพิ่ม, รองศาสตราจารย์, ดร.ศุภิฌา ธนะจิตต์, รองศาสตราจารย์, นายเอิบ เขียวรื่นรมณ์, ศาสตราจารย์เกียรติคุณ สื่อสิ่งพิมพ์:pdf AbstractThe aggregate size distribution and its relationships with other soil properties were determined in eight soils under different tropical forest types: secondary mixed deciduous forest, dry dipterocarp forest, dry evergreen forest and an ecotone zone. The aggregate stability of individual aggregate size fractions WSA1 to WSA6 were determined by a wet-sieving method as: 2 mm ? WSA1 <8 mm; 1 mm ? WSA2 < 2 mm; 0.5 mm ? WSA3 < 1 mm; 0.25 mm ? WSA4 < 0.5 mm ; 0.1 mm ? WSA5 < 0.25 mm; and WSA6 < 0.10 mm.. They were moderately shallow to very deep and slightly to strongly acidic. The soil texture was sandy loam to clay with low to high levels of organic matter content (2.0–18.7 g.kg-1), available phosphorus (0.13–0.17 mg.kg-1), available potassium (11–174 mg.kg-1), and cation exchange capacity (4.5–38.5 cmolc.kg-1). There were no differences in the aggregate size distribution among the soils with nearly half of the net aggregates being dominated by macroaggregate size WSA1, especially in the topsoil layers. Organic carbon, available P, bulk density, sand+silt and the clay fractions, and extractable Mg, Fe and Mn played important roles in the water stability of aggregation of these soils in different sizes. Organic carbon was the main source contributing to the formation of macroaggregates (r = 0.77in the topsoils, which consequently reduced the bulk density of these soils (r= -0.58 ). Various amorphous forms of Fe, especially in the amorphous form, were clearly involved in the formation of microaggregates (below 2.5 mm) in subsurface soils. |
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ผลงานตีพิมพ์ในวารสารวิชาการผลของปุ๋ยไนโตรเจนละลายช้าที่มีต่อสมบัติบางประการของดิน และการเจริญเติบโตของกล้ามะเขือเทศ (2013)ผู้แต่ง:Dr.Thongchai Mala, Associate Professor , Mr.Audthasit Wongmaneeroj, Assistant Professor , Mr.Suphachai Amkha, Assistant Professor , Dr.Sirinapa Chungopast, Assistant Professor , ดุสิต จิตตนูนท์, ไชยา บุญเลิศ, วารสาร: |
ที่มา:วารสารแก่นเกษตร(อยู่ระหว่างการตีพิมพ์)หัวเรื่อง:ผลของปุ๋ยไนโตรเจนละลายช้าที่มีต่อสมบัติบางประการของดินและการเจริญเติบโตของกล้ามะเขือเทศ |
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หัวเรื่อง:ไม่มีชื่อไทย (ชื่ออังกฤษ : Spatial Modeling for Soil Properties Prediction in Mountainous Areas Using Partial Least Squares Regression) ผู้เขียน:สุวิทย์ อ๋องสมหวัง, Rawee Rattanakom สื่อสิ่งพิมพ์:pdf AbstractSoil properties are one of the most important categories of information for land management and environmental modeling. Unfortunately, soil properties in mountainous areas with slopes of more than 35% are rarely investigated in Thailand due to the complexity of their landscapes and the cost and time requirements. The main objective was to predict soil properties in mountainous areas relating to soil forming factors using partial least squares regression (PLSR). The combination of topographic position index values from two different scales and criteria sets was firstly used to classify landform for in situ soil survey. Then, analyzed soil properties of the topsoil and subsoil (sand, silt, clay, pH, organic matter, total N, available P, exchangeable K, cation exchange capacity (CEC) and base saturation) and soil forming factors (rainfall, normalized difference vegetation index, elevation, slope, aspect, plan curvature, profile curvature, curvature, topographic wetness index and Al/Si ratio) were used to construct soil-landscape models using PLSR. It was found that the best predictive model for topsoil prediction was sand (R2 = 0.92) and the worst was silt (R2 = 0.52) while the best predictive model for subsoil property prediction was CEC (R2 = 0.85) and the worst was total N and available P (R2 = 0.59). Accuracy assessment for the topsoil and subsoil properties prediction models using normalized root mean square error varied between 0.18 to 0.25 and 0.18 to 0.36, respectively. In addition, the selected predictive soil properties were used for soil texture classification and soil fertility assessment. In conclusion, it is suggested that soil-landscape modeling using PLSR can be efficiently used as a tool for spatial soil property prediction in mountainous areas where soil characteristics and properties are not available. |