Effect of Ploughing Depth on the Growth and Yield of Heracleum candicans： a Threatened Medicinal Herb and a Less-explored Potential Crop of the Himalayan Region

This paper examines the effect of ploughing depths （A -- 60 cm, B -- 45 cm and C -- 30 cm） on the growth and yield of Heracleum candicans Wall （Apiaceae）, a threatened medicinal herb of the Himalayan region. This less-explored plant is being suggested as a potential crop for the mountain agriculture. The study was carried out in an orchard in Himachal Pradesh, India at 2500 m altitude, for two successive growth years. During the first year, all plants remained in juvenile state; in the second year, nearly 65 % plants produced flowers only under 60cm ploughing depth. Among its morphological traits, plant height, collar diameter and aboveground flesh weight were found to be strongly correlated （P 〈 0.01） with the belowground biomass during the first year （r =0.968, 0.925 and 0.973, respectively） and during the second year （r=0.945, 0.928 and 0.775, respectively）. Increase in the ploughing depth was significantly correlated （P〈0.01） with all growth parameters, including the belowground dry weight, marketable portion of the produce. The belowground biomass （commercial yield; 16.28 Qt/hec） at depth A was about 2.6 and 4.7 times higher than those recorded at depths B and C, respectively. The results clearly justify the importance of deep ploughing and this paper strongly recommends it for economically sustainable cropping.     

The use of MODIS data to derive acreage estimations for larger fields: A case study in the south-western Rostov region of Russia

Recent developments in remote sensing technology, in particular improved spatial and temporal resolution, open new possibilities for estimating crop acreage over larger areas. Remotely sensed data allow in some cases the estimation of crop acreage statistics independently of sub-national survey statistics, which are sometimes biased and incomplete. This work focuses on the use of MODIS data acquired in 2001/2002 over the Rostov Oblast in Russia, by the Azov Sea. The region is characterised by large agricultural fields of around 75 ha on average. This paper presents a methodology to estimate crop acreage using the MODIS 16-day composite NDVI product. Particular emphasis is placed on a good quality crop mask and a good quality validation dataset. In order to have a second dataset which can be used for cross-checking the MODIS classification a Landsat ETM time series for four different dates in the season of 2002 was acquired and classified. We attempted to distinguish five different crop types and achieved satisfactory and good results for winter crops. Three hundred and sixty fields were identified to be suitable for the training and validation of the MODIS classification using a maximum likelihood classification. A novel method based on a pure pixel field sampling is introduced. This novel method is compared with the traditional hard classification of mixed pixels and was found to be superior.     

青藏高原植物形态和解剖适应性研究进展

与低海拔地区相比，青藏高原的太阳辐射、水分条件、氧分压、气温等环境条件都有明显差异，青藏高原的植物在细胞壁厚度、栅栏细胞层数、通气组织大小、异细胞数量和分布、表皮附属物类型等方面与低海拔地区的相比也有较大的不同。综述了在青藏高原特殊的生态条件下，植物在形态和解剖方面的适应性表现，分析了该领域目前的研究特点和存在的一些问题，并在全球环境变化背景下，对其发展前景进行了展望，指出了未来的发展趋势。     

基于遥感信息的华北冬小麦区域生长模型及模拟研究

卫星遥感估产和作物生长模拟在作物监测和产量预测方面有各自不可替代的优势。但是,遥感估产难以揭示作物生长发育和产量形成的内在机理,作物模拟在区域应用时初始值的获取和参数的区域化遇到很多困难。如何利用二者的互补性使其相互结合受到人们关注。该文在Wofost模型本地化和区域化的基础上,首次利用同化法的思路探讨了MODIS遥感信息与华北冬小麦生长模拟模型结合的可行性和方法,初步建立了潜在生产水平(水分适宜条件)下区域遥感-作物模拟框架模型(WSPFRS模型)。模拟结果显示:WSPFRS模型对区域尺度的出苗期重新初始化后,模拟的开花期、成熟期空间分布的准确性比Wofost模拟结果有所改进;利用遥感信息对区域尺度上返青期生物量重新初始化后,模拟贮存器官干重的空间分布更接近实际单产的分布,贮存器官干重的高值区与实际高产区基本相符。该研究将为下一步实际水分供应条件下基于遥感信息的冬小麦区域生长模拟研究奠定了基础。     

Detection of rice sheath blight for in-season disease management using multispectral remote sensing

Timely diagnosis of crop diseases in fields is critical for precision on-farm disease management. Remote sensing technology can be used as an effective and inexpensive method to identify diseased plants in a field scale. However, due to the diversity of crops and their associated diseases, application of the technology to agriculture is still in research stage, which needs to be elaborately investigated for algorithm development and standard image processing procedures. In this paper, we examined the applicability of broadband high spatial-resolution ADAR (Airborne Data Acquisition and Registration) remote sensing data to detect rice sheath blight and developed an approach to further explore the applicability. Based on the field symptom measurements, a comprehensive field disease index (DI) was constructed to measure infection severity of the disease and to relate to image sampled infections. In addition to direct band digital number (DN) values, band ratio indices and standard difference indices were used to examine possible correlations between field and image data. The results indicated that the broadband remote sensing imagery has the capability to detect the disease. Some image indices such as RI₁₄, SDI₁₄ and SDI₂₄ worked better than others. A correlation coefficient above 0.62 indicated that these indices would be valuable to use for identification of the rice disease. In the validation analysis, we obtained a small root mean square error (RMS = 9.1), confirming the applicability of the developed method. Although the results were encouraging, it was difficult to discriminate healthy plants from light infection ones when DI < 20 because of their spectral similarities. Hence, it was clear that identification accuracy increases when infection reaches medium-to-severe levels (DI > 35). This phenomenon illustrated that remote sensing images with higher spectral resolution (more bands and narrower bandwidth) were required in order to further examine the capability of separating the light diseased plants from healthy plants.     

AN APPARENT TEMPERATURE MODEL BASED ON THERMAL EQUILIBRIUM

In this paper,a comprehensive analysis and review of the advances in the research of human body comfort degree is made.Based on the studies of human thermal equilibrium theories contributed by previous researchers,different apparent temperature models corresponding to different environments are set up in accordance with the current situation and the characteristics of metabolism in different groups of people in China.After case studies and comparison with present dominant human body comfort degree statistical models,it is proved that the apparent temperature models have high rationality and wide adaptability.Furthermore,the comfort scaling standard according to apparent temperature is suggested,which is suitable for the middle latitude regions in China.     

四川烤烟主产区冰雹灾害风险评估

以四川烤烟主产区冰雹灾害为研究对象,将烤烟气候适应性特征和自然灾害系统论相结合,利用冰雹频率、DEM高程数据、下垫面类型以及农业经济数据等资料,构建冰雹灾害风险评估指标体系,从致灾因子危险性、孕灾环境敏感性、承灾体易损性和抗灾能力4个方面进行分析,最终建立四川烤烟主产区冰雹灾害精细化风险评估模型并计算风险分布指数,借此将攀西烟区划分为由高至低的5个风险区域和1个不适宜种植区。结果表明,安宁河源头河谷地区、雅砻江下游流域以及攀西地区南部的河谷低山区和丘陵区冰雹灾害风险处于较高水平。评估结果为区域烤烟种植结构调整及冰雹灾害防御工作提供了科学指导。     

南海海岛自动气象站防护应用技术探索

立足海南及南海的自然条件,结合海岛自动气象站在南海高温、高湿、高盐雾、强辐射、强风等恶劣气候环境下使用情况,通过对历年来海岛自动气象站故障及失效模式的统计和分析,总结分析故障原因。根据设备维护人员多年气象设备保障工作积累总结的经验,从海岛自动气象站结构和防护要求出发,集成应用市场上优质材料、先进工艺和多种成熟、关键设备防护技术,形成一些气象设备防护的有效方法措施,以提高海岛自动气象站对海洋环境的适应性和性能,延长设备使用寿命。     

Estimating winter wheat biomass by assimilating leaf area index derived from fusion of Landsat-8 and MODIS data

A sufficient number of satellite acquisitions in a growing season are essential for deriving agronomic indicators, such as green leaf area index (GLAI), to be assimilated into crop models for crop productivity estimation. However, for most high resolution orbital optical satellites, it is often difficult to obtain images frequently due to their long revisit cycles and unfavorable weather conditions. Data fusion algorithms, such as the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) and the Enhanced STARFM (ESTARFM), have been developed to generate synthetic data with high spatial and temporal resolution to address this issue. In this study, we evaluated the approach of assimilating GLAI into the Simple Algorithm for Yield Estimation model (SAFY) for winter wheat biomass estimation. GLAI was estimated using the two-band Enhanced Vegetation Index (EVI2) derived from data acquired by the Operational Land Imager (OLI) onboard the Landsat-8 and a fusion dataset generated by blending the Moderate-Resolution Imaging Spectroradiometer (MODIS) data and the OLI data using the STARFM and ESTARFM models. The fusion dataset had the temporal resolution of the MODIS data and the spatial resolution of the OLI data. Key parameters of the SAFY model were optimised through assimilation of the estimated GLAI into the crop model using the Shuffled Complex Evolution-University of Arizona (SCE-UA) algorithm. A good agreement was achieved between the estimated and field measured biomass by assimilating the GLAI derived from the OLI data (GLAI_L) alone (R² = 0.77 and RMSE = 231 g m⁻²). Assimilation of GLAI derived from the fusion dataset (GLAI_F) resulted in a R² of 0.71 and RMSE of 193 g m⁻² while assimilating the combination of GLAI_L and GLAI_F led to further improvements (R² = 0.76 and RMSE = 176 g m⁻²). Our results demonstrated the potential of using the fusion algorithms to improve crop growth monitoring and crop productivity estimation when the number of high resolution remote sensing data acquisitions is limited.     

Differentiation in reproductive traits of geminate mangrove crabs of the genus Aratus (Decapoda: Brachyura) across the Central American Isthmus

The mangrove crab Aratus pisonii was considered to have an amphi‐American distribution; however, a recent study revealed that the Eastern Tropical Pacific populations were genetically distinct, thus representing a new species: Aratus pacificus. These species separated by the Isthmus of Panama have diverged under different environmental conditions that may have influenced their reproductive biology. As the available information about this genus concerns almost exclusively the Caribbean species, the aim of the present study was to analyse and compare reproductive aspects of A. pacificus and A. pisonii obtained from both the Pacific and Caribbean coasts of Costa Rica. Females were collected from April 2011 to April 2012, and reproductive features such as breeding season, size distribution of ovigerous females, fecundity, reproductive output, embryo volume and embryo water content were assessed. Both species produced embryos during the entire sampled period. Most females of A. pacificus carrying embryos close to hatching were found during the rainy season. Ovigerous females of A. pisonii were substantially larger and reached sexual maturity at a larger size than females of A. pacificus. Embryo production started in A. pacificus at a smaller female size than in A. pisonii. As fecundity increased with female size, the average fecundity was lower in A. pacificus. Females of A. pisonii produced larger embryos, which might be related to lower food availability: higher energy content in the embryo enhances the chances of larval survival. These data regarding reproductive features of the Pacific and Caribbean species support the conclusion to separate A. pacificus from A. pisonii.