scholarly journals Effects of Silicon on Photosynthetic Characteristics of Maize (Zea maysL.) on Alluvial Soil

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Zhiming Xie ◽  
Fengbin Song ◽  
Hongwen Xu ◽  
Hongbo Shao ◽  
Ri Song
Keyword(s):  
Photosynthetic Efficiency ◽  
Alluvial Soil ◽  
Optimal Dose ◽  
Photosynthetic Characteristics ◽  
Growth Stages ◽  
Total Chlorophyll ◽  
Chlorophyll Contents ◽  
Maize Leaves ◽  
Different Growth Stages ◽  
Photosynthetic Ability

The objectives of the study were to determine the effects of silicon on photosynthetic characteristics of maize on alluvial soil, including total chlorophyll contents, photosynthetic ratePn, stomatal conductancegs, transpiration rate (E), and intercellular CO2concentrationCiusing the method of field experiment, in which there were five levels (0, 45, 90, 150, and 225 kg·ha−1) of silicon supplying. The results showed that certain doses of silicon fertilizers can be used successfully in increasing the values of total chlorophyll contents,Pn, andgsand decreasing the values ofEandCiof maize leaves, which meant that photosynthetic efficiency of maize was significantly increased in different growth stages by proper doses of Si application on alluvial soil, and the optimal dose of Si application was 150 kg·ha−1. Our results indicated that silicon in proper amounts can be beneficial in increasing the photosynthetic ability of maize, which would be helpful for the grain yield and growth of maize.

scholarly journals Silicon Improves Maize Photosynthesis in Saline-Alkaline Soils

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Zhiming Xie ◽  
Ri Song ◽  
Hongbo Shao ◽  
Fengbin Song ◽  
Hongwen Xu ◽  
...  
Keyword(s):  
Photosynthetic Efficiency ◽  
Optimal Dose ◽  
Growth And Yield ◽  
Growth Stages ◽  
Alkaline Stress ◽  
Alkaline Soil ◽  
Alkaline Soils ◽  
Saline Alkaline Soils ◽  
Different Growth Stages ◽  
Maize Photosynthesis

The research aimed to determine the effects of Si application on photosynthetic characteristics of maize on saline-alkaline soil, including photosynthetic rate (Pn), stomatal conductance (gs), transpiration rate (E), and intercellular CO2concentration (Ci) of maize in the field with five levels (0, 45, 90, 150, and 225 kg·ha−1) of Si supplying. Experimental results showed that the values ofPn,gs, andCiof maize were significantly enhanced while the values ofEof maize were dramatically decreased by certain doses of silicon fertilizers, which meant that Si application with proper doses significantly increased photosynthetic efficiency of maize in different growth stages under stressing environment of saline-alkaline soil. The optimal dose of Si application in this experiment was 150 kg·ha−1 Si. It indicated that increase in maize photosynthesis under saline-alkaline stress took place by Si application with proper doses, which is helpful to improve growth and yield of maize.

Leaf area durations and grain yields of two tropical rice varieties

1968 ◽  
Vol 8 (34) ◽  
pp. 587
Author(s):  
PC Owen
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Photosynthetic Efficiency ◽  
Temperate Climate ◽  
Growth Stages ◽  
Rice Varieties ◽  
Area Index ◽  
Grain Yields ◽  
Different Growth Stages

A series of differing leaf area index regimes during the growth of two tropical rice varieties was produced by partial defoliation at different growth stages. In addition, part of the crop was completely defoliated after panicle emergence. Comparison of the effects of the range of leaf area durations (D) thus produced showed that these rice varieties differed from temperate climate cereals. Grain yields were least associated with D after panicle emergence, but were most influenced by D before emergence. This effect is mainly via an influence upon the number of spikelets formed per panicle. Grain : leaf ratio, a measure of photosynthetic efficiency, was considerably lower than values reported for wheat.

Effects of Straw Mulching and Tillage Measures on the Photosynthetic Characteristics of Maize Leaves

2019 ◽  
Vol 62 (3) ◽  
pp. 851-858
Author(s):  
Jilong Liu ◽  
Lu Liu ◽  
Qiang Fu ◽  
Lingling Zhang ◽  
Jiawen Li ◽  
...  
Keyword(s):  
Photosynthetic Rate ◽  
Photosynthetic Capacity ◽  
Light Response ◽  
Conventional Tillage ◽  
Growth Stages ◽  
No Tillage ◽  
Straw Mulching ◽  
Straw Mulch ◽  
Maize Leaves ◽  
Different Growth Stages

Abstract. This study investigated the response mechanisms of maize leaf photosynthetic characteristics to straw mulching and tillage measures in the black soil region of northeast China. Five treatments were established based on tillage and the average straw mulch yield from prior years (6500 kg ha-1): conventional tillage with no straw mulching (CK), conventional tillage with 1.0-fold (6500 kg ha-1) mulching (CM1), no tillage with 0.5-fold (3250 kg ha-1) mulching (NM0.5), no tillage with 1.0-fold (6500 kg ha-1) mulching (NM1), and no tillage with 1.5-fold (9750 kg ha-1) mulching (NM1.5). The net photosynthetic rate, stomatal conductance, intercellular CO2 concentration, and light response curves of maize leaves were determined and compared between the treatments with different straw mulching amounts and farming methods and between different growth stages. The photosynthetic capacity of maize leaves was greater under NM1.5 than under the other treatments except at the V6 growth stage, and the increase in yield was the most obvious effect. The photosynthetic capacity of maize leaves can be improved by increasing the quantity of straw mulch. The photosynthesis of maize was affected by nonstomatal factors at different growth stages, and straw mulching reduced the negative effects of nonstomatal factors on the photosynthesis of maize leaves. Based on a light response model of the photosynthetic rate, the maximum net photosynthetic rate, light saturation point, and apparent quantum efficiency increased as the straw mulch quantity increased, and the magnitude of the increase was greatest between the 1.0-fold and 0.5-fold straw mulching treatments. This finding indicated that straw mulching can increase the adaptability of maize to strong light and improve the efficiency of maize under weak light; moreover, the NM1.5 treatment led to the greatest improvement in the light response characteristics of maize leaves. Keywords: Photosynthetic characteristic, Photosynthetic light response curve, Straw mulching, Tillage measure.

Bisphenol A effects on the chlorophyll contents in soybean at different growth stages

2017 ◽  
Vol 223 ◽  
pp. 426-434 ◽  
Author(s):  
Liya Jiao ◽  
Hezhou Ding ◽  
Lihong Wang ◽  
Qing Zhou ◽  
Xiaohua Huang
Keyword(s):  
Bisphenol A ◽  
Growth Stages ◽  
Chlorophyll Contents ◽  
Different Growth Stages

scholarly journals Modified Red Blue Vegetation Index for Chlorophyll Estimation and Yield Prediction of Maize from Visible Images Captured by UAV

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5055 ◽  
Author(s):  
Yahui Guo ◽  
Hanxi Wang ◽  
Zhaofei Wu ◽  
Shuxin Wang ◽  
Hongyong Sun ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Grain Weight ◽  
Support Vector ◽  
Growth Stages ◽  
Yield Prediction ◽  
Chlorophyll Contents ◽  
Learning Machine ◽  
Long Term Observation ◽  
Mean Square Errors ◽  
Different Growth Stages

The vegetation index (VI) has been successfully used to monitor the growth and to predict the yield of agricultural crops. In this paper, a long-term observation was conducted for the yield prediction of maize using an unmanned aerial vehicle (UAV) and estimations of chlorophyll contents using SPAD-502. A new vegetation index termed as modified red blue VI (MRBVI) was developed to monitor the growth and to predict the yields of maize by establishing relationships between MRBVI- and SPAD-502-based chlorophyll contents. The coefficients of determination (R2s) were 0.462 and 0.570 in chlorophyll contents’ estimations and yield predictions using MRBVI, and the results were relatively better than the results from the seven other commonly used VI approaches. All VIs during the different growth stages of maize were calculated and compared with the measured values of chlorophyll contents directly, and the relative error (RE) of MRBVI is the lowest at 0.355. Further, machine learning (ML) methods such as the backpropagation neural network model (BP), support vector machine (SVM), random forest (RF), and extreme learning machine (ELM) were adopted for predicting the yields of maize. All VIs calculated for each image captured during important phenological stages of maize were set as independent variables and the corresponding yields of each plot were defined as dependent variables. The ML models used the leave one out method (LOO), where the root mean square errors (RMSEs) were 2.157, 1.099, 1.146, and 1.698 (g/hundred grain weight) for BP, SVM, RF, and ELM. The mean absolute errors (MAEs) were 1.739, 0.886, 0.925, and 1.356 (g/hundred grain weight) for BP, SVM, RF, and ELM, respectively. Thus, the SVM method performed better in predicting the yields of maize than the other ML methods. Therefore, it is strongly suggested that the MRBVI calculated from images acquired at different growth stages integrated with advanced ML methods should be used for agricultural- and ecological-related chlorophyll estimation and yield predictions.

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