基于GF-1/WFV数据的冬小麦条锈病遥感监测

条锈病是冬小麦常见病害,利用遥感影像对条锈病病害区域进行准确监测具有重要意义。该文利用GF-1/WFV影像,结合条锈病地面光谱数据分析,采用冬小麦条锈病遥感监测指数(wheat stripe rust index,WSRI)对河南西华县冬小麦条锈病发病范围进行了估测。首先,利用冬小麦NDVI加权指数(weighted NDVI index,WNDVI)获取冬小麦种植区域。其次,利用影像4个波段反射率之和提取不同冬小麦品种的分布范围,值较高的为条锈病高抗品种(郑麦系列),较低的则是条锈病易感品种(矮壮系列)。再次,构建冬小麦条锈病指数(wheat stripe rust index,WSRI),结合地面实地调查的条锈病分布数据,通过设定合理的WSRI指数划分阈值,提取条锈病染病区域并进行精度验证。结果表明,研究区内小麦条锈病空间分布识别的总体精度在84.0%以上,具有区域监测应用的潜力。该方法简单,可操作性强,表明宽波段GF-1影像结合WSRI指数的技术,是一种比较可行的小麦条锈病遥感监测方案。     

特用经济作物栽培技术实习实践教学改革——以河北科技师范学院为例

为提升河北科技师范学院实习实践教学的质量,从3个实习实训基地教学方式的改革到实习课程考核制度的改革两方面的综合改革入手,旨在激发学生的学习动力和兴趣,引导学生提出问题并辅助学生加以解决,进而保证学科教学改革顺利进行,使得学生实习实践能力有所提升。     

长三角地区农作物秸秆资源量的时空分布特点

为提高长三角地区秸秆资源的综合利用率,采用草谷比法,评估长三角地区秸秆的资源量和秸秆资源的分布特点。结果表明:2000-2014年长三角地区农作物秸秆资源总量呈稳中上升趋势;秸秆分布地区格局差异显著;作物秸秆产量主要分布在粮食主产区的江苏省和安徽省,浙江省和上海市则比较低,2000-2014年作物秸秆资源量为江苏安徽浙江上海;农作物秸秆主要类型为稻谷、小麦和油菜籽,以稻谷为长三角地区最主要的粮食作物秸秆。     

Corrective Potential of Alkaline Residue (Dregs) from Cellulose Industry in an Acid Soil Cultivated Under No-tillage

The use of alkaline residues from cellulose industry can increase soil fertility and crop productivity, but some of these residues, such as dregs, can also reduce soil physical quality. This study aimed to evaluate the effects of the dregs compared to lime as corrective for soil acidity applied on the surface under no-tillage. The treatments applied, half in 2004 and half in 2006, were: without corrective; dregs rates of 3.25, 6.5 and 13 Mg ha^?1 and dolomitic lime rates of 5.25 and 10.5 Mg ha^?1. After 5.5 years since the first application, soil chemical and physical attributes were determined, as well as soybean yield in 2010 and bean yield in 2011. Positive effects were observed on the soil chemical attributes with the application of dregs or lime, such as increased pH, calcium content, cation exchange capacity, and base saturation, and decreased the aluminum saturation. However, it was observed increase in sodium content and calcium/magnesium ratio with the application of dregs, however without impairing the soil physical quality. The soybean and bean yield increased in a similar way using dregs or lime. These results indicate the possibility of using dregs as corrective of soil acidity.     

Assessment of Methods for Measuring Soil Microbial Biomass Carbon in Temperate Fruit Tree-Based Ecosystems

We investigated the potential of three methods of quantifying microbial biomass carbon (MBC), viz., chloroform fumigation-extraction (CFE) following organic C estimation through Vance method (CFE-V) and Snyder–Trofymow method (CFE-ST), and substrate-induced respiration (SIR) method in soils under various temperate fruit crops along with a control (no plantation) at 0–20 and 21–40 cm soil depths. CFE methods have shown significant (p < 0.05) increase in chloroform labile C in all orchards over the control in surface soil. The interaction between the fruit crops and methods, although significant (p < 0.01), indicated that CFE-ST and SIR methods were statistically at par with each other within the same fruit crop, except peach plantation (CEF-ST significantly lower than SIR) in 0–20 cm soil depth. The coefficient of variation recorded for chloroform labile organic C estimates by CFE-ST method makes it more precise than CFE-V method, especially in 0–20 cm soil depth. The very close agreement between the methods suggests that over this narrower range (i.e., smaller geographical area) all methods are appropriate for assessing MBC. However, SIR, being most sensitive to orchard plantations and strongly correlated with various soil chemical properties, could preferably be recommended for estimation of MBC in such soils. As an alternative to CFE-V method, CFE-ST may also be used for estimation of chloroform labile organic C in these soils.     

New indicator for classification of agroclimatic conditions for the cultivation of catch crops

The realization of the benefits of stubble catch crops (CC) cultivated after the harvest of the main crop requires the ability to produce substantial amounts of biomass before the onset of winter. The growth and biomass production of CC is primarily determined by the time period of sowing and weather conditions of the site. The construction of a new indicator of agroclimatic conditions for the cultivation of CC is described. This indicator includes the possible time period for CC sowing according to the harvest time of the preceding main crop, temperature, and water conditions for emergence and growth. The termination of growth due to low temperatures is considered. The assumptions used for the construction of the indicator, and the relationships to CC biomass were validated with data from field experiments. The resulting maps of regions in the Czech Republic with similar indicator values for three groups of CC differing in temperature demands are shown.     

旱作作物垄膜种植增温作用及增产效应研究

针对大部分旱作区气候条件恶劣、粮食低产不稳和抗旱减灾能力差等突出问题,在内蒙古阴山北麓典型旗县武川县与大兴安岭南麓典型旱作区兴安盟乌兰浩特市对全覆膜双垄沟种植方式的增温效应及产量形成关系进行了研究,设置传统半覆膜和平作不覆膜种植方式为对照,分别以播种面积逐年扩大的向日葵和传统大面积种植作物玉米为研究材料,总结分析了垄膜种植技术的增温增产作用机理:两种作物全覆膜双垄沟种植方式的全生育期在株间5 cm、15 cm、25 cm土层与行间5 cm、15 cm土层的土壤平均温度分别比平作不覆膜处理增加0.17~4.39℃与0.26~4.17℃;苗期行间日平均温度比平作不覆膜处理分别高1.71℃、2.43℃,株间日平均温度高3.41℃、3.59℃;全生育期土壤平均有效积温分别为2178.8℃、2621.4℃,较平作不覆膜处理增加174.7℃、217.6℃;全覆膜双垄沟种植方式收获时两种作物植株的各项生理指标在各处理中皆为最优;向日葵与玉米的平均产量分别为4165.5 kg hm~(-2)、13633.5 kg hm~(-2),与传统半覆膜和平作不覆膜处理对比增产率分别为29.1%、45.9%和29.1%、17.9%。     

大豆籽粒的化学-力学特性灰色关联度及本构模拟

为研究大豆籽粒在不同受载情况下的力学特性,探索其化学-力学特性之间的关系,该文选择11种大豆籽粒在含水率为8.65%下对其进行化学组分、针尖压入、剪切、压缩试验,并借助Abaqus软件建立本构模型,对压缩试验过程进行模拟仿真。力学试验和模拟结果表明:所测大豆籽粒硬度为18.39~52.58 N/mm,大豆籽粒破损强度为3.65~15.32 MPa,大豆籽粒极限剪切力为12.70~52.33 N,纵轴的抗剪能力明显高于横轴;不同压缩形式和剪切方向分别对大豆籽粒破损强度和极限剪切力影响极显著;试验与仿真的载荷-变形曲线拟合良好,说明所建立的大豆本构模型能够分析研究其抗挤压特性。灰色关联度分析结果表明:与化学组分含量最为密切的力学指标是硬度与接触刚度,其中硬度与粗蛋白质、粗脂肪、粗淀粉、粗纤维含量的关联度分别为0.309 4、0.327 8、0.171 9、0.191 8,接触刚度与其关联度分别为0.220 6、0.283 7、0.186 9、0.133 4,粗蛋白质和粗脂肪含量对硬度与接触刚度的影响最大,其次是粗纤维素,粗淀粉含量。研究结果可为品质预测和品种鉴别提供新的方法和依据。     

基于CASA模型的区域冬小麦生物量遥感估算

该文对原始CASA(carnegie-ames-stanford-approach)模型中归一化植被指数(normalized difference vegetation index,NDVI)最值提取方法及光合有效辐射吸收比(fraction of absorbed photosynthetically active radiation,FPAR)的算法进行了深入分析,并通过综合分析大量国内外文献,更加科学合理的确定了最大光能利用率的取值,最终确立了适合该研究区的CASA模型。该文以河北省邯郸市3个县域冬小麦为研究对象,以HJ-1A/B星遥感数据产品为数据支撑,采用CASA模型对研究区2014年冬小麦生物量进行了估算和精度验证,结果表明:研究区冬小麦生物量平均值为1 485 g/m~2,50%以上区域在1 500~2 000 g/m~2之间。冬小麦实测生物量与预测生物量相关性达到显著水平,R~2为0.811 5。经过50组数据分析对比,平均相对误差为2.13%,其中,最大值为11.54%,最小值为0.33%;平均预测生物量为1 807.54 g/m~2,与平均实测生物量1 720.74 g/m~2相比,绝对误差为86.80 g/m~2,为估算区域冬小麦产量提供理论支撑。     

基于透射光谱的玉米叶片水分含量快速检测

为实现玉米叶片水分含量快速检测,利用近红外光谱仪在300~1 700 nm采用透射法对玉米叶片水分含量进行快速检测。试验利用烘干法对叶片水分梯度进行控制,并测量玉米叶片的透射光谱曲线和含水率。对透射光谱数据采用Savitzky-Golay方法进行平滑预处理,滤除光谱波动噪声干扰。分析了叶片透射光谱与含水率之间的相关关系,通过相关性分析提取敏感波长800、932、1 423 nm;利用主成分分析法提取敏感波长478、748、1058和1 323 nm。综合二者敏感波长最终筛选出水分敏感波长800、1 323、1 058和1 423 nm。利用这4个波长的组合得到比值植被指数、差值植被指数和归一化植被指数等12种植被指数,选取了最优差值植被指数DVI(1423、800)与透射率T1 323和T1 058建立了玉米叶片含水率多元线性回归诊断模型,建模集决定系数Rc2=0.968 8,验证集决定系数Rv2=0.951 9,预测结果方根误差为0.061。结果表明,利用透射光谱技术检测的玉米叶片水分含量具有较高的精度,可为植物叶片水分快速检测仪器开发提供指导。