농촌진흥청 국립농업과학원 토양환경 작물별 비료사용 처방 데이터
공공데이터포털
전국의 토양시료를 채취 하고 분석 결과를 바탕으로 각 필지별로 작물재배에 필요한 적정 비료량 데이터 제공* 토양분석 (화학적 특성파악) : pH, 유기물, 질소, 인산, 칼륨, 마그네슘, 전기전도도, 규산 등
Data and code from: A high throughput approach for measuring soil slaking index
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,This dataset includes soil wet aggregate stability measurements from the Upper Mississippi River Basin LTAR site in Ames, Iowa. Samples were collected in 2021 from this long-term tillage and cover crop trial in a corn-based agroecosystem.,We measured wet aggregate stability using digital photography to quantify disintegration (slaking) of submerged aggregates over time, similar to the technique described by Fajardo et al. (2016) and Rieke et al. (2021). However, we adapted the technique to larger sample numbers by using a multi-well tray to submerge 20-36 aggregates simultaneously. We used this approach to measure slaking index of 160 soil samples (2120 aggregates).,This dataset includes slaking index calculated for each aggregates, and also summarized by samples. There were usually 10-12 aggregates measured per sample.,We focused primarily on methodological issues, assessing the statistical power of slaking index, needed replication, sensitivity to cultural practices, and sensitivity to sample collection date. We found that small numbers of highly unstable aggregates lead to skewed distributions for slaking index. We concluded at least 20 aggregates per sample were preferred to provide confidence in measurement precision. However, the experiment had high statistical power with only 10-12 replicates per sample. Slaking index was not sensitive to the initial size of dry aggregates (3 to 10 mm diameter); therefore, pre-sieving soils was not necessary. The field trial showed greater aggregate stability under no-till than chisel plow practice, and changing stability over a growing season. These results will be useful to researchers and agricultural practitioners who want a simple, fast, low-cost method for measuring wet aggregate stability on many samples.,
농촌진흥청 국립농업과학원 농경지화학성 통계정보 V2
공공데이터포털
흙토람 농경지 화학성 데이터는 전국 농경지에서 채취한 토양 시료를 분석하여 산도(pH), 유기물 함량, 유효인산, 치환성 양이온(칼륨, 칼슘, 마그네슘), 양이온치환용량(CEC), 염류농도(EC) 등의 주요 화학적 특성을 제공합니다. 이 데이터는 토양의 비옥도와 양분 상태를 과학적으로 진단하고, 작물별 적정 시비처방 및 토양 환경 개선을 위한 기초자료로 활용됩니다. 또한 지속가능한 농업 실현과 더불어, 토양 산성화·염류집적 등 환경 문제에 대한 대응, 농업 정책 수립, 연구 및 교육 자료로도 폭넓게 사용됩니다.
Data for Grassland-to-cropland conversion increased soil, nutrient, and carbon losses in the US Midwest between 2008 and 2016
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These are the soil quality data for each county (listed by fips code) for each scenario. This dataset is associated with the following publication: Zhang, X., T. Lark, C. Clark, Y. Yuan, and S. LeDuc. Grassland-to-cropland conversion increased soil, nutrient, and carbon losses in the US Midwest between 2008 and 2016. Environmental Research Letters. IOP Publishing LIMITED, Bristol, UK, 16: 1-14, (2021).
Soil Water Content Data for The Bushland, Texas Large Weighing Lysimeter Experiments
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,This dataset contains soil water content data developed from neutron probe readings taken in access tubes in each of the four large, precision weighing lysimeters and in the fields surrounding each lysimeter at the USDA-ARS Conservation and Production Laboratory (CPRL), Soil and Water Management Research Unit (SWMRU), Bushland, Texas (Lat. 35.186714°, Long. -102.094189°, elevation 1170 m above MSL) beginning in 1989. Readings were taken periodically with a field-calibrated neutron probe at depths from 10 cm to 230 cm (maximum of 190 cm depth in the lysimeters) in 20-cm depth increments. Periods between readings were typically one to two weeks, sometimes longer according to experimental design and need for data. Field calibrations in the Pullman soil series were done every few years. Calibrations typically produced a regression equation with RMSE <= 0.01 m3 m-3. Data were used to guide irrigation scheduling to achieve full or deficit irrigation as required by the experimental design. Data may be used to calculate the soil profile water content in mm of water from the surface to the maximum depth of reading. Profile water content differences between reading times in the same access tube are considered the change in soil water storage during the period in question and may be used to compute evapotranspiration (ET) using the soil water balance equation: ET = (change in storage + P + I + F + R, where P is precipitation during the period, I is irrigation during the period, F is soil water flux (drainage) out of the bottom of the soil profile during the period, and R is the sum of runon and runoff during the period. Typically, R is taken as zero because the fields were furrow diked to prevent runon and runoff during most of each growing season.,See the README for descriptions of each data file.,