水稻不同栽植密度下水稻生长情况对比

以下司镇某试验田为耕作对象,设计了不同栽植密度下水稻生长情况分析的试验对比。分析过程中,将每667m2产量作为衡量水稻生长情况的直接指标,得到了该镇水稻种植环境下最优的栽植密度,为该镇水稻种植密度的合理确定提供了有效的依据。

基于改进YOLO v5s的复杂环境下蔗梢分叉点识别与定位

甘蔗蔗梢分叉点的精确识别与高度定位是实现甘蔗收获机切梢器实时控制的关键技术之一,也是提高甘蔗收获机械化水平和降低甘蔗含杂率的重要途径。针对甘蔗地环境复杂、光照变化大、蔗梢分叉点相互遮挡等问题,首先通过田间调查,并现场测试、分析甘蔗生长点、甘蔗分叉点及相互关系的特征规律,采集图像的甘蔗分叉点的统计分析,并结合现场对甘蔗分叉点高度的测量统计分析,发现其均具有明显的正态统计特征。接着,提出了一种基于改进YOLO v5s的蔗梢分叉点识别方法。该方法采用单目和双目相机在广西大学扶绥农科基地采集甘蔗图像数据,并进行数据预处理和标注,构建了甘蔗蔗梢分叉点数据集。然后,在YOLO v5s中引入BiFPN特征融合结构和CA注意力机制,以增强不同层次特征的交互和表达能力,并使用GSConv卷积和Slim-Neck范式设计,在原始模型主干网络中引入Ghost模块替换原始普通卷积,来降低模型的计算量和参数量,提高模型的运行效率。最后,通过在现场采集的数据集上进行训练和测试,验证了该方法的有效性和优越性。实验结果表明,该方法在甘蔗蔗梢分叉点数据集上平均精确率达到92.3%、召回率89.3%和检测时间19.3 ms,相比原始YOLO v5s网络,平均精确率提高5个百分点,召回率提高4个百分点,参数量降低43%,模型内存占用量减少5.5 MB,检测时间减少0.7 ms。最后,根据甘蔗分叉点具有明显的正态统计特征的规律,利用该特征结合双目视觉的定位算法,可为开展甘蔗收获机切梢的特征识别、切梢器高度定位及实时控制研究奠定理论及技术基础。

Comparison of six statistical approaches in the selection of appropriate fish growth models

The performance of six statistical approaches,which can be used for selection of the best model to describe the growth of individual fish,was analyzed using simulated and real length-at-age data.The six approaches include coefficient of determination(R2),adjusted coefficient of determination(adj.-R2),root mean squared error(RMSE),Akaike's information criterion(AIC),bias correction of AIC(AICc) and Bayesian information criterion(BIC).The simulation data were generated by five growth models with different numbers of parameters.Four sets of real data were taken from the literature.The parameters in each of the five growth models were estimated using the maximum likelihood method under the assumption of the additive error structure for the data.The best supported model by the data was identified using each of the six approaches.The results show that R2 and RMSE have the same properties and perform worst.The sample size has an effect on the performance of adj.-R2,AIC,AICc and BIC.Adj.-R2 does better in small samples than in large samples.AIC is not suitable to use in small samples and tends to select more complex model when the sample size becomes large.AICc and BIC have best performance in small and large sample cases,respectively.Use of AICc or BIC is recommended for selection of fish growth model according to the size of the length-at-age data.

Study on Zymomonas Mobilis Growth and Its Relationship with Glutaminase Production by Using Statistical Tools

Glutaminase is used industrially to enhance flavor and aroma and to enrich foodstuffs nutritionally. It also has potential for pharmaceutical application as anti-leukemia agent. The bacteria of Zymomonas mobilis has been studied for ethanol production, however, there is no study regarding glutaminase production. The aim of the present study was to establish the influencing factors for the growth of Z mobilis and its relationship with glutaminase production using statistical tools. Analysis of variance in blocks was carried out in a complete block design and the Tukey test demonstrated the importance of the components of the culture medium, absence of agitation and fermentation time. Minimum culture medium was used in the optimization varying the glucose concentrations （10, 30, and 50 g/L）, glutamine （0, 0.5 and 1g/L） and culture time （18, 24 and 30 hours）. Maximum production was obtained at 8.86 U/L glutaminase. Optimized conditions were used in the growth kinetics, where typical exponential growth was observed. Glutaminase production was shown to be related to biomass production.

Projected Long-Term Behavior of the CO2 Emission Factor in the Electricity System of Uruguay

Estimating CO2 emission factor of the electricity system is a key aspect in the calculation of the baseline emissions for projects certified as CDM （Clean Development Mechanism）, which replace energy from the grid. Currently, Uruguay is driving the expansion of the electricity system based on domestic renewable energies, in addition to replacing oil-based fuels for others with lower emission factors. This implies a substantial change of the generation park in the next decade and of the associated CO2 emissions. In this paper, a calculation methodology of the baseline emissions is adapted for its incorporation in the software SimSEE （Electric Energy Systems Simulator）, which is used for modeling the Uruguayan electric system, and therefore, allows modeling the current energy generator park and the future one. Using this tool, the CO2 emission factor＇s evolution is evaluated in the 2012-2020 period. The 2020 scenario is based on an optimal expansion of the electric system. The results indicate a strong reduction of the emission factor between 2012 and 2020, going from average values （for 100 simulations） around 0.60 tCO2/MWh to 0.15 tCO2/MWh. In this possible future scenario, CDM certification will probably not act as a strong incentive in Uruguay for the development of projects based on non-traditional renewable energies.

吉林省春玉米生产潜力及其敏感性分析

基于"作物生长动态统计"模型计算吉林省春玉米光合生产潜力、光温生产潜力和气候生产潜力,运用敏感系数法计算并分析了生产潜力对全生育期平均气温和降水的敏感性。结果表明:春玉米光合生产潜力和光温生产潜力在吉林省由西向东呈递减趋势,中部的气候生产潜力最大,为17 266kg/hm^2,西部和东部分别为10 787、16 983kg/hm^2;西部、中部和东部生产潜力气温影响率分别为20.1%、19.5%和30.9%;生产潜力降水影响率分别为50.9%、17.6%和3.2%;西部和中部的气温敏感系数均值分别为1.77和1.99,西部最大为3.63;西部的降水敏感系数均值最大,为1.6,东部则形成了低值区。