基于无人机多时相遥感影像的冬小麦产量估算

为高效准确地预测小麦产量,以浙江省冬小麦为研究对象,利用四旋翼无人机精灵4多光谱相机获取冬小麦5个关键生育时期（拔节期、孕穗期、抽穗期、灌浆期、成熟期）的冠层多光谱数据,选取多光谱相机的五个特征波段计算各生育时期的72个植被指数,分别通过逐步多元线性回归（SMLR）、偏最小二乘回归（PLSR）、BP神经网络（BPNN）、支持向量机（SVM）、随机森林（RF）构建不同生育时期的产量估算模型,最后采用决定系数（R）、均方根误差（RMSE）和相对误差（RE）对估算模型进行评价,筛选出最优估算模型。结果表明,基于随机森林建立的模型估算效果最优,SMLR、PLSR和SVM三种方法建立的模型估算效果接近。利用随机森林算法所建拔节期、孕穗期、抽穗期、灌浆期、成熟期模型的R、RMSE和RE分别为0.92、0.35、11%;0.93、0.33、10%;0.94、0.32、9%;0.92、0.36、9%;0.77、0.67、33%。模型验证时,抽穗期估算效果最好（R、RMSE和RE分别为0.91、0.35和15%）,拔节期、孕穗期、灌浆期估算效果接近且有很好的估算能力,成熟期估算精度最差（R、RMSE和RE分别为0.71、0.47和13%）。由此说明,结合机器学习算法和无人机多光谱提取的植被指数可以提高小麦产量估算效果。     

遥感光谱指标和神经网络结合的冬小麦地上部生物量估测

为探讨基于神经网络对小麦地上部生物量（aboveground biomass,AGB）进行遥感估测的可行性,在江苏省泰州泰兴市、盐城大丰区和宿迁沭阳县布设冬小麦大田试验,在对冬小麦近红外波段反射率（near-infrared band reflectance,REF_nir）、红光波段反射率（red band reflectance,REF_red）、归一化差值植被指数（normalized difference vegetation index,NDVI）、差值植被指数（difference vegetation index,DVI）、比值植被指数（ratio vegetation index,RVI）、土壤调节植被指数（soil adjusted vegetation index,SAVI）和优化土壤调节植被指数（optimized soil adjusted vegetation index,OSAVI）等7个遥感光谱指标与冬小麦生长指标（LAI和AGB）进行相关性分析基础上,构建基于BP神经网络的冬小麦AGB估测模型,并与多元线性回归估测模型进行精度比较。结果表明,冬小麦拔节期REF_red、NDVI、RVI、SAVI、OSAVI和LAI与AGB之间存在较好相关性,其中LAI与AGB的相关性最高（相关系数为0.782）,SAVI与AGB的相关性最低(相关系数为0.647)。利用BP神经网络建立的冬小麦AGB估测模型AGB_BP的决定系数（r）为0.918,均方根误差（root mean square error,RMSE）为582.9 kg·hm^-2,平均相对误差（average relative error,ARE）为18.4%。利用多元线性回归分析建立的冬小麦AGB估测模型AGB_RA的r为0.784,RMSE为871.1 kg·hm^-2, ARE为32.6%。利用冬小麦抽穗期AGB实测数据再对模型AGB_BP和AGB_RA进行验证,其RMSE分别为1 140.4和1 676.7 kg·hm^-2, ARE分别为20.5%和33.1%。由此可以看出,冬小麦估测模型AGB_BP精度优于模型AGB_RA,说明利用多个遥感光谱指标结合LAI建模可以有效提高冬小麦AGB的估测精度。     

基于无人机可见光影像与生理指标的小麦估产模型研究

为及时、准确地掌握小麦产量动态信息,基于无人机遥感平台,分别分析了小麦4项生理指标［地面实测叶面积指数、叶片含氮量、叶片含水量及叶片叶绿素相对含量（SPAD值）］及10项植被指数与产量的相关性,以筛选出与产量最为敏感的生理指标与植被指数,并比较了3种建模方法（一元回归UR、多元逐步回归SMLR和主成分回归PCAR）在小麦各生育时期估产的适用性,进而得到小麦最优估产模型。结果表明：（1）不同生育时期两类变量与产量的相关性变化特征一致,均表现为抽穗期>灌浆期>成熟期;不同生理指标、植被指数与产量的相关性在各生育时期均存在差异,生理指标表现为叶片含氮量>LAI>SPAD>叶片含水量;而植被指数在各时期表现不同;（2）以生理指标与植被指数为自变量,采用SMLR模型构建的抽穗期估产模型拟合精度最高,R、RMSE和nRMSE分别为0.828、362.53 kg·hm^-2和12.35%;（3）小麦估产模型在各生育时期的预测精度表现为抽穗期>灌浆期>成熟期。     

冬小麦不同冠层叶片光合蒸腾和水分利用效率变化特征及对灌溉的响应

为了解冬小麦不同冠层叶片光合和蒸腾作用特征以及随水分条件的变化规律,通过田间试验,以冬小麦京冬22为试验材料,设置0 mm（T₀）、220 mm（T₁）、280 mm（T₂）3种水分处理,比较分析了冬小麦不同冠层叶片净光合速率、蒸腾速率及水分利用效率对光合有效辐射和灌溉响应的差异。结果表明,三种水分处理下,冬小麦不同冠层叶片的蒸腾速率和光合速率随光合有效辐射的增加而增加,随后趋于平缓。不同冠层叶片蒸腾速率、光合速率对光合有效辐射的响应表现为上层>中层>下层;不同冠层叶片WUE对光合有效辐射的响应表现为上中层>下层。光合有效辐射相同时,灌水处理（T₁和T₂）的叶片光合蒸腾速率均高于不灌水处理（T₀）。T₁、T₂处理下,叶片光合速率对光合有效辐射响应在整个生育期内表现为灌浆期>抽穗期>成熟期>拔节期,蒸腾速率对光合有效辐射响应在整个生育期内表现为抽穗期>灌浆期>拔节期>成熟期;T₀处理下,叶片光合速率对光合有效辐射响应在整个生育期内表现为灌浆期>拔节期>抽穗期>成熟期,蒸腾速率对光合有效辐射响应在冬小麦整个生育期内表现不显著。因此,在进行小麦叶片到单株光合蒸腾尺度拓展估算时,应考虑冠层位置和水分条件对拓展结果的影响。     

多光谱与热红外数据融合在冬小麦产量估测中的应用

为了解多光谱与热红外数据融合对冬小麦产量估测精度的影响,以30个黄淮麦区冬小麦品种为材料,利用三种灌溉处理（处理1、处理2和处理3灌水量分别为240、190和145 mm）下冬小麦拔节期、挑旗期、抽穗期与灌浆期的无人机多光谱和热红外动态数据,构造了多个光谱指数,以支持向量机构建冬小麦产量估测模型,并验证其精度。结果表明,植被指数与籽粒产量的相关性受溉水量影响,处理1下植被指数与籽粒产量均呈正相关,处理2下植被指数除土壤调整植被指数（SAVI）和转化叶绿素吸收反射指数（TCARI）外均与籽粒产量呈正相关,处理3下植被指数与籽粒产量均呈负相关。通过多光谱和热红外数据融合构建的冬小麦产量估测模型的预测精度比仅使用多光谱数据构建的模型提高8%。不同灌溉条件下,通过多光谱与热红外数据融合构建的模型的预测精度存在差异,在处理1、处理2和处理3下拔节期、挑旗期、抽穗期和灌浆期验证决定系数（R）最高值分别为0.63、0.68和0.56,均方根误差（RMSE）最低值分别为0.60、0.24和0.41 t·hm^-2,且在三种灌溉条件下灌浆期预测效果均最佳。因此,利用无人机光谱对小麦品种产量估测时应将多光谱与热红外数据融合,用支持向量机（SVM）算法构建产量估测模型,且模型在灌浆期具有较高预测  精度。     

关中冬小麦叶片氮素含量高光谱遥感监测模型

为给黄土高原大范围的冬小麦氮素营养遥感监测提供理论依据,通过田间试验,研究了冬小麦叶片氮素含量遥感监测的最佳生育时期、最敏感波段及其他最优光谱参量。结果表明,灌浆期是利用高光谱遥感监测冬小麦叶片氮素营养状况的最佳生育时期;在拔节、抽穗和灌浆期680nm波段光谱反射率R680均能较好地反映冬小麦叶片氮素含量,基于光谱位置以及叶面积指数的光谱参量也能较好地反映冬小麦叶片氮素含量。拔节期、抽穗期和灌浆期分别以680nm波段光谱反射率R680、绿峰反射率Rg和植被指数(SDr-SDb)/(SDr+SDb)对小麦叶片氮素含量的拟合效果最佳,其回归方程分别为Y=27.54-280.247 X+1456.245 X2、Y=8.632 X-0.24和Y=25.83 X1.012。     

基于机器学习的春小麦叶片水分含量高光谱估算

为了比较不同机器学习算法在干旱半干旱区春小麦叶片水分含量（leaf water content,LWC）遥感监测中的应用效果及筛选最佳波段组合,在田间尺度上,以春小麦冠层高光谱数据为基础,采用两波段组合形式,计算15种光谱参数（比值植被指数RVI、归一化植被指数NDVI、差值植被指数DVI和12种水分植被指数）,通过对抽穗期叶片含水量与光谱参数拟合效果进行对比与分析,分别构建了基于机器学习［人工神经网络（artificial neural network,ANN）、K近邻(K-nearest neighbors,KNN)和支持向量回归(support vector regression,SVR）］和光谱参数的春小麦LWC反演模型,并对模型精度进行验证,以确定有效波段组合。结果表明,小麦抽穗期LWC与冠层高光谱反射率（R_784～950）、12种水分植被指数均显著相关（P＜0.01）;波段组合形式有效地优化了两波段指数的波段组合,在800～1 000 nm区间光谱参数（RVI_1046,1057、NDVI_1272,1279、DVI_1272,1279）的波段组合计算明显提升了其对LWC的敏感性;在不同的机器学习算法中,基于两波段组合光谱参数的KNN算法所见模型对LWC的预测效果（r=0.64,RMSE=2.35,RPD=2.01）优于ANN、SVR两种算法。这说明两波段光谱指数和KNN算法在春小麦叶片水分含量的高光谱遥感估算中具有一定的优势。     

综合近红外-红波段-短波红外三波段光谱特征空间的小麦冠层含水量反演

为提高返青期-拔节期-开花期-灌浆期不同覆盖条件下小麦冠层含水量的遥感反演精度，综合分析基于Nir-Red和Nir-Swir光谱特征空间开展作物含水量监测的优势与局限，利用垂直干旱指数（perpendicular drought index，PDI）和短波红外垂直失水指数（shortwave infrared perpendicular water stress index，SPSI）的比值形式，构建了一种基于近红外-红波段-短波红外（Nir-Red-Swir）三波段光谱特征空间的垂直植被水分指数（three-band perpendicular vegetation water index，TPVWI）。结果表明，在不同生育时期，TPVWI与小麦冠层含水量（vegetation water content，VWC)均具有显著相关关系（P<0.01），且对植被含水量的敏感性优于PDI、作物水分监测指数（plant water index，PWI）、SPSI和NDVI 4种植被指数，且在反映小区域内小麦冠层含水量的时空趋势上有较好的表征能力。对比地面实测数据，利用TPVWI建立的作物含水量估测模型的预测精度较高，r与RMSE分别为0.763和2.296%，说明利用综合Nir-Red-Swir三波段光谱空间特征的植被水分指数在监测不同覆盖条件下的作物含水量具有一定的可行性，可丰富当前作物冠层含水量遥感监测的理论方法。     

生物炭还田方式对冬小麦籽粒灌浆特性及产量的影响

为探明生物炭不同还田方式对冬小麦产量形成的影响,选用扬麦13为材料,研究了旋耕生物炭不还田（CK）、生物炭旋耕还田（XG）、常规翻耕还田（FG）和深翻还田（SFG）对冬小麦产量、干物质转运和籽粒灌浆特征的影响。结果表明,与CK相比,XG、FG和SFG处理显著增加冬小麦开花期、成熟期地上干物质积累量,促进花后干物质向籽粒转运,其中XG处理花后干物质对籽粒产量的贡献率比CK提高4.97%,二者间差异显著,而FG、SFG处理与CK间无显著差异;XG、FG和SFG处理对冬小麦强、弱势粒灌浆起始势和灌浆活跃期无显著影响,但可提高冬小麦强、弱势粒快增期灌浆速率和最大灌浆速率（V_max）,缩短到达最大灌浆速率的时间（T_max）,以XG处理效果最明显,其强、弱势粒V_max分别比CK提高16.41%、6.49%, T_max减少6.69%、12.97%,差异均显著;XG、FG和SFG处理能优化产量构成,其中XG处理有效穗数、千粒重、穗粒数、产量最高,分别比CK提高3.63%、8.19%、17.01%、14.27%,差异均显著。因此,在小麦-玉米轮作雨养无灌溉条件下,玉米秸秆生物炭旋耕还田可促进小麦干物质积累及花后干物质向籽粒的转运,提高强、弱势粒灌浆速率,增加冬小麦产量。     

基于遥感信息和WOFOST模型参数同化的冬小麦单产估算方法研究

为探讨遥感信息和作物生长模型在作物估产方面的优势互补特性,选取河北省藁城市冬小麦作为研究对象,采集多个关键生育时期的生理生化、农田环境、气象等数据,并获取准同步的环境减灾小卫星HJ-CCD影像数据,采用植被指数反演冬小麦叶面积指数（LAI）,基于扩展傅里叶振幅灵敏度检验法(EFAST)对WOFOST作物模型的26个初始参数进行全局敏感性分析,筛选敏感性参数,调整WOFOST模型的核心参数,利用查找表优化算法构建基于WOFOST模型和遥感LAI数据同化的区域尺度冬小麦单产预测模型,并定量预测区域冬小麦单产水平。结果表明,增强型植被指数（EVI）是遥感反演LAI的最佳植被指数(开花期建模r=0.913,RMSE=0.410,灌浆期建模r=0.798,RMSE=0.470),预测能力最强(开花期r=0.858,RMSE=0.531,灌浆期r=0.861,RMSE=0.428);筛选出6个待优化参数,即TSUM1、SLATB1、SLATB2、SPAN、EFFTB3和TMPF4;产量预测精度r=0.914,RMSE=253.67 kg·hm_-2,找到了待优化参数的最佳取值,最终完成了单产模拟。     

Mineral composition of some traditional Mexican teas

Teas of plant origin traditionally consumed by the Mountain Pima of Chihuahua, Mexico, were analyzed for mineral nutritional content. Fe, Cu, Zn, Ca, and Mg composition was determined for native teas made from shoots ofTagetes lucida, T. filifolia, Elytraria imbricata, andHolodiscus dumosus, and from root xylem ofCeanothus depressus andPhaseolus ritensis. Native uses of these teas are also described.     

Studies on natural repellents against potato tuber moth (Phthorimaea operculella Zeller) in country stores

Summary The effects of the leaves of five plant species, one from each of the generaAmbrosia, Anemone, Eupatorium, Eucalyptus andLantana, on potato tuber moth were investigated under indigenous storage conditions at the Central Potato Research Station, Shillong (1800 m above sea level). Their action was compared with that of a biological insecticide (spores ofBacillus thuringiensis), a chemical insecticide (carbaryl), and an untreated control. The data collected after six months storage on tuber damage, sprout damage and the rotting indicated that the leaves ofLantana aculeata provided most protection to the tubers, reducing damage from over 70% in the check to below 5%, and sprout damage from over 45% to below 3%. Next best wasEucalyptus globulus followed byB. thuringiensis. They may be used on tubers stored for table use or for seed as they had no adverse effect on germination or on the yield of a subsequent crop.     

Comparative Assessment of the Efficacy of Various Nitrogen Fertilizers

Summary

The efficiency of N fertilizers is usually poor; often less than 50% of the applied N is taken up by the crop. This review focuses on various N fertilizers with respect to the significance of different N loss pathways, namely (i) ammonia volatilization, (ii) dinitrogen and nitrogen oxide emissions, and (iii) nitrate leaching. Further, the significance of biological N immobilization, ammonium fixation and, finally, the impact of nitrate vs. ammonium uptake on crop yield are also discussed. The reviewed literature shows that N fertilizers may differ markedly in their susceptibility to losses. There is, however, considerable scope to improve N efficiency of each N source by proper N management practices.     

Redox Status and Neuro Inflammation Indexes in Cerebellum and Motor Cortex of Wistar Rats Supplemented with Natural Sources of Omega-3 Fatty Acids and Astaxanthin: Fish Oil,Krill Oil,and Algal Biomass

Health authorities worldwide have consistently recommended the regular consumption of marine fishes and seafood to preserve memory, sustain cognitive functions, and prevent neurodegenerative processes in humans. Shrimp, crabs, lobster, and salmon are of particular interest in the human diet due to their substantial provision of omega-3 fatty acids (n-3/PUFAs) and the antioxidant carotenoid astaxanthin (ASTA). However, the optimal ratio between these nutraceuticals in natural sources is apparently the key factor for maximum protection against most neuro-motor disorders. Therefore, we aimed here to investigate the effects of a long-term supplementation with (n-3)/PUFAs-rich fish oil, ASTA-rich algal biomass, the combination of them, or krill oil (a natural combination of both nutrients) on baseline redox balance and neuro-inflammation indexes in cerebellum and motor cortex of Wistar rats. Significant changes in redox metabolism were only observed upon ASTA supplementation, which reinforce its antioxidant properties with a putative mitochondrial-centered action in rat brain. Krill oil imposed mild astrocyte activation in motor cortex of Wistar rats, although no redox or inflammatory index was concomitantly altered. In summary, there is no experimental evidence that krill oil, fish oil, oralgal biomass (minor variation), drastically change the baseline oxidative conditions or the neuro-inflammatory scenario in neuromotor-associated rat brain regions.     

Potential of dry fractionation of wheat bran for the development of food ingredients,part II: Electrostatic separation of particles

Wheat bran is a composite material made of several layers, such as pericarp, testa and aleurone. It could be fractionated into purified fractions, which might either be used as food ingredients, or serve as a starting material for extraction of bioactive compounds. The aim of this work was to evaluate the potential of using electrostatic separation as a way to obtain purified fractions from wheat bran. Ultrafine-ground bran obtained either by cryogenic grinding or by grinding at ambient temperature was used as starting material. The ultrafine bran was then charged by tribo-electrification and introduced in a chamber containing two high voltage electrodes, where bran particles were separated depending on their acquired charge, allowing positively and negatively charged fractions to be collected separately. The particle size distribution, microstructure and biochemical composition of the obtained fractions were studied. The charge of the particles was influenced by their biochemical composition: particles rich in highly branched and cross-linked arabinoxylans (pericarp) were separated from particles rich in β-glucan, ferulic acid and para-coumaric acid (aleurone cell walls). The testa and the intracellular compounds from aleurone were not highly charged, neither positively nor negatively. The most positively charged fraction represented 34% of the initial bran, and contained 62% of the ferulic acid present in the initial bran. The yield of the separation process was good (5.4% loss), and could be further increased.     

In vitro antimicrobial activity of different accessions ofSolanum commersonii Dun. from Uruguay

Summary The in vitro antimicrobial activity of extracts from accessions ofSolanum commersonii Dun. collected in the south of Uruguay was investigated against five microorganisms including the pathogenRalstonia solanacearum. A total of 30 extracts corresponding to organic and aqueous extracts were studied. Interestingly, most of the positive results for growth inhibition were againstR. solanacearum. The extracts were also analyzed for the presence of glycoalkaloids and lectins. Six of the ten aqueous extracts showed lectin presence and a wide variation in the type and amounts of glycoalkaloids, was found. Results indicate that there is no clear relationship between the antimicrobial activity against the five microorganisms screened and the presence or amounts of lectins and glycoalkaloids, traditionally regarded as possible antimicrobial metabolites in theSolanum genus, which indicates the presence of as yet unidentified antimicrobial compounds.     

Novel food and non-food uses for sorghum and millets

Sorghum and millets have considerable potential in foods and beverages. As they are gluten-free they are suitable for coeliacs. Sorghum is also a potentially important source of nutraceuticals such antioxidant phenolics and cholesterol-lowering waxes. Cakes, cookies, pasta, a parboiled rice-like product and snack foods have been successfully produced from sorghum and, in some cases, millets. Wheat-free sorghum or millet bread remains the main challenge. Additives such as native and pre-gelatinised starches, hydrocolloids, fat, egg and rye pentosans improve bread quality. However, specific volumes are lower than those for wheat bread or gluten-free breads based on pure starches, and in many cases, breads tend to stale faster. Lager and stout beers with sorghum are brewed commercially. Sorghum's high-starch gelatinisation temperature and low beta-amylase activity remain problems with regard to complete substitution of barley malt with sorghum malt . The role of the sorghum endosperm matrix protein and cell wall components in limiting extract is a research focus. Brewing with millets is still at an experimental stage. Sorghum could be important for bioethanol and other bio-industrial products. Bioethanol research has focused on improving the economics of the process through cultivar selection, method development for low-quality grain and pre-processing to recover valuable by-products. Potential by-products such as the kafirin prolamin proteins and the pericarp wax have potential as bioplastic films and coatings for foods, primarily due to their hydrophobicity.     

<Emphasis Type="Italic">Pulque</Emphasis>, An Alcoholic Drink from Rural Mexico,Contains Phytase. Its <Emphasis Type="Italic">in vitro</Emphasis> Effects on Corn Tortilla

Pulque is made by fermenting the agave sap or aguamiel of Agave atrovirens with a whole array of microorganisms present in the environment including several lactic acid bacteria and yeasts such as Saccharomyces cerevisiae. Ascorbic acid was determined in pulque and aguamiel, respectively. Phytase activity in lees, liquid and freeze-dried pulque was assayed by measuring the appearance of phosphate from phytate by a colorimetric method likewise phosphate from phytate present in fresh corn tortilla was measured after in vitro incubation with pulque. Iron, zinc, calcium, magnesium and selenium contents were measured in pulque and corn tortilla as well as in nixtamalized corn flour (NCF), the latter is used to make instant tortilla, since corn provides most of the energy as well as most of the phytate in the Mexican rural diet. Pulque showed phytase activity but much less ascorbic acid and iron than previously reported; additionally, phytase in pulque hydrolyzed most of phytate’s corn tortilla. Lees, which is mostly made of pulque’s microbiota, significantly accumulated iron and zinc but no selenium. NCF was fortified with iron by the manufacturers but poorly blended. There were significant differences on selenium content between tortillas samples, apparently some soils in central Mexico are selenium deficient. Moderate pulque intake appears to increase the bioavailability of iron and zinc bound by phytate in corn.