基于无人机影像的冠层光谱和结构特征监测甜菜长势

甜菜是中国北方地区重要的经济作物。快速、准确、高通量的获取甜菜的地上部和块根鲜质量、块根含糖率、叶绿素含量对甜菜生产具有重要意义。该研究采用无人机搭载数码和多光谱相机,获取甜菜叶丛快速生长期、块根及糖分增长期和糖分积累期的数码影像和多光谱影像,提取了冠层的结构特征和光谱特征。选择随机森林回归（Random Forest Regression,RFR）和偏最小二乘回归（Partial Least Squares Regression,PLSR）2种建模方法基于获取的冠层特征,构建甜菜全生育期的地上部和块根鲜质量、块根含糖率和SPAD（Soil and Plant Analyzer Development）值估算模型。研究结果表明,随机森林回归模型和偏最小二乘回归模型对地上部和块根鲜质量、含糖率都做出较好的预测,R2范围分别为0.9～0.94、0.88～0.9,rRMSE范围分别为7.6%～17%、8.8%～20%。对SPAD值的预测均较弱,R2分别为0.66和0.67。为了减小输入变量集的大小以及去掉对预测不敏感的变量,该研究采用置换重要性（Permutation Importance,PIMP）来筛选冠层光谱特征和结构特征中对预测有重要影响的变量。结果表明基于筛选出的重要性特征构建的随机森林回归模型和偏最小二乘回归模型对地上部和块根鲜质量、含糖率都做出较好的预测,R2范围分别为0.89～0.94、0.74～0.91,rRMSE范围分别为7.3%～19%、7.6%～19%。对SPAD值的预测均较弱,R2分别为0.65和0.68。进一步表明随机森林回归模型在精度上略好于偏最小二乘回归模型。同时基于PIMP筛选变量的方法在保持原有精度的同时能实现降低数据收集复杂性的目的。研究结果为基于无人机遥感技术快速、准确监测甜菜长势和估测块根类作物的根部活性物质提供了参考。     

Soil water-retention prediction from pedotransfer functions for some Indian soils

This paper discusses the development of pedotransfer functions (PTFs) and uses a multiple nonlinear regression technique to validate point and parametric PTFs for the estimation of a water-retention curve from basic soil properties such as particle-size distribution, bulk density and organic matter content. One hundred soil samples were collected at different depths from different locations in the Pavanje river basin that lies within the southern coastal region of Karnataka, India. Prediction accuracies were evaluated using the coefficient of determination (R ²), root mean square error (RMSE) and mean error (ME) between measured and predicted values. Overall, both point and parametric methods predicted water contents at selected water potentials with considerable accuracy. However, prediction of the soil water-retention curve using PTFs by point estimation method was relatively more successful (best case R ² = 0.983) for the sampled soils. F-tests were also conducted for all cases. For one regression equation, the p-value was zero and for other equation, values were close to zero. Critical comparative analysis was carried out on the performances of the point and parametric methods. Use of the developed PTFs is suggested for the prediction of a water-retention curve for loamy sand and sandy loam soils in this area of the coastal region of southern India.     

近红外光谱结合偏最小二乘法快速评估土壤质量

以长江中下游粮食主产区水稻土为研究对象,采集17种不同施肥处理下共136个土壤样品在350 ～2 500 nm范围的近红外光谱,利用偏最小二乘回归分析结合交叉验证法建立了近红外漫反射光谱与传统化学分析方法测得的全碳、全氮、碳氮比、速效钾、速效磷、电导率、土壤pH等土壤指标之间的定量分析模型。模型的决定系数（R2）以及化学分析值标准差（SD）与模型的内部交叉验证均方差（RMSECV）的比值RSC用于判定建立的模型的好坏。结果表明：全碳、全氮、碳氮比和pH模型的R2和RSC分别为：R2=0.94,RSC=4.31;R2=0.95,RSC=4.35;R2=0.97,RSC=5.60;R2=0.92,RSC=3.37,说明上述土壤指标的预测结果很好。速效钾模型的R2和RSC分别为：R2=0.87,RSC=2.23,表明预测结果尚好。而速效磷和电导率模型的R2和RSC分别为：R2=0.18,RSC=1.16;R2=0.37,RSC=1.31,说明两者的预测结果均很不理想。综上所述,水稻土的土壤质量相关指标（全碳、全氮、碳氮比、速效钾和土壤pH）可以通过近红外光谱结合偏最小二乘法（NIR-PLS）快速评估。     

基于地理权重回归模型的土壤有机质空间预测

准确了解土壤有机质的空间分布是合理施肥的重要前提,也是水土流失控制及保护环境的重要基础。利用113个土壤有机质样点数据,以海拔高度、土壤侵蚀强度、土地利用、比值植被指数、样点至河流的欧氏距离、亚铁矿物指数及坡度为参考因子,来尝试利用GWR(Geographically Weighted Regression)模型探索多重因素作用下的土壤有机质空间分布,并通过与普通线性回归(ordinary least squares,OLS)相比较,来了解GWR模型的精度,进而进行了土壤有机质的空间制图,并对其制图效果进行了评价。结果表明,与OLS模型相比,GWR预测模型它能显著降低AIC(Akaike Information Criterion)值,较大程度地提高模型的决定系数,并有效地减少模型的回归残差值。从制图的总体效果看,GWR模型的预测结果与实测值的吻合程度要优于OLS模型。文章还对利用GWR模型进行回归时的样点数量、因子筛选及因子定量化等方面进行了相应的讨论。     

Studies on the humus forms of forest soils

Samples described in the previous paper were analyzed for humus composition by the method of Kumada el al,, elementary composition of humic acids, nitrogen distribution among humic acid, fulvic acid, and humin, and organic matter composition by the modified Waksman method. The samples obtained by physical fractionation from each horizon of Higashiyama soil were as follows: f₁ and f₂ from the L layer, f₁, f₂ and f₃ from the F layer, f₁ f₂, sand, silt, and clay fractions from the H-A and A horizons.

With the progress of decomposition, the following tendencies were rather clearly observed.

The extraction ratio of soluble humus, amounts of humic acid and fulvic acid, and PQ, value tended to increase with some exceptions. The degree of humification of humic acid proceeded. Most humic acids belonged to the Rp type, but those of the clay fractions belonged to the B type.

As for the elementary composition of humic acid, transitional changes from the Lf₁ to the clay fraction of the A horizon were observed. But differences in elementary composition among humic acids were far less, compared with those among whole fractions.

Nitrogen contents in humic, fulvic, and humin fractions increased with the progress of decomposition and humiliation, and the largest relative increase was found in fulvic acid nitrogen.

According to the modified Waksman's method, the amounts of residues and protein increased, while the total amounts of each extract, except for the HCl extract, and the amounts of sugars and starch, phenolic substances, hemicelluloses and pectin, and cellulose decreased. Sugars and starch comprised only a small portion of the hot water extract, and polyphenols substances comparable to sugars and starch were also found in the extract. Hemicelluloses and pectin accounted for only about one-half of the HCl extract. Several characteristic differences in the elementary composition of extracts and residues were found.

Pheopigments existed in benzene-ethanol extracts and their amounts seemed to decrease from Lf₁ to Ff₂.     

柑橘矢尖蚧发生期预测回归方程研究

矢尖蚧是危害柑橘生产的重要害虫之一,搞好测报可以指导适时防治。笔者在重庆市北碚区柑橘园对矢尖蚧进行多年系统监测,结果表明,矢尖蚧在该地一年发生3代,世代重叠,第1代发生较为整齐,便于统一防治。因此,以2012年-2018年该虫发生前3个月的气象资料和矢尖蚧发生的田间历史数据为依据,应用DPS软件,分别采用简单法和多因子互作法进行逐步回归,建立了春季矢尖蚧第1代发生期的预测回归方程。两个方程总体回归达显著水平或极显著水平,两种方法建立的回归方程证明:第1代发生高峰期与发生前3个月的温度、湿度、雨日和降雨量等气象资料均有关系。将2019年数据用来进行检验,结果表明两个回归方程结论均为“比较准确”,均能比较准确地预测出该地矢尖蚧的发生高峰期。     

Lessons from 10 years of stakeholder adoption of a soil bioassay for assessing the risk of spinach Fusarium wilt

Although the maritime Pacific Northwest (PNW) is the only region of the United States suitable climatically for spinach seed production, the acidic soils are highly conducive to spinach Fusarium wilt caused by Fusarium oxysporum f. sp. spinaciae. A soil bioassay developed to quantify the risk of spinach Fusarium wilt in fields has been offered to seed growers annually since 2010. Soil sampled from growers' fields each winter was planted with highly susceptible, moderately susceptible, and partially resistant spinach inbred lines, and the plants rated weekly to calculate a Fusarium wilt severity index (FWSI) and the area under the disease progress curve (AUDPC). Results for 147 soils tested from 2010 to 2013 have been published. This study examined results for an additional 248 soils tested from 2014 to 2019 with the bioassay modified to include an option of agricultural limestone amendment to the soils tested. FWSI and AUDPC were affected significantly (p < .001) by the main effects of soil and spinach inbred line, and the interaction of these factors. Correlation analyses showed a range in degree of association of FWSI and AUDPC with spinach seed crop rotation duration and soil properties, depending on the spinach inbred line (r = −.255 to –.267, n = 172 soils with characteristics suitable for correlation analyses). Stepwise regression models for 172 soils with relevant parameters for regression analyses identified spinach seed crop rotation interval, rate of agricultural limestone amendment, soil pH, and soil Fe, Mn, and Zn concentrations as most strongly associated with FWSI and AUDPC. However, the models accounted for ≤33.4% (R²) of the variability in Fusarium wilt risk. The soil bioassay remains a primary tool for spinach seed growers to select fields with low risk of Fusarium wilt.     

特用玉米模式化栽培试验研究

以影响黑糯玉米产量的氮肥、磷肥、密度等限制因子为自变量,进行通用回归旋转设计,以籽粒产量建立数学模型并分析,提出了黄土高原生产特种玉米的高产、高效栽培模式.分析得出黄土高原特种玉米产量和毛收益最佳组合为:施氮466.5 kg/hm2、施磷426.0 kg/hm2,密度为10.95万株/hm2时,最高单产可以达到11.175 t/hm2;施N 424.5 kg/hm2,P2O5 211.5 kg/hm2,保苗7.05株/hm2时,最高毛收益可达到1.236万元/hm2,经济效益显著.     

菠萝植株性状相关的通径分析

根据161株菲律宾品种菠萝植株的果实重量、果眼数、叶片数、叶片重和茎重等5个性状的观测数据,进行通径分析,获得关于这些性状的特征数、通径图、通径系数、决定系数;并对通径系数进行显著性检验,建立“最优”回归方程:y=242.292 2.5084x_1 8.3126x_2 0.3663x_3。它的复相关系数为R=0.9275。结果期的菠萝植株所具有的叶片重是影响果实重量的最重要性状。由于性状间均存在着显著的正相关,其他性状(x_1,x_2,x_4)对菠萝果实重量的间接影响也很大,必须同时兼顾。