春小麦蛋白质、脂肪、淀粉含量间的相关与回归分析

本文通过对20个春小麦品种(或品系)蛋白质、脂肪、淀粉百分含量间的相关、回归、协方差分析,表明蛋白质百分含量与淀粉百分含量间为极显著的负相关;脂肪百分含量与淀粉百分含量间为极显著的负相关;蛋白质百分含量与脂肪百分含量间为极显著的正相关。并建立了淀粉、脂肪、蛋白质百分含量间的回归方程。在同一试验条件下,各品种(或品系)蛋白质、脂肪、淀粉百分含量变异系数的大小,在一定程度上反映出各品种在品质性状上的纯合程度。变异系数愈小,表明纯合程度愈高;变异系数愈大,表明纯合程度愈低。因此,在那些变异系数较大的品种(或品系)中,可选出表型性状与原品种(或品系)基本相似,而在品质性状上却有较大提高的优质新品系。     

Yield Stability of Winter Wheat (Triticum sp.) Cultivars and Lines

The purpose of this study was to compare responsiveness to environment as well as the stability of newly developed promising lines with traditional commercial cultivars. Subject research was conducted in Ankara between 1983-1989 on common and durum wheat cultivars and lines. Regression coefficient (b) was used as the criterion of genotypes' responsiveness to environment whereas deviation from regression (S²d) and coefficient of determination (r²) were used as stability parameters. Each experiment year was regarded as an environment and yield average of each year was used as the environmental index.
In consequence of the research, it was determined that new varieties with high yield, adaptable to diverse environments could be developed by means of hybridizations between parents having different genetic characteristics which were provided from diverse ecological regions.     

推求合理畦宽的方法及应用

为了寻求合理的节水省时畦宽,以更好地利用现有水源,在1990、1991年试验和实践的基础上,用统计回归分析方法对大城县农田畦田规格进行了分析,求出了合理畦宽,并从灌水持续时间、用电量、提水量等方面对合理畦宽的节水、节能效果进行了分析。     

黄淮夏大豆主要农艺性状的遗传分析

利用黄淮地区的12个高产夏大豆品种(系),通过NCⅡ交配设计,对12个主要农艺性状的遗传进行了分析。结果表明,所有性状的加性方差大于显性方差。主茎节数、株高、每簇荚数和主茎荚数的加性成分占绝对优势,遗传力较高。分枝荚数、单株粒数和单株粒重的显性成分比例大,遗传力较低,其中单株粒重趋于完全显性。主茎节数的显性成分很少,其它性状均为部分显性。建立了单株产量与产量因子之间的逐步回归方程。     

楸树自然变异与良种选择

对楸树中７种与生长相关的变异因子进行了数量化分析，得出树高、胸径、单株立木材积的主要因子与生长的相关关系，并建立了线性回归方程。提出了良种这样及早期测定的形质性状标准。     

东方蝾螈外部体型指数回归方程的建立

为了探讨东方蝾螈在人工养殖效果评估方面 ,在确定屠宰或捕捞的大小与时间的适宜度方面 ,在生理、病理分析时 ,在治疗时间和用药量等诸方面 ,都达到取材时期的合理性问题 ,测定了东方蝾螈的身型指数 ,并初步建立了回归方程Y =- 2 5 0 +0 .6 2X1 ,并对相关数据的处理方法进行了探讨。     

巨桉纸浆原料林土壤养分与林木生长研究

通过相关分析及回归分析，探讨了巨桉人工林土壤养分与林木生长的关系，结果表明：土壤速效N、速效P、土壤有机质的浓度与林木胸径、树高、材积极显著正相关，土壤全N、全P与林木胸径树高、材积显著正相关。建立了胸径、树高、材积与土壤养分的线形回归方程，最佳数学表达式说明速效N、速效P是影响巨桉林生长的关键土壤养分。     

Biological and Physical Constraints on Maize Production in the Humid Forest and Western Highlands of Cameroon

The aim was to identify biological and physical factors responsible for reducing maize yield in Cameroon. Two surveys were conducted in 137 fields in two agroecological zones in 1995–1997. In the Humid Forest (HF), Bipolaris maydis, Stenocarpella macrospora, Puccinia polysora, Rhizoctonia solani and soil fertility were factors that reduced maize production in 1995 and 1996. In the Western Highlands (WHL), Cercospora zeae-maydis, and the interaction between soil fertility and maize variety were the most important constraints to maize production in 1996. In 1997, C. zeae-maydis, S. macrospora, physiological spot and stem borer damage (Busseola fusca) were negatively related to ear weight. The combination of these biological factors (diseases and insects), and the physical parameter of soil fertility were responsible for reducing maize yield in these selected benchmarks of Cameroon. Maximum potential yield reductions were estimated at 68% due to B. maydis and 46% due to S. macrospora, respectively, in the HF in 1995. In 1996, maximum potential yield reductions in the HF were estimated at 34%, 41% and 30% due to S. macrospora, P. polysora and R. solani, respectively. In the WHL, C. zeae-maydis had the potential to cause a yield reduction of 79% in 1996. In the WHL in 1997, the interaction between C. zeae-maydis and B. fusca, stem diseases and the physiological spot caused potential reductions of 52%, 34% and 39%, respectively.     

基于高光谱特征参数的冬小麦氮营养指数估算

为了实现快速高精度获取冬小麦氮营养指数的高光谱监测技术，利用美国SVC HR-1024I型野外光谱辐射仪对2017-2019年关中地区的冬小麦进行遥感监测，获取“三边”参数、任意两波段光谱指数和植被指数，通过相关性分析和逐步回归分析方法筛选冬小麦氮营养指数的敏感光谱参数，结合偏最小二乘回归(PLSR)、随机森林算法(RFR)、支持向量机回归(SVR)和梯度增强回归(GBDT)建立冬小麦氮营养指数模型，并对模型估算精度进行验证。结果表明，从拔节期到灌浆期，各时期的氮营养指数与任意两波段光谱指数均呈极显著相关，其中拔节期氮营养指数与任意两波段光谱指数相关性均高于其他时期，且基于一阶导数光谱的归一化光谱指数和比值光谱指数与氮营养指数的相关系数最大，为0.66。拔节期基于梯度增强回归的冬小麦氮营养指数预测模型的决定系数(r²)和均方根误差(RMSE)分别为0.96和0.05,模型验证的r²、RMSE和相对预测偏差(RPD)分别为0.95、0.12和2.12,模型预测精度最高。因此，拔节期基于梯度增强回归的冬小麦氮营养指数估算模型可用于冬小麦氮营养监测...     

Enhancing pedotransfer functions with environmental data for estimating bulk density and effective cation exchange capacity in a data‐sparse situation

Soil bulk density (BD) and effective cation exchange capacity (ECEC) are among the most important soil properties required for crop growth and environmental management. This study aimed to explore the combination of soil and environmental data in developing pedotransfer functions (PTFs) for BD and ECEC. Multiple linear regression (MLR) and random forest model (RFM) were employed in developing PTFs using three different data sets: soil data (PTF‐1), environmental data (PTF‐2) and the combination of soil and environmental data (PTF‐3). In developing the PTFs, three depth increments were also considered: all depth, topsoil (<0.40 m) and subsoil (>0.40 m). Results showed that PTF‐3 (R²; 0.29–0.69) outperformed both PTF‐1 (R²; 0.11–0.18) and PTF‐2 (R²; 0.22–0.59) in BD estimation. However, for ECEC estimation, PTF‐3 (R²; 0.61–0.86) performed comparably as PTF‐1 (R²; 0.58–0.76) with both PTFs out‐performing PTF‐2 (R²; 0.30–0.71). Also, grouping of data into different soil depth increments improves the estimation of BD with PTFs (especially PTF‐2 and PTF‐3) performing better at subsoils than topsoils. Generally, the most important predictors of BD are sand, silt, elevation, rainfall, temperature for estimation at topsoil while EVI, elevation, temperature and clay are the most important BD predictors in the subsoil. Also, clay, sand, pH, rainfall and SOC are the most important predictors of ECEC in the topsoil while pH, sand, clay, temperature and rainfall are the most important predictors of ECEC in the subsoil. Findings are important for overcoming the challenges of building national soil databases for large‐scale modelling in most data‐sparse countries, especially in the sub‐Saharan Africa (SSA).