抗旱性复混肥对土壤物理性状、持水量和马铃薯经济效益的影响

采用田间试验方法,研究抗旱性复混肥配方及其对土壤物理性质、持水量和马铃薯经济效益的影响,以期筛选出抗旱性复合肥最佳配方和施用量。结果表明:影响马铃薯产量的因素由大到小依次为:马铃薯专用肥废弃物组合肥保水剂,抗旱性复合肥最佳配方组合为废弃物组合肥3 000 kg/hm~2、保水剂37.50kg/hm~2、马铃薯专用肥2 230 kg/hm~2。随着抗旱性复混肥施用量的增加,土壤总孔隙度、持水量、马铃薯块茎质量和产量在增加,土壤容重在降低。经回归统计分析,抗旱性复混肥与马铃薯产量间的回归方程为:y=28.87+1.771 3x-0.035 4x2,最佳施肥量为5.28 t/hm~2,计算结果与田间施用抗旱性复混肥5.28 t/hm~2相吻合。     

薰衣草叶螨药剂防治筛选试验

为害新疆伊犁薰衣草的主要是土耳其斯坦叶螨(Tetranychus turkestani),通过(240克/升)螺螨酯(4000倍液)、3.2%阿维菌素乳油(3000倍液)、16%四螨.哒螨灵可湿性粉剂(1600倍液)、73%炔螨特乳油(2500倍液)、0.6％苦参碱水剂(1000倍液)5种药剂防治试验,药后1天、3天,3.2%阿维菌素防效最高,达到80.02%和90.30%；药后7天,螺螨酯防效最高,为91.85%；药后15天,螺螨酯防效较好,为95.23%。螺螨酯、阿维菌素、四螨.哒螨灵、炔螨特在0.05显著水平和0.01极显著水平均无显著差异,且最高防治效果均大于85%,建议交替使用。     

黔育1号菊苣与紫花苜蓿、鸭茅间作栽培效果研究

依据贵州省松桃县的气候特点和牧草种植需要,用黔育1号菊苣与北林202紫花苜蓿、黔草4号鸭茅分别进行间作试验,从产量、营养品质、生产效益等方面对间作复合群体与3种牧草单播进行比较分析,探讨黔育1号菊苣与不同牧草间作种植模式的增产效益。结果表明,在贵州松桃地区,黔育1号菊苣+北林202紫花苜蓿间作,年均鲜草产量可达87.27 t/hm²,比紫花苜蓿单播产量增加36.17%,生产效益提高20.77%,粗蛋白含量达26.83%。该研究结果可为松桃县种草养畜产业的发展提供技术支撑。     

The application of proximal visible and near-infrared spectroscopy to estimate soil organic matter on the Triffa Plain of Morocco

Soil organic matter (SOM) is a fundamental soil constituent. The estimation of this parameter in the laboratory using the classical method is complex time-consuming and requires the use of chemical reagents. The objectives of this study were to assess the accuracy of two laboratory measurement setups of the VIS-NIR spectroscopy in estimating SOM content and determine the important spectral bands in the SOM estimation model. A total of 115 soil samples were collected from the non-root zone (0–20 cm) of soil in the study area of the Triffa Plain and then analysed for SOM in the laboratory by the Walkley–Black method. The reflectance spectra of soil samples were measured by two protocols, Contact Probe (CP) and Pistol Grip (PG)) of the ASD spectroradiometer (350–2500 nm) in the laboratory. Partial least squares regression (PLSR) was used to develop the prediction models. The results of coefficient of determination (R²) and the root mean square error (RMSE) showed that the pistol grip offers reasonable accuracy with an R² = 0.93 and RMSE = 0.13 compared to the contact probe protocol with an R² = 0.85 and RMSE = 0.19. The near-Infrared range were more accurate than those in the visible range for predicting SOM using the both setups (CP and PG). The significant wavelengths contributing to the prediction of SOM for (PG) setup were at: 424, 597, 1432, 1484, 1830,1920, 2200, 2357 and 2430 nm, while were at 433, 587, 1380, 1431, 1929, 2200 and 2345 nm for (CP) setup.     

Inhibiting soil loss and runoff from small plots induced by an individual freeze-thaw cycle using three rangeland species

This study investigated the role of three rangeland species viz. Agropyron trichophorum, Medicago sativa, and Lolium prenne on mitigating of effects of a freeze-thaw (FT) cycle on runoff generation and soil loss from small experimental plots. Small plots (0.5 × 0.5m) were prepared in three replicates for control (i.e., under a FT cycle only) and treatments (i.e., individually planted with the study species and subject to a FT cycle). The treated plots were then placed at a slope of 20% and subjected to simulated rainfall with intensity of 70 mm h⁻¹ and 30 min duration. The results of the study showed a significant effect (P < 0.05) of the plants on controlling runoff and soil loss after a FT cycle. Also, the detrimental effects of the FT cycle due to performance of ice lenses and formation of an active melting layer in the soil surface were ameliorated by the presence of litter on the soil and root-binding effect of the plants. Time to runoff increased by 54, 111 and 10%, runoff volume decreased by 27, 68 and 0.4% and soil loss changed by −34, −62, and +6.5% in the plots planted with A. trichophorum, L. prenne and M. sativa, respectively. The results of the current study indicated that L. prenne had the maximum benefit on reducing runoff and soil loss from the plots undergoing a FT cycle.     

Effect of time resolution of rainfall measurements on the erosivity factor in the USLE in China

Rainfall erosivity, one of the factors in the Universal Soil Loss Equation, quantifies the effect of rainfall and runoff on soil erosion. High-resolution data are required to compute rainfall erosivity, but are not widely available in many parts of the world. As the temporal resolution of rainfall measurement decreases, computed rainfall erosivity decreases. The objective of the paper is to derive a series of conversion factors as a function of the time interval to compute rainfall erosivity so that the R factor computed using data at different time intervals could be converted to that computed using 1-min data. Rainfall data at 1-min intervals from 62 stations over China were collected to first compute the ‘true’ R factor values. Underestimation of the R factor was systematically evaluated using data aggregated at 5, 6, 10, 15, 20, 30, and 60-min to develop conversion factors for the R factor and the 1-in-10-year storm EI₃₀ values. Compared with true values, the relative error in R factor using data at fixed intervals of ≤10min was <10% for at least 44 out of 62 stations. Errors increased rapidly when the time interval of the rainfall data exceeded 15 min. Relative errors were >10% using 15-min data for 66.1% of stations and >20% using 30-min data for 61.3% of stations. The conversion factors for the R factor, ranging from 1.051 to 1.871 for 5 to 60-min data, are higher than those for the 1-in-10-years storm EI₃₀, ranging from 1.034 to 1.489 for the 62 stations.     

Study on a soil erosion sampling survey in the Pan-Third Pole region based on higher-resolution images

Soil erosion is one of the most severe global environmental problems, and soil erosion surveys are the scientific basis for planning soil conservation and ecological development. To improve soil erosion sampling survey methods and accurately and rapidly estimate the actual rates of soil erosion, a Pan-Third Pole region was taken as an example to study a methodology of soil erosion sampling survey based on high-spatial-resolution remote sensing images. The sampling units were designed using a stratified variable probability systematic sampling method. The spatiotemporal characteristics of soil erosion and conservation were taken into account, and finer-resolution freely available and accessible images in Google Earth were used. Through the visual interpretation of the free high-resolution remote sensing images, detailed information on land use and soil conservation measures was obtained. Then, combined with the regional soil erosion factor data products, such as rainfall-runoff erosivity factor (R), soil erodibility factor (K), and slope length and steepness factor (LS), the soil loss rates of some sampling units were calculated. The results show that, based on these high-resolution remote sensing images, the land use and soil conservation measures of the sampling units can be quickly and accurately extracted. The interpretation accuracy in 4 typical cross sections was more than 80%, and sampling accuracy, described by histogram similarity in 11 large sampling sites, show that the landuse of sampling uints can represent the structural characteristics of regional land use. Based on the interpretation of data from the sample survey and the regional soil erosion factor data products, the calculation of the soil erosion rate can be completed quickly. The calculation results can reflect the actual conditions of soil erosion better than the potential soil erosion rates calculated by using the coarse-resolution remote sensing method.     

Assessing spatial variability and erosion susceptibility of soils in hilly agricultural areas in Southern Italy

Soil erosion is one of the main environmental problems in the Mediterranean area. This problem is becoming even more important especially in Italy, in the Apennines, where severe erosive processes occur due to the action of concentrated running water. The erodibility (K-Factor) of a soil, estimated using the Revised Universal Soil Loss Equation (RUSLE), is a measure of its susceptibility to erosion and depends on several soil properties such as organic matter, texture and permeability and structure.To assess the spatial variability of soil properties and soil erodibility in hilly agricultural areas and to investigate the relationships between soil features and landscape morphodynamics, a detailed study in Molise region (southern Italy), in a small drainange basin located along its hilly Adriatic flank, was carried out. In this catchment, 63 topsoil samples (A horizons) were collected and 10 soil profiles, forming a catena crossing 3 land units, were sampled. The calculated K-Factors ranges between 0.012 and 0.048 t ha h ha⁻¹ MJ⁻¹ mm⁻¹ indicating a complex spatial distribution, due to the several local pedological and geomorphological factors affecting soil erodibility. The results give clear evidence about the relationships among soil characteristics, soil erodibility and landscape morpho-dynamics (land units).Comparing the soil loss rates estimated for the study area with those reported in literature, a good correspondence can be observed only for the more stable land unit, not characterized by intense erosive processes. The proposed methodology is suitable to highlight areas characterized by similar morphodynamics features, and comparable soil erodibility, for a more effective spatialization of K factor.     

The use of remote sensing to detect the consequences of erosion in gypsiferous soils

Tillage practices on sloping ground often result in unsustainable soil losses impairing soil functions such as crop productivity, water and nutrients storage, and soil organic carbon (SOC) sequestration. A sloping olive grove (10%) was planted in shallow gypsiferous soils in 2004. It was managed by minimum tillage; the most frequent management practice in central Spain. The consequences of erosion were studied in soil samples (at 0–10, 10–20, and 20–30 cm depths) by analyzing SOC, available water and gypsum content, and by detecting spectral signatures using an ASD FieldSpecPro® VIS/NIR-spectroradiometer. The Brightness index (BI), Shape index (FI), and Normalized Difference Vegetation Index (NDVI) were derived from the ASD spectral signatures and from remote sensing (Sentinel-2 image) data. The development of these young olive trees was estimated from the measured diameter of the trunks (17 ± 18 cm diameter). In 20–30 cm of the soil, the carbon stock (38 ± 18 Mg ha⁻¹) as well as the available water content (12 ± 6%) was scarce, affecting the productivity of the olive grove. The above-mentioned indices obtained from the laboratory samples and the pixels of the Sentinel-2 image were significantly (p < 0.01) correlated, with a correlation coefficient of around 0.4. The BI was related to the gypsum content and the slope of the plot. The FI was related to the carbon and water contents. The NDVI derived from the satellite image identified the influence of soil degradation on the trees and the carbon content. The spatial-temporal changes of the indices might help in tracking soil changes over time.     

温室茄子氮、磷、钾素最大利润施用量研究

为了研究温室茄子氮、磷、钾素最大利润施用量,为茄子合理施肥和安全生产提供参考,在甘肃省张掖市甘州区党寨镇温室内,采用田间小区试验方法,进行了温室茄子氮、磷、钾素最大利润施用量研究。结果表明:随着氮、磷、钾素施用量梯度的增大,茄子产量逐渐增加,边际产量、边际产值和边际利润均呈递减趋势,其中边际利润最终出现负值。根据最大利润施用量计算公式求得茄子氮、磷、钾素最大利润施用量分别为0.62、0.41、0.29 t/hm~2,进而得出最大利润施用量的理论产量分别为95.58、96.04、95.35 t/hm~2。