Estimation of litchi (Litchi chinensis Sonn.) leaf nitrogen content at different growth stages using canopy reflectance spectra

The estimation of crop nitrogen status in fresh vegetation leaf using field spectroscopy is challenging due to the weak responses on leaf/canopy reflectance and the overlapping with the absorption features of other compounds. Although the spectral indices were proposed in the literature to predict leaf nitrogen content (LNC), the performance of selected spectral indices to estimate the LNC is often inconsistent. Moreover, the models for nitrogen content estimation changed with the growth stage. The goal of this study was to evaluate the performance of published indices, ratio of data difference index (RDDI) and ratio of data index (RDI) developed by band iterative-optimization algorithm in LNC estimation. The correlation analysis, linear regression and cross validation were used to analyze the relationship between spectral data and LNC and construct the best performed estimation model. The study was conducted by the data of five growing seasons of litchi from the orchards in Guangdong Province of China. Results showed that the relationship between chlorophyll (Chl) related spectral indices and LNC varied with the growth stage. Even in flower bud morphological differentiation stage and autumn shoot maturation stage, there were not significant correlations between the proposed spectral indices and LNC. Besides it is difficult to estimate the LNC by the general model across the growth stages due to the integrated effects of cultivar, biochemical, canopy structure, etc. The band iterative-optimization algorithm can improve the sensitivity of spectral data to LNC to some extent. The optimal RDDI performed better than other indices for the synthetic dataset and the dataset in each growth stage. And the sensitive bands selected in the optimal indices at each growth stage are not consistent, which are not only related to the Chl absorption but also other biochemical components, such as starch, lignin, cellulose, protein, etc. In general, the LNC can be estimated by the optimized CR-based RDDI indices in autumn shoot maturation stage, flower spike stage, fruit maturation stage, and flowering stage with the R² > 0.50 and RMSE < 0.14. Although there were the significant relationship between RDIs and RDDIs in flower bud morphological differentiation stage, the highest R²s of the model developed by RDDIs and RDIs were less than 0.50 in cross validation. This study indicated that the applicability of canopy reflectance to estimate litchi LNC was closely related to the growth stage of litchi. Growth stage-specific models will be preferred for estimating litchi LNC estimation.     

橄榄基因组AFLP扩增体系的优化

为建立适于橄榄研究用的AFLP技术体系,以10个橄榄品种为材料,对其基因组DNA从酶切、连接、预扩增和选择性扩增等方面进行条件优化。研究结果表明,DNA模板用量为500 ng,酶切体系中限制性内切酶EcoRⅠ和MseⅠ各加入3 U,37℃水浴4 h;连接体系中T4DNA连接酶加入1.5 U,16℃连接6 h;并利用优化后的预扩增体系和选择性扩增体系筛选出6对适合于橄榄AFLP分析的引物组合:E/AAC-M/CAT、E/AAC-M/CTT、E/ACA-M/CAA、E/AGG-M/CAA、E/ACC-M/CAA、E/ACT-M/CAT。采用该体系得到的电泳条带清晰可靠、多态性好,可用于对橄榄遗传多样性的研究。     

利用多种分子标记构建龙眼高密度分子遗传图谱

 以龙眼特优质品种‘凤梨朵’为母本, 大果型主栽品种‘大乌圆’为父本, 杂交创建了‘凤梨朵’ ב大乌圆’F₁群体。从该杂种群体中随机选用94个单株作为作图群体, 连同两个亲本品种, 进行了RAPD、ISSR、SRAP和AFLP分子标记分析, 并运用JoinMap3.0进行连锁分析, 分别构建了‘凤梨朵’和‘大乌圆’的分子遗传图谱, 其中, ‘凤梨朵’的遗传图谱为21个连锁群, 包含183个标记位点,覆盖总图距965.1 cM, 位点间平均遗传距离为5.84 cM; ‘大乌圆’的遗传图谱为22个连锁群, 包含251个标记位点, 覆盖总图距1 064.8 cM, 位点间平均遗传距离为4.65 cM。这是龙眼上首次报道的高密度分子遗传图谱, 为后续的基因定位及辅助选择奠定了良好的基础。     

广东鲜食橄榄果实质构特性比较

为比较分析广东省主要鲜食橄榄果实质构特性的差异,探讨鲜食橄榄果实质地评价的量化参数,验证感官评价质地的有效性。采用质构刺穿试验法对7个优质鲜食橄榄品种果肉质构参数和2种水肥管理方式不同成熟期的‘香甜榄’果实品质进行测定和比较分析。结果表明,不同品种之间果肉的各质构参数变异系数为12.57%~23.95%,差异性显著,与感官评价一致;果皮强度与果皮脆性和果皮韧性均呈显著正相关,果皮破裂深度与果肉硬度呈显著负相关。采用本次试验栽培管理方式可以提高橄榄完熟果实可溶性固形物6%、可滴定酸3.5%、单宁54.9%、果皮强度12.7%、果皮脆性23.5%,降低粗纤维10%、果皮韧性13.7%。果实质地品质参数主成分分析表明,果皮强度、果实硬度和纤维指数可作为质地参数量化区分不同品种间的差别,并明确果皮强度、果实硬度分别小于2300、1600 g和纤维指数大于10,为鲜食橄榄果肉质地品质较好的数值范围。研究初步建立了利用质构刺穿试验法量化评价鲜食橄榄果实质地品质的方法。     

荔枝蒂蛀虫在荔枝果期的预测预报方法

通过采用分级、田间调查和室内饲养,掌握荔枝蒂蛀虫发育动态,能准确预测预报成虫的羽化及卵孵化高峰期,结合药物防治,把蒂蛀虫为害率控制在5%以下.