Comprehensive Characterization Model of Integrated Cotton Fiber Quality Index

An integrated cotton fiber quality index （ICFQI） model with cotton fiber qualities which can directly express cotton fiber integrated quality and spinning yarn quality was studied. The fiber length, strength, Micronalre （fiber fineness and fiber maturity）, uniformity of fiber length, and short fiber content are the pivotal indexes expressing ICFQI. All of the results above are the basic knowledge to build up the models of ICFQI. According to spinning consistency index （SCI）, spinning strength and spinning yarn integrated quality, ICFQI was the best choice. As the methods of ICFQI had quite a lot of advantages like explicit mechanism, few independent variables. The integrated fiber quality index had a significant positive correlation with yarn strength and spinning consistency, significant negative correlation with yarn evenness and yarn thin places. In additional, the model of the relationship between ICFQI and SCI was established as： SCI=0. 235 6·ICFQI ＋56.153. It was concluded that ICFQI value was the shared reference index for the testing of fiber inspection agency and the selection and distribution of raw cotton bales by textile mills.

化学封顶对不同果枝数棉田株型和产量的影响及其评价指标的筛选

【目的】研究化学封顶对不同果枝数棉田株型和产量的影响及其评价指标的筛选,分析棉花化学封顶剂摇钱素和向铃转的最佳施药时期,优选化学封顶效果评价指标,为化学封顶筛选应用提供支撑。【方法】采用完全随机区组试验设计,以人工打顶为对照,选择化学封顶剂摇钱素和向铃转,分别设置果枝数9台时、果枝数10台时、果枝数11台时、果枝数12台时4个化学封顶处理,测量棉花株高及株高增长量、倒1果枝~倒4果枝长度、有效果枝数、单株果节数、茎粗、主茎节间数、棉铃空间分布和籽棉产量。【结果】与人工打顶相比,果枝数9台时化学封顶处理的棉花株高显著增加,果枝数10台时施用向铃转、果枝数11台和12台时喷施摇钱素后单株果节数增加,化学封顶后主茎节间数增多、倒1果枝~倒4果枝长度变短,果枝数10台时施用向铃转后有效果枝率、化学封顶后茎粗、除果枝数9台时喷施摇钱素后上部铃占比外棉铃空间分布均变化不大。果枝数10台时喷施向铃转、果枝数11台和12台时喷施摇钱素后籽棉产量与人工打顶相比差异不显著。单株有效果枝率(以下简称果枝率)可作为化学封顶对棉花株型调控的评价指标。【结论】果枝数10台时喷施向铃转、果枝数11台时喷施摇钱素后棉花有效果枝率和单株果节数最高、株高增长量不高、籽棉产量不降低,有效果枝率可用于评价化学封顶对棉花株型调控的首选指标。

基于无人机多光谱的棉花多生育期叶面积指数反演

【目的】叶面积指数(leaf area index,LAI)是表征作物长势、光合、蒸腾的重要指标。论文旨在研究不同生育期、多生育期无人机多光谱数据棉花LAI估测模型,明确不同生育期间棉花LAI估测模型变化规律,为实时掌握棉花长势并因地制宜进行田间科学管理提供依据。【方法】利用大疆精灵4多光谱无人机获取棉花现蕾期、初花期、结铃期、吐絮期多光谱图像和RGB图像。选用归一化差植被指数(NDVI)、绿度归一化差植被指数(GNDVI)、归一化差红边指数(NDRE)、叶片叶绿素指数(LCI)、优化的土壤调节植被指数(OSAVI)5种多光谱指数和修正红绿植被指数(MGRVI)、红绿植被指数(GRVI)、绿叶指数(GLA)、超红指数(EXR)、大气阻抗植被指数(VARI)5种颜色指数分别建立棉花各生育期及棉花生长多生育期数据集合,结合打孔法获取地面LAI实测数据,使用机器学习算法中偏最小二乘(PLSR)、岭回归(RR)、随机森林(RF)、支持向量机(SVM)、神经网络(BP)构建棉花LAI预测模型。【结果】覆膜棉花LAI随着生育期的变化呈现先增长后下降的趋势,现蕾期、初花期、结铃期内侧棉花叶面积指数均值均显著大于外侧(P<0.05);选择的指数在各时期彼此间均呈显著相关(P<0.05),总体而言,多光谱指数与颜色指数间的相关性随着生育期的进行而呈现下降趋势,选择的指数在各时期均与棉花LAI相关性显著(P<0.05),多光谱指数相关系数介于0.35—0.85,颜色指数相关系数介于0.49—0.71,相关系数绝对值较大的指数多为多光谱指数,颜色指数与棉花LAI的相关系数绝对值较小;估测模型性能结果显示棉花各生育期模型中多光谱指数优于颜色指数,且各指数模型预测性能随着生育期的变化呈现一定规律性,NDVI是预测棉花LAI的最优指数。从模型结果上看,RF模型和BP模型在各生育期下获得了较高的估计精度。初花期LAI反演模型精度最高,最优模型验证集R2为0.809,MAE为0.288,NRMSE为0.120。多生育期最优模型验证集R2为0.386,MAE为0.700,NRMSE为0.198。【结论】棉花内外侧LAI在现蕾期、初花期、结铃期存在显著差异。在各生育期中,RF和BP模型是预测棉花LAI较优模型。NDVI在各指数中表现最好,是预测棉花LAI的最优指数。多生育期模型效果较单生育期明显下降,最优指数为GNDVI,最优模型为BP。本研究中预测棉花LAI的最优窗口期是初花期。研究结果可为无人机遥感监测棉花LAI提供理论依据和技术支持。

结合变异系数法和机器学习模型的棉花长势监测

为了更加准确地获取棉花关键物候期的长势信息,本文首先通过棉花制图指数提取棉花种植区域;然后利用变异系数法将反映棉花长势的株高、SPAD值、叶片湿重、叶片干重与叶面积5种指标构建为一个综合长势指标,即棉花长势指数(FBCGI);最后选取最优特征变量,结合随机森林模型构建棉花长势反演模型。结果表明:①棉花总体分类精度达到81.65%;②与5种单一长势指标相比,构建的FBCGI与植被指数的相关性更高;③基于最优特征变量和随机森林模型构建的棉花长势监测模型,在建模集和验证集中的R 2和RMSE分别为0.74、0.07和0.51、0.10。研究结果可为棉花长势监测提供重要参考。

塔里木河流域水-耕地-粮棉系统耦合关系及影响因素分析

作为典型的干旱区和生态脆弱区,塔里木河流域是我国粮食、棉花的重要生产基地。水资源、耕地资源与粮棉资源的良性协调发展成为流域可持续发展的关键。通过构建塔里木河流域水-耕地-粮棉系统,测算其发展指数,并以耦合协调度模型测量了系统的耦合程度,在此基础上利用Fractional Logit模型分析了水-耕地-粮棉系统协调发展的影响因素。结果表明:(1)塔里木河流域各系统的发展指数呈现水系统>水-耕地-粮棉系统>耕地系统>粮棉系统。五地州中,巴音郭楞蒙古自治州各系统发展指数排名与流域一致,喀什地区和阿克苏地区在耕地和粮棉系统发展水平领先,水资源系统发展水平靠后,而克孜勒苏柯尔克孜自治州与和田地区则是水系统发展指数位居前列,耕地和粮棉系统发展较落后。(2)流域内水-耕地-粮棉系统耦合协调度介于0.475~0.680之间,处于勉强协调与初级协调之间。五地州中,喀什地区最高,克孜勒苏柯尔克孜自治州最低。这一指标经过缓慢提升后在2017年后明显下降。五地州中,阿克苏地区下降最为明显。(3)水库数量、一般公共预算支出及人口数量是影响水-耕地-粮棉系统协调发展状况的关键因素,三者每增加1个单位将分别引起耦合协调度1.0%、21.0%、35.6%的提升。

基于无人机多光谱遥感的棉花生长参数和产量估算

及时准确地监测棉花长势和产量是精准农业栽培管理的关键。无人机(UAV)平台能够快速获取高时空分辨率的遥感数据,在作物生长参数和产量估算方面显示出巨大的潜力。以山东省滨州市棉花为研究对象,利用安装在无人机上的多光谱相机获取遥感影像,分别提取各波段反射率,筛选出8种植被指数,采用多元线性回归(MLR)、随机森林(RF)、人工神经网络(BPNN)3种方法分别构建棉花的株高、叶绿素相对含量、单株产量的估计模型并进行验证。结果表明,基于BPNN的预测模型精度明显优于MLR和RF模型,盛花期与成熟期棉花株高估计模型验证集的R^(2)分别为0.842和0.670;叶绿素相对含量估算模型验证集的R^(2)分别为0.725和0.765;产量估算模型验证集的R^(2)分别为0.860和0.846。为无人机遥感在作物生长参数与产量估算领域中的应用提供理论依据,为进一步优化农业生产管理、科学决策提供参考。

典型残膜回收机棉田作业性能试验对比

为获取目前使用的典型残膜回收机的作业性能,文中选取了具有代表性的3种地表残膜回收机和2种耕层残膜回收机进行覆膜种植棉田测试。测试指标选取残膜回收率、含杂率、作业效率、作业费用、油耗和故障率。通过多次测试,在残膜回收率、含杂率、作业效率、作业费用、故障率和油耗等方面,地表4JSM型棉秸秆还田及残膜回收联合作业机、耕层SG-2型梳齿式耕层残膜回收机明显优于其他3种机型。表层残膜回收机作业时,残膜回收率、作业效率与含杂率是衡量作业性能的关键指标。测试结果可为用户提供参考。

不同水分胁迫处理对陆地棉核心种质资源的影响

为研究不同水分胁迫下陆地棉对干旱的响应能力并筛选棉花抗旱关键指标和优异抗旱种质资源,选取30份陆地棉核心种质为试验材料,以全生育期正常灌水处理为对照,设置播种后和花铃期各浇水1次和花铃期断水2次2种胁迫处理,在蕾期、花铃期和吐絮期测定相应指标,通过描述性统计分析、差异分析、主成分分析和相关性分析,采用抗旱综合度量值(D)进行各材料的抗旱性评价。结果表明,干旱胁迫对不同棉花材料的生长发育均有不同程度的影响,播种后和花铃期各浇一水处理的D值离散较大(0.285~0.774),能更清晰地区分不同品种的抗旱性。利用D值可将30份材料分为4类:第Ⅰ类为抗旱材料,包括‘中棉所41’‘新陆早7号’等6个品种;第Ⅱ类为中抗材料,包括‘晋棉46’‘新陆早31号’等11个品种;第Ⅲ类为敏感材料,包括‘中棉所17’‘鲁1138’等5个品种;第Ⅳ类为高敏材料,包括‘新陆中8号’‘酒棉8号’等8个品种。果枝始节数、果枝数、株高、皮面产量和衣分5个指标对干旱较为敏感,可作为棉花抗旱评价的关键指标。以上研究结果可为棉花抗旱育种提供参考。

基于无人机RGB影像的棉花苗期株数提取研究

快速、准确、大范围地获取棉花苗期株数对于棉花早期育种决策以及实现棉田的精准管理起着至关重要的作用。针对棉花苗期田间存在盖地膜等干扰易对株数提取造成影响,提出一种基于过红指数和超绿指数,结合图像处理方法对无人机RGB影像进行棉花株数统计的方法。利用新疆阿克苏地区阿瓦提县的棉田无人机影像进行研究,对采集到的数据进行预处理、超绿指数(ExG)和过红指数(ExR)计算、Otsu阈值分割等处理,经处理后的二值图像噪点以及盖地膜产生的误分类像选择采用Majority分析处理进行去噪,其中对Majority分析中的3×3、5×5、7×7、9×9不同大小的变换核的去噪效果进行对比分析,实现对棉花苗期株数的提取。经试验得出在过红指数9×9变换核处理下棉花株数提取效果最好,统计的株数准确率达到97.84%。超绿指数在不同大小的变换核处理后的棉花株数统计准确率都在95%以上,其中基于5×5变换核提取的棉花株数准确率达到98.86%。本方法不仅能够提高棉花株数统计的准确性,也可为棉田早期育种,精准管理提供技术支撑。

ES/棉热粘合混纺纱的制备及性能

为了开发一种热粘合混纺纱,研究热粘合纤维的混入对纱线结构和性能的影响,采用ES纤维和棉纤维进行混纺,制备出不同混纺比(40/60、50/50、60/40、70/30、100/0)、不同细度(30tex、24tex、18tex)的ES纤维/棉混纺纱,研究了不同热粘合处理条件下(加热温度、加热时间)纱线断裂强力、毛羽指数和芯吸性能等变化。结果表明,热粘合处理后混纺纱的断裂强力有较大的提升,随着热粘合温度的升高、热粘合时间的增加,纱线的毛羽指数明显减小,但芯吸性能有所下降。

基于机器学习算法的滴灌棉花地上部氮浓度估测模型研究

地上部氮浓度是准确诊断作物氮素丰缺进而评价其生长状况的重要指标。通过构建基于高光谱的滴灌棉花地上部氮浓度估测模型,实现棉花氮素含量的实时、无损、精确获取,为精准施肥提供理论依据和技术支撑。以新疆北部主栽棉花‘新陆早45号’和‘新陆早53号’为供试品种,设置6个施纯氮处理(0、120、240、348、360、480 kg/hm^(2)),测量棉花冠层高光谱信息,利用函数变换去除冗余,一阶与二阶导数筛选结果相似,倒数的对数筛选结果较为分散。采用机器学习权重排序进行特征筛选,共选出359、371、751、752、746、739、755 nm等7个特征波段。同时遍历波长组合,优化前人研究与氮素高相关的植被指数,共选出RVI′_(810,460)、NDVI′_(811,856)、NDVI′_(750,705)、RVI′_(740,720)、RVI′_(851,852)、DVI′_(359,360)、NDVI′_(851,852)等7个光谱指数。将筛选得到的特征波段与植被指数分别利用岭回归、决策树、引导聚类、增强学习算法与棉花氮素建立养分估测模型,最终Adaboost迭代算法所建立滴灌棉花地上部氮浓度估测模型效果最优,模型精度R^(2)达到0.911,RMSE为1.362。利用光谱信息可以有效反演棉花氮营养状态,基于植被指数构建的模型估测精度较特征波段更为稳定;对现有的植被指数特征波段进行优化,可以有效提升模型的估测精度;对比分析不同建模方式下模型精度,集成学习相比单机器学习在进行棉花氮营养估测时更有优势。

机采长绒棉质量控制与梳理效果探析

为了解决长绒棉人工采摘成本高、机采含杂率高等问题,从长绒棉品种、种植、采摘、加工技术与工艺,梳理效率和梳理效果方面分析机采长绒棉质量控制的关键路径;通过对比分析不同国家生产的机采长绒棉物理指标及性能,以及梳棉工序、精梳工序的梳理效率和梳理效果,指出:改善机采长绒棉的种植环境、梳理器材的质量,是提高机采长绒棉梳理效果和梳理效率的途径,也是降低纺纱梳理成本、提高梳棉工序和精梳工序梳理质量的关键。

机采棉种植模式下不同棉花品种适应性研究

明确各品种在机采棉种植模式下形态、生理及产量因子变化,为长江流域棉花机械化生产中品种选择提供理论基础。通过2018—2019年大田试验,以‘中棉所63F2’(杂交棉品种)低密度(4.5万株/hm^(2))为对照,研究‘中棉所63F2’和‘中棉所425’(常规早熟棉品种)、‘中棉所50’(常规早熟棉品种)等3个棉花品种在高密度(9.0万株/hm^(2))机采棉种植模式下的品种生育进程、农艺性状、干物质积累及产量变化。结果表明,各品种在机采棉种植模式下,其叶面积指数、干物质积累量、成铃数及产量均高于对照;‘中棉所63F2’单铃重、籽棉产量高于2个常规早熟棉花品种,但未达显著水平。常规早熟棉品种‘中棉所425’、‘中棉所50’成熟较早、集中成铃,适宜长江流域一年两熟模式下连茬种植。

Effects of Copper-based Nutritional Foliar Fertilizers on Photosynthetic Characteristics,Yield and Disease Control Efficiency of Cotton

[Objectives] The effects of copper-based nutrient foliar fertilizer on photosynthetic characteristics,yield,accumulation and distribution of trace elements in various organs,disease prevention effect and soil enzyme activity were studied,so as to provide a theoretical basis for the application of foliar fertilizers in cotton production. [Methods]Through two years of field experiments,six treatments were set in total,namely spraying water( CK),traditional Bordeaux mixture( BDM),Kocide 2000( KCD),copper-based nutrient foliar fertilizer( CF),iron-copper-based nutrient foliar fertilizer( CFFe),and zinc-boron-copper-based nutrient foliar fertilizer( CFZnB). Randomized block arrangement was adopted. Chlorophyll content in leaves was measured at each growth stage of the cotton. Photosynthetic characteristics of leaves were measured at the peak bolling stage. Plants were sampled at initial boll opening stage. The whole plant was divided into root,stem,leaf and cotton boll parts,in which the total copper,total zinc,total iron contents and accumulations were determined. Soil samples were collected from each plot,followed by the determination of soil enzyme activity. Disease index was investigated at bud,flowering and boll-forming and boll opening stage. [Results]( 1) Spraying CFFe,CFZnB,CF and KCD could significantly improve chlorophyll content of cotton leaves,and the CFFe treatment had the highest increase up to13. 30%,followed by the CFZnB treatment,which was 11. 40% higher than the CK; and photosynthetic rate,stomata conductance and transpiration rate could be improved significantly,and the CFFe treatment showed the highest photosynthetic rate,which increased by 26. 35% compared with the CK,followed by the CFZnB treatment,which increased by 17. 96% compared with CK; and intercellular CO2 concentration was significantly reduced.( 2) Spraying BDM,KCD,CF,CFFe and CFZnB can significantly increase total copper content and accumulation in various cotton organs( except the total copper content in the stem part of the CFZnB treatment; the CFZnB and CFFe treatments can significantly increase total zinc content and accumulation in various cotton organs; and spraying CFFe,CFZnB and CF can significantly increase total iron content and accumulation in various cotton organs( except the total iron content in the stem part of the CF treatment).( 3)Spraying CFFe,CFZnB,CF,KCD and BDM greatly reduced the disease index at flowering and boll-forming and boll opening stages.( 4) The CFZnB and CFFe treatments had the highest soil urease activity,which was 7. 14% higher than that of the CK,but the difference from the CK was not significant; the catalase activity of each treatment was significantly higher than that of the BDM treatment; and the sucrase activity of each treatment was significantly higher than that of the CK.( 5) Spraying CFFe,CFZnB,CF and KCD significantly improved lint yield of cotton,and the CFZnB treatment showed the highest yield increase up to 12. 34%,followed by the CFFe treatment,with an increase in the range of 8. 77%-10. 20%. [Conclusions]Copper-based nutrient foliar fertilizers have dual functions of disease control and prevention and plant nutrition and health care,and not only can significantly increase cotton yield,but also has certain disease prevention effect.It is recommended to use copper-based nutrient foliar fertilizers.

Motes percentage and ginning outturn as affected with cotton cultivar and location

The present study was conducted to analyze cotton cultivar and location differences in motes, and to determine the relationships among these and ginning outturn. Therefore, the seed cotton of five promising hybrids namely;G.77 × Pima S6 and G.84 × (G.74 × G.68) growing in [Kafr El-Sheikh - Kafr El-Dawar - Etay El-Barood - Damietta], G.89 × Pima S6 growing in [El-Sharkia - El-Gharbiya - El-Dakahliya - El-Monofiya], G.83 × (G.75 × 5844) × G.80 and G.90 × Australian growing in [Sohag - El-Minia - Beni-Sueif - El-Faium] were used in this study. The results obtained indicate that the varieties exhibited different behavior responses to environmental conditions. On the whole, environmental factors associated with differences in place of growth, appeared to have much more influence on the number of motes than did varietal factors. Most of the locks for the promising hybrids at the different locations tend to cluster around the mean of 6 or 7 seeds per lock. There is a fairly marked tendency for the lock index, lint weight and lint percentage to decrease as the motes percentage increase. On the other hand, most of the promising hybrids under study tend to increase in the seed index as the motes percentage increase. However, the increasing in seed index as a result of the increasing in motes percentage for some cotton cultivars growing at different environments could be explain the difference in behavior for these cotton cultivars in lint percentage.

融合无人机光谱信息与纹理特征的棉花叶面积指数估测

农田尺度下作物叶面积指数(Leaf area index,LAI)的精准监测,对于研究群体结构对产量和管理措施的响应具有重要意义。目前普遍采用无人机光谱特征反演作物的LAI指数,作为长势和冠层结构诊断的重要依据,其估测精度的准确性是否可以提高仍有待研究。作物表面特征,如灰度和颜色,在不同生育阶段会发生变化。为此,本研究考虑到LAI的影响因素,设置不同的种植密度和氮素水平营造差异化的冠层结构,利用搭载多光谱传感器的无人机获取主要生育时期棉花的冠层图像得到植被指数(Vegetation indexs,VIs),基于二阶概率统计滤波(Co-occurrence measures)方法获取均值(MEA)、方差(VAR)、协同性(HOM)、对比度(CON)、相异性(DIS)、信息熵(ENT)、二阶矩(SEM)和相关性(COR)等8个纹理特征值(Texture features,TFs)。最后,采用支持向量机回归(SVR)、偏最小二乘法(PLSR)、深度神经网络(DNN)分别建立基于光谱特征、纹理特征以及二者结合的棉花LAI的估算模型,并比较差异。试验结果表明:VI((nir/green))、VI((nir/red))、GNDVI、OSAVI和均值与LAI具有较高的相关性;采用SVR建立的LAI估测精度最高(R2=0.78,RMSE为0.22,RRMSE为0.10);在3种估算模型中,植被指数与纹理特征相结合的SVR模型,较VIs、TFs模型精度分别提高7.89%和32.26%。因此,融合无人机光谱信息和图像纹理的LAI估算模型为密植作物棉花冠层结构的诊断提供了一种可行、准确的方法。

Evaluation of genetic diversity in short duration cotton(Gossypium hirsutum L.)

Background: Cotton(Gossypium hirsutum L.) is an important fiber crop in Bangladesh. Genetic diversity among the genotypes of a germplasm has a great importance for cotton breeding. An experiment was carried out at the experimental field of Cotton Research, Training and Seed Multiplication Farm, Sreepur, Gazipur during the cropping season of 2015-2016 with 100 genotypes to evaluate genetic diversity of cotton genotypes for short duration using field performance.Results: The genotypes under study were grouped into ten clusters through multivariate analysis using GENSTAT-5.Cluster III contained maximum number of genotypes(16) while cluster X contained the least number of genotypes(7).The inter cluster distances were larger than intra cluster distances in all cases suggesting wider genetic diversity among the genotypes of different clusters. The maximum and minimum inter cluster distances were observed between clusters II and V(10.78) and clusters VIII and IX(3.30), respectively. The results indicated diverse and close relationship among the genotypes of those clusters. Earliness index, single boll weight and days to boll opening showed the higher contribution to the genetic divergence among 19 characters.Conclusion: Based on the results of genetic diversity and earliness index, the genotypes from cluster Ⅱ could be used as parent in hybridization program for the development of short duration cotton variety.

捻度对锦纶/棉混纺纱质量指标的影响

为进一步提升锦纶/棉混纺纱质量,针对捻度与锦纶/棉混纺纱质量指标的关系问题进行了分析。在其它工艺相同的条件下调整细纱工序捻度的设置,纺制了16种锦纶/棉混纺纱,对其质量指标进行测试,并通过SPSS软件对捻度与混纺纱质量指标之间的关系进行拟合与回归分析,建立了混纺纱质量指标随捻度变化的回归预测模型。结果表明,捻度与锦纶/棉混纺纱强伸性能、粗细节和毛羽指标显著相关,测试组数据与预测值间残差绝对值均在3倍残差标准差以内,验证了模型的有效性。捻度大小直接影响锦纶/棉混纺纱的强伸性能、粗细节和毛羽指标,预测模型反映了捻度对混纺纱强伸性能、粗细节和毛羽指标影响的数量相关关系,为锦纶/棉混纺纱生产中捻度设计和快速调整提供了参考依据。

基于叶片生物量的南疆盐碱地棉花临界氮稀释曲线构建

为验证基于叶片生物量的西北内陆区(新疆南疆中熟棉区)盐碱地滴灌棉花临界氮稀释曲线年际间的稳定性和适应性,明确叶氮营养指数(LNNI)模型、叶片氮浓度(LNC)、氮水平(Nlevel)和籽棉产量(Y)间的关系模型对西北内陆区(新疆南疆中熟棉区)盐碱地滴灌棉花氮状况和适宜施氮量诊断、评价结果的一致性,通过2年定位5个氮水平(0、75、150、300、450 kg/hm^(2))的田间试验,建立了基于叶片生物量(LBM)不同棉花品种的临界氮(LNCc)稀释曲线、LNNI及LNC与Nlevel和Y间的关系模型。结果表明:(1)LNC与LBM符合幂指数关系,模型可分为两部分描述:新陆中55号(当LBM≥1.02 t/hm^(2)时,LNCc=3.41×LBM-0.38;LBM<1.02 t/hm^(2)时,LNCc=2.18%),新陆中78号(当LBM≥1.07 t/hm^(2)时,LNCc=4.08×LBM-0.43;当LBM<1.07 t/hm^(2)时,LNCc=2.61%);(2)新陆中55号和78号LNCc基于1∶1直线的R2、RMSE、ME分别为0.941、0.116 g/100 g、0.944和0.975、0.088 g/100 g、0.975,年际间具有较好的稳定性和适应性;(3)不同年际间,氮水平下新陆中55号和78号LNNI分别在0.76~1.12、0.70~1.09间波动,LNNI模型对新陆中55号和78号适宜氮水平诊断结果均以300 kg/hm^(2)处理最优;(4)LNC与Nlevel和Y关系模型得到新陆中55号和78号结铃期(BS)、吐絮期(OS)的LNC和Y分别为2.32%、1.95%和5850、5860 kg/hm^(2)及2.30%、1.99%和6070、5970 kg/hm^(2),适宜施氮量范围在313.3~380.0、335.0~385.0 kg/hm^(2)之间,这与氮水平和籽棉产量关系模型对新陆中55号和78号的适宜施氮量评价结果基本一致。研究结果可为西北内陆区(新疆南疆中熟棉区)盐碱地滴灌棉花氮状况精确诊断和适宜施氮量评价提供理论依据和方法参考。

气候变暖对新疆棉花种植气候适宜性分区的影响

基于新疆102个气象站1961—2020年历史气候资料,使用统计学方法以及ArcGIS的空间插值技术,在对近60年影响新疆棉花种植的主要气候因子,≥10℃积温、无霜冻期和7月平均气温时空变化分析的基础上,结合新疆棉花种植气候适宜性区划指标,就不同品种熟性棉花适宜种植分区的变化进行研究。结果表明:1961—2020年新疆≥10℃积温、无霜冻期和7月平均气温呈显著增多或上升趋势,并且上述要素均于1997年发生突变。受其影响,1997年后较之前,新疆不同品种熟性棉花适宜种植区的海拔上限均不同程度的抬升,其中,准噶尔盆地和吐鲁番、哈密盆地棉区海拔上限抬升150~200 m,塔里木盆地棉区抬升50~100 m;气候变暖使新疆宜棉区扩大,不宜棉区缩小,且部分棉区适宜种植的棉花品种向生育期较长、产量较高的品种转变,这对促进新疆棉花的发展十分有利。