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。     

水稻赖氨酸含量测定方法改进及其最优动态分类研究

赖氨酸是水稻营养成分中第一限制性氨基酸。为优化赖氨酸的测定方法,设置了本试验,通过超声振荡器取代普通振荡器,进行300W超声功率下酰化用时及染料结合反应用时的研究。结果表明,最佳酰化用时为15 min,染料结合用时为90 min。与国标法相比,优化后的方法酰化用时变长、染料结合用时变短,测定总用时明显缩短,但测定结果和试验精度更高。可见,采用超声波振荡代替传统振荡器振荡能改进赖氨酸的测定方法。另外,采用最优动态聚类法对赖氨酸含量进行分类,能防止人为分类的不确定性,做到分类方案的最优化。     

Comparison of estimators and feature selection procedures in forest inventory based on airborne laser scanning and digital aerial imagery

Digital maps of forest resources are a crucial factor in successful forestry applications. Since manual measurement of this data on large areas is infeasible, maps must be constructed using a sample field data set and a prediction model constructed from remote sensing materials, of which airborne laser scanning (ALS) data and aerial images are currently widely used in management planning inventories. ALS data is suitable for the prediction of variables related to the size and volume of trees, whereas optical imagery helps in improving distinction between tree species. We studied the prediction of forest attributes using field data from National Forest Inventory complemented with ad hoc field plots in combination with ALS and aerial imagery data in Aland province, Finland. We applied feature selection with genetic algorithm and greedy forward selection and compared multiple linear and nonlinear estimators. Maximally around 40 features from a total of 154 were required to achieve the best prediction performances. Tree height was predicted with normalized root mean squared error value of 0.1 and tree volume with a value around 0.25. Predicting the volumes of spruce and broadleaved trees was the most challenging due to small proportions of these tree species in the study area.     

四倍体马铃薯块茎蛋白含量分子标记的开发与验证

块茎蛋白含量是马铃薯的重要品质性状之一,相关分子标记的开发研究较少。本研究以马铃薯高蛋白品种大西洋、低蛋白品种定薯1号及包含173份子代的蛋白含量分离群体为材料,通过高通量简化基因组测序技术与集群分离分析(BSA)相结合,开发了SCAR8-107标记,并以此标记对分离群体的74份高蛋白、42份低蛋白子代及54个四倍体马铃薯品种验证表明,SCAR8-107标记在后代分离群体和四倍体马铃薯品种中的检测结果与表型蛋白含量的对应度分别达到了90.51%和72.97%,经过Pearson’s双侧相关性分析,相关性均达到了极显著水平。SCAR8-107的开发对于四倍体马铃薯块茎蛋白含量标记辅助选择与加速马铃薯品质育种具有重要意义。     

红茶感官品质及成分近红外光谱快速检测模型建立

以在发酵过程中小叶种工夫红茶为研究对象,分别建立了基于近红外光谱检测技术的感官品质评分和理化品质指标(茶黄素、茶红素、茶褐素、儿茶素和酚氨比)的定量分析模型。在模型建立过程中,探讨了特征变量优选方法对预测模型的影响。首先,对获取的近红外光谱数据进行标准正态变量变换法(standard normal Z transformation,SNV)预处理,进而采用联合区间偏最小二乘回归(synergy interval PLS,Si-PLS)、随机蛙跳算法(shuffled frog leaping algorithm,SFLA)、竞争性自适应权重取样法(competitiveadaptivereweightedsampling,CARS)和连续投影(successive projections algorithm,SPA),筛选出各品质指标的最优特征波长变量;最后基于优选波长分别建立各发酵品质指标的偏最小二乘法(partial least squares regression,PLS)线性预测模型和支持向量机(support vector regression,SVR)非线性预测模型。模型结果比较表明,Si、CARS、SFLA和SPA等变量筛选方法可有效压缩变量,以及进一步提高模型精度。非线性模型的预测均方根误差值(root-mean-square error of prediction,RMSEP)均明显小于PLS模型,相关性系数(correlation coefficient,R)和相对分析误差(relative percent deviation,RPD)均高于PLS模型。对于红茶发酵品质的检测上,非线性模型性能优于线性模型。感官品质、茶褐素和儿茶素的最优变量SVR预测模型的RPD值分别为3.923、3.234和5.462,酚氨比和茶红素模型的RPD值分别为2.815和2.223。除茶黄素的评价模型外(RPD为1.77),基于最优特征波长的各品质指标SVR模型的RPD值均大于2,表明模型具有极好的预测性能。研究结果为实现工夫红茶发酵品质的近红外光谱快速检测的实际应用奠定理论基础。     

Breeding for boron tolerance in lentil (Lens culinaris Medik.) using a high‐throughput phenotypic assay and molecular markers

This study describes the identification of a quantitative trait locus (QTL) in the recombinant inbred line population of ILL2024 × ILL6788 and subsequent validation of associated molecular markers. A high‐quality genetic linkage map was constructed with 758 markers that cover 1,057 cM, with an average intermarker distance of 2 cM. QTL analysis revealed a single genomic region on Lc2 to be associated with B tolerance and accounted for up to 76% of phenotypic variation (Vp). The best markers for B tolerance were assessed for their utility in routine breeding applications using validation panels of diverse lentil germplasm and breeding material derived from ILL2024. A marker generated from the dense genetic map of this study was found to be the most accurate of all markers available for B tolerance in lentil, with a success rate of 93% within a large breeding pool derived from ILL2024. However, given the number of the unrelated lines for which the marker–trait association was not conserved, B tolerance screening is still required at later stages to confirm predicted phenotypes.     

Identifying Soil and Plant Nutrition Factors Affecting Yield in Irrigated Mature Pistachio Orchards

The main objective of this study was to evaluate the potential use of a hybrid Genetic Algorithm-Artificial Neural Network (GA–ANN) method for predicting pistachio yield and for identifying the determinant factors affecting pistachio yield in Rafsanjan region, Iran. A total of 142 pistachio orchards were selected randomly and soil samples were taken at three depths. Besides, water samples and leaves from branches without fruit were taken in each sampling point. Management information and pistachio yields were achieved by completing a questionnaire. Primarily, 58 variables affecting pistachio yield were measured, and then 26 out of them were selected by minimizing mean square error (MSE) using a feature selection (FS) method. The results showed that the accuracy of the method was acceptable. Furthermore, the sensitivity analysis showed that the main determinant features affecting the pistachio yield were the irrigation water amount, leaf phosphorus, soil soluble magnesium, electrical conductivity (EC), and leaf nitrogen.     

Genomewide association analysis of salt tolerance in soybean [Glycine max (L.) Merr.]

Salinity is a common abiotic stress causing soybean [Glycine max (L.) Merr.] yield loss worldwide. The use of tolerant cultivars is an effective and economic approach to coping with this stress. Towards this, research is needed to identify salt‐tolerant germplasm and better understand the genetic and molecular basis of salt tolerance in soybean. The objectives of this study were to identify salt‐tolerant genotypes, to search for single‐nucleotide polymorphisms (SNPs) and QTLs associated with salt tolerance. A total of 192 diverse soybean lines and cultivars were screened for salt tolerance in the glasshouse based on visual leaf scorch scores after 15–18 days of 120 mM NaCl stress. These genotypes were further genotyped using the SoySNP50K iSelect BeadChip. Genomewide association mapping showed that 62 SNP markers representing six genomic regions on chromosomes (Chr.) 2, 3, 5, 6, 8 and 18, respectively, were significantly associated with salt tolerance (p < 0.001). A total of 52 SNP markers on Chr. 3 are mapped at or near the major salt tolerance QTL previously identified in S‐100 (Lee et al., 2014). Three SNPs on Chr. 18 map near the salt tolerance QTL previously identified in Nannong1138‐2 (Chen, Cui, Fu, Gai, & Yu, 2008). The other significant SNPs represent four putative minor QTLs for salt tolerance, newly identified in this study. The results above lay the foundation for fine mapping, cloning and molecular breeding for soybean salt tolerance.     

Challenges in organic component selection and biochar as an opportunity in potting substrates: a review

Plant production in potting substrates provides maximum profit on the applied inputs, and hence, directly improving the socio-economic condition of the grower/nurserymen. The main challenge in this industry is sourcing of materials for their potting substrates. Peat and perlite have been widely preferred materials. However, recently higher prices, more restrictive legislation of many countries and wetland ecosystem destruction through its extraction has limited peat use. Nowadays, producers focus towards peat alternatives that provide good performance, are readily available, inexpensive and environment friendly to attain sustainability in potted plant production. In an effort to grasp sustainability during the last few decades, many industrial and agricultural waste materials were reviewed for their use in potting substrates. In these studies, the major focus remained on material characterization, neglecting their economics, technical aspects and environmental impacts. Thus, switching from peat and perlite to alternatives requires material exploration. In the present review, we summarize a clearer and practical approach for substituting different materials especially biochar to fulfill the need of modern potting substrate industry. Biochar has the potential to sustain the substrate production on a long-term basis.     

草莓丝核菌根腐病病原菌鉴定及7种杀菌剂的抑菌作用测定

为了解草莓丝核菌根腐病的病原种类及筛选防治丝核菌根腐病的有效杀菌剂,本研究基于形态学特征、细胞核荧光染色、菌丝融合群测定以及rDNA-ITS的序列分析,对北京和河北承德地区的草莓丝核菌根腐病的病原菌进行了鉴定,并利用菌丝生长速率法测定了7种杀菌剂对丝核菌的抑菌作用。结果发现,北京地区的丝核菌为双核丝核菌(binucleate Rhizoctonia,BNR),属于融合群AG-A;河北的丝核菌为立枯丝核菌Rhizoctonia solani,属于融合群AG-4。氟啶胺、吡唑醚菌酯、噻呋酰胺、戊唑醇、咯菌腈、氟硅唑对2种丝核菌均有很强的抑制作用,EC_(50)值为0.063 9～2.485 7μg/mL,抑霉唑的抑制作用较差,EC_(50)值为9.966 8～11.236 8μg/mL。同一种杀菌剂对不同丝核菌的抑制作用存在差异,噻呋酰胺、戊唑醇、氟硅唑、咯菌腈和抑霉唑对立枯丝核菌的抑制作用强于对双核丝核菌。试验结果为生产上合理选用杀菌剂防治草莓丝核菌根腐病提供了科学依据。