棉田土壤养分分析与土壤墒情监测系统应用

【目的】研究土壤养分的空间变异程度及分布规律,为该区域科学施肥提供依据。【方法】以新疆生产建设兵团第八师石河子总场六分场数字农业示范田为研究区域,应用土壤墒情监测系统、GIS与地统计学的方法,对棉田土壤含水量与温度进行实时采集、分析并存储在服务器里面,分析石河子总场土壤含水量和温度变化规律、棉田土壤养分空间分布特点及变异规律。【结果】(1)根据监测数据分析,随着灌水量增加和棉花生育期推进,上层0~30 cm比下层40~60 cm的土壤含水量变化趋势明显。0~20 cm土层土壤补偿水比较充分,各个监测点土壤含水量基本维持在比较适宜的范围内。土壤各层温度受大气温度影响并随着土层深度的加深而减弱,随着土层深度的逐渐加深滞后时间相对延长;受棉株逐渐长高变大以后遮阴等造成的影响,7月以后各土层温度逐渐持平,波动不大。(2)土壤全氮、速效磷和速效钾均呈现出中等程度变异;(3)土壤速效钾的块金值在25%~75%(块金值为0.497)表现为中等空间自相关性外,土壤全氮、速效磷指标的块金系数小于25%表现为强烈的空间自相关性。【结论】应用土壤墒情实时监测系统指导棉田灌溉,较往年没有任何减产减质的情况下,棉花灌溉在全生育期内比以往灌溉次数下降了1~3次,节约水资源约20%左右。研究区域内土壤全氮、速效磷和速效钾变异呈现中等程度变异特征,全氮、速效磷表现为极强空间自相关性,速效钾表现为中等强度的空间相关性。     

安徽沿江地区油麦后直播棉的品种选用策略

在目前安徽沿江地区不能实现棉花机采的情况下,提出了“植株高度既适于机采也适于人工采收,含絮力适中(不易落花便于集中采收),生育期适中(播种到采收为180天左右),纤维品质及产量性状较优(纤维长度30.0 mm以上,断裂比强度30.0 cN/tex以上,马克隆值5.0以下,籽棉产量3750 kg/hm 2以上,衣分在40%左右)”的油(或麦)后直播棉模式的人工采收品种选用策略。旨在促进安徽沿江地区棉花生产稳定发展。     

化学打顶对阿拉尔垦区主栽品种光合冠层的影响

化学打顶是指利用植物生长调节剂来打破作物顶端优势,进而保障作物的正常生长和生产。本文为探究化学打顶对作物的影响,利用摇钱素和棉花打顶剂处理新陆中70和新陆中82不同品种,同时测定不同化学打顶剂处理条件下,棉花的净光合速率、气孔导度、蒸腾速率、胞间CO₂浓度及棉花冠层叶面积指数指标。研究发现：不同化学打顶处理条件下,与人工打顶相比化学打顶的棉花的五种指标变化均不明显,但新陆中70和新陆中82品种的净光合速率平均值与对照相比分别高出3 μmol/(m2.s)和2 μmol/(m2.s),且冠层叶面积指数值比人工打顶的略高。试验结果表明化学打顶处理后没有造成棉花疯长,提高了光能利用率,进而增加作物群体的光合作用。     

Relationships Among the Feeding Behaviors of a Mirid Bug on Cotton Leaves of Different Ages and Plant Biochemical Substances

Apolygus lucorum (Meyer-Dür) (Hemiptera: Miridae) tends to feed on young plant tissues. To explore the relationship between stylet probing behaviors of adult A. lucorum and conditions of cotton leaves, we conducted an experiment using electropenetrography (EPG). Behaviors were recorded on four cotton varieties, in relation to thickness and biochemical traits of differently-aged leaves. Cotton leaf age had a significant effect on the probing behavior of A. lucorum but cotton variety did not. One-day-old leaves of A. lucorum received the highest mean number of stylet probes (penetrations) per insect, and longest mean durations per insect of combined stylet probing or its components, cell rupture and ingestion behaviors. All of the leaf traits (thickness and biochemical substances) were similar among these four cotton varieties. Leaf thickness had a significantly negative effect on the same four variables above. Gossypol and tannin also had a negative impact on combined probing duration. Redundancy analysis showed that the four EPG variables were closely related to nutrient substances (amino acids, sugar, and water) while they had the opposite relationship with plant defense substances (gossypol and tannin). On cotton in the seedling stages, A. lucorum fed more readily on the youngest, thinnest leaves in our no-choice EPG experiments. Nutrients and chemical resistance substances determined the probing duration of A. lucorum. Our findings can contribute to better understanding of patterns of feeding and host consumption by A. lucorum, ultimately improving cotton resistance to A. lucorum.     

剔除土壤背景的棉花水分胁迫无人机热红外遥感诊断

剔除无人机热红外影像中的土壤背景是提高作物水分诊断精度的有效途径,但也是热红外图像处理的难点问题。本文以不同水分处理的花铃期棉花为研究对象,分别在09:00、13:00和17:00等3个时刻,连续5 d采集无人机高分辨率热红外影像,并采用二值化Ostu算法和Canny边缘检测算法对热红外图像进行掩膜处理,实现对土壤背景的剔除,然后分别计算二值化Ostu算法、Canny边缘检测算法和包含土壤背景下的3种棉花水分胁迫指数(Crop water stress index,CWSI),最后建立不同时刻下3种CWSI与棉花叶片气孔导度Gs的关系模型。研究结果表明,应用Canny边缘检测算法可有效剔除热红外影像中的土壤背景,剔除土壤背景后的温度直方图呈单峰的偏态分布;3种处理方法获得的作物水分胁迫指数CWSI中,Canny边缘检测算法的CWSI最小,二值化Ostu算法的CWSI较高,包含土壤背景的CWSI最大;采用Canny边缘检测算法剔除土壤背景后的CWSI与棉花叶片气孔导度Gs的决定系数R2达到0.84,Ostu算法的结果次之,包含土壤背景的最差。本研究可为无人机热红外遥感监测作物水分状况提供参考。     

抛膜链齿输送式残膜回收机设计与试验

新疆棉田残膜污染问题严重,机械回收残膜是目前主要的回收方式。现有残膜回收机普遍采用弹齿或伸缩杆齿式起膜装置,回收过程中容易出现残膜缠绕工作部件、卸膜难等问题,影响起膜和卸膜效果。为此,借鉴现有机型的优点,通过刨膜辊刀起膜、抛膜辊刀抛送原理,设计一种起膜抛送、链齿输送、自动脱膜的抛膜链齿输送式残膜回收机。该机具主要由起膜装置、输送装置、脱膜装置、传动系统和集膜箱等组成。残膜通过抛送起膜,配合链齿输送,实现残膜与土块分离,保证了起膜的可靠性;利用自动脱膜和刮板式脱膜机构完成卸膜,解决了残膜缠绕、卸膜难的问题。田间试验结果表明:当作业速度为4~7 km/h时,残膜回收率均值为90.6%,机具作业效率均值为0.84 hm~2/h,残膜含杂率均值为3.971%,当作业速度较快时,提高了作业效率,但回收率降低,含杂率增大。当作业速度为5 km/h时,回收率均值为91.8%,作业效率均值为0.733 hm~2/h,含杂率均值为2.605%,为较适宜的作业速度。该机具运行可靠,起膜与脱膜效果较好,可用于新疆棉田残膜回收。     

Effect of Spatial Soil Moisture Stress on Cotton Root Architecture

[Objective] This study aimed to explore the effects of spatial soil moisture stress on cotton root growth, and to analyze the corresponding changes in cotton root architecture. [Method] To produce soil moisture spatial stress, cotton spacing was set at 30 cm. The cotton was all irrigated on one side of the pole (the side sampling point). By excavating the cotton root, analysis of the main root bifurcation, which was cultivated away from the irrigation point, could be undertaken. [Result] The analyses of the cotton A (the nearest plant to the irrigation location) root system showed that soil moisture near the irrigation point was distributed uniformly. The root system architecture of the cotton cultivated near the irrigation point mostly presented a symmetrical "umbrella" pattern; the difference in root diameter between the main and lateral roots was 5–6 mm, and the average angle between them was 70°–80°, which decreased with the increase in cotton growth stage. Soil moisture spatial stress influenced the cotton plant C, which was cultivated away from the irrigation point, such that the root system architecture was asymmetrical. The roots of cotton plant C grew towards the high soil moisture zone; 48.15% of the lateral roots became thicker, which acted as a bifurcated main root. The difference in diameter between the bifurcated roots was 1–4 mm, and the average angle of the bifurcated roots along the vertical direction was between 20°–37°, which increased with the increase in cotton growth stage. [Conclusion] The results provide important information on the physiological responses of the cotton root system to the soil moisture environment.     

地膜覆盖时间对新疆棉田水热及棉花耗水和产量的影响

该文主要研究不同的地膜覆盖时间对棉田水热及棉花产量的影响。设置了6个地膜覆盖时间:40 d(J1)、55 d(J2)、70 d(J3)、85 d(J4)、100 d(J5)和140 d(全生育期覆盖,CK),2016和2017年在阿克苏绿洲典型滴灌棉田进行田间试验,分析不同地膜覆盖时间对土壤温度、土壤水分、耗水量(crop evapotranspiration,ET_c)、产量、水分利用效率(water use efficiency,WUE)的影响。结果表明,不同地膜覆盖时间可影响土壤水热状况。随着地膜覆盖时间延长,0～80 cm土层含水率逐渐增加,ET_c持续降低,WUE呈增加趋势,但超过100 d后对ET_c及WUE无显著影响。J1、J2、J3和J4处理在揭除膜后,土壤含水率迅速降低,土壤深层水快速消耗,进入铃期后处理间差异才逐步开始缩小。地膜覆盖时间小于100 d会显著减少单株成铃数,降低单铃质量,最终造成减产。J1～J5覆盖时间中,J5处理产量(2 a平均为6 800 kg/hm~2)和WUE(2 a平均为11.5 kg/(hm~2·mm))最高(P0.05),且J5与CK差异不显著(P0.05),可见,地膜覆盖100 d较适宜。该研究结果可为绿洲棉区合理地使用地膜提供科学依据,也为残膜回收及降解地膜的安全应用提供理论支持。     

花铃期干旱胁迫对不同棉花品种光合特性影响及抗旱性评价

以28份抗旱性不同的棉花品种为材料,通过大田花铃期水分胁迫,以抗旱系数和主成分分析综合评价各个棉花品种的抗旱水平,并对其评价和等级进行划分。结果表明,各个棉花品种在花铃期干旱胁迫下,各指标反应程度不同,其中叶绿素、净光合速率、水蒸汽压亏缺、气孔导度变化较明显,通过RI值聚类分析,将材料分成4个大类,第Ⅰ类为高抗型品种有C1470、ND359-5、新炮1号、新陆中39等18份品种;第Ⅱ类为中抗型的包括天合995、吉扎81、大铃棉、TM-1、10615-1、塔什干7号;第Ⅲ类为敏感型的包括新陆早1号、新石K7、鲁棉28;第Ⅳ为极敏感型的新陆早26。进一步利用逐步回归建立回归方程D=-1.496+0.775Ci+0.160Gs-0.020VPD+0.719Pn+0.799Tr-0.241WUE+0.663Chl(R2=0.996),筛选出7个指标,分别为Ci、Gs、VPD、A、Tr、WUE、Chl,各材料估计精度大于97.55%。     

Cotton Image Segmentation Algorithm Based on Fusion Method of Markov Random Field and Quantum Particle Swarm Cluster

[Objective] The aim of this study was to improve the cotton image segmentation accuracy in a picking robot image processing system. [Method] An image segmentation algorithm based on a fusion method of Markov random field and quantum particle swarm optimization clustering was proposed. The process of the proposed algorithm is as follows: first, transform the RGB (red, green, blue) images into grayscale; second, use it to segment these images; finally, the threshold of the connected area is set on the basis of the segmented image to obtain the target area. Then, the cotton front image and the cotton side image are selected from the images collected from different angles. The segmentation experiment was carried out by using this algorithm, and compared with the Otsu algorithm, the fuzzy C-means algorithm, the quantum particle swarm image segmentation algorithm and the Markov random field image segmentation algorithm. [Result] The results showed that the segmentation accuracy and peak signal to noise ratio of the proposed algorithm were 98.94% and 77.48 dB. When compared with the Otsu algorithm, fuzzy C-means algorithm, quantum particle swarm optimization algorithm and Markov random field algorithm, the average segmentation accuracy and peak signal to noise ratio of the proposed algorithm increased by 2.47%–4.56%, and 9.81–13.11 dB, respectively. [Conclusion] The proposed algorithm had higher segmentation accuracy and higher peak signal to noise ratio than the other algorithms tested.