Leaf photosynthetic function duration during yield formation of large-spike wheat in rainfed cropping systems

Improving photosynthetic capacity significantly affects the yield of wheat (Triticum aestivum L.) in rainfed regions. In this study, the physiological characteristics of eight large-spike wheat lines were compared with a multiple-spike cultivar as a control (CK) in a field over two consecutive seasons: 2010–2012. The tillering peak was 7–21 d after returning green for line 2040, the average rate of decline of relative water content was slower, and the average duration time of photosynthetic rate was longer than CK in vitro. There was a strong linear and positive correlation between photosynthetic rate and root activity at jointing, flowering, and grain-filling stages. In addition, average yields were higher in large-spike lines than CK (multiple-spike cultivar). The results suggest that large-spike lines might have greater water retaining capacity during yield formation under rainfed conditions

Evaluating a new method to estimate the rate of leaf respiration in the light by analysis of combined gas exchange and chlorophyll fluorescence measurements

Day respiration (Rd) is an important parameter in leaf ecophysiology. It is difficult to measure directly and is indirectly estimated from gas exchange (GE) measurements of the net photosynthetic rate (A), commonly using the Laisk method or the Kok method. Recently a new method was proposed to estimate Rd indirectly from combined GE and chlorophyll fluorescence (CF) measurements across a range of low irradiances. Here this method is tested for estimating Rd in five C3 and one C4 crop species. Values estimated by this new method agreed with those by the Laisk method for the C3 species. The Laisk method, however, is only valid for C3 species and requires measurements at very low CO2 levels. In contrast, the new method can be applied to both C3 and C4 plants and at any CO2 level. The Rd estimates by the new method were consistently somewhat higher than those by the Kok method, because using CF data corrects for errors due to any non-linearity between A and irradiance of the used data range. Like the Kok and Laisk methods, the new method is based on the assumption that Rd varies little with light intensity, which is still subject to debate. Theoretically, the new method, like the Kok method, works best for non-photorespiratory conditions. As CF information is required, data for the new method are usually collected using a small leaf chamber, whereas the Kok and Laisk methods use only GE data, allowing the use of a larger chamber to reduce the noise-to-signal ratio of GE measurements

Fundus Image Classification Using VGG-19 Architecture with PCA and SVD

Automated medical image analysis is an emerging field of research that identifies the disease with the help of imaging technology. Diabetic retinopathy (DR) is a retinal disease that is diagnosed in diabetic patients. Deep neural network (DNN) is widely used to classify diabetic retinopathy from fundus images collected from suspected persons. The proposed DR classification system achieves a symmetrically optimized solution through the combination of a Gaussian mixture model (GMM), visual geometry group network (VGGNet), singular value decomposition (SVD) and principle component analysis (PCA), and softmax, for region segmentation, high dimensional feature extraction, feature selection and fundus image classification, respectively. The experiments were performed using a standard KAGGLE dataset containing 35,126 images. The proposed VGG-19 DNN based DR model outperformed the AlexNet and spatial invariant feature transform (SIFT) in terms of classification accuracy and computational time. Utilization of PCA and SVD feature selection with fully connected (FC) layers demonstrated the classification accuracies of 92.21%, 98.34%, 97.96%, and 98.13% for FC7-PCA, FC7-SVD, FC8-PCA, and FC8-SVD, respectively

Estimation of Solar Radiation for Tomato Water Requirement Calculation in Chinese-Style Solar Greenhouses Based on Least Mean Squares Filter

The area covered by Chinese-style solar greenhouses (CSGs) has been increasing rapidly. However, only a few pyranometers, which are fundamental for solar radiation sensing, have been installed inside CSGs. The lack of solar radiation sensing will bring negative effects in greenhouse cultivation such as over irrigation or under irrigation, and unnecessary power consumption. We aim to provide accurate and low-cost solar radiation estimation methods that are urgently needed. In this paper, a method of estimation of solar radiation inside CSGs based on a least mean squares (LMS) filter is proposed. The water required for tomato growth was also calculated based on the estimated solar radiation. Then, we compared the accuracy of this method to methods based on knowledge of astronomy and geometry for both solar radiation estimation and tomato water requirement. The results showed that the fitting function of estimation data based on the LMS filter and data collected from sensors inside the greenhouse was y = 0.7634x + 50.58, with the evaluation parameters of R2 = 0.8384, rRMSE = 23.1%, RMSE = 37.6 Wm−2, and MAE = 25.4 Wm−2. The fitting function of the water requirement calculated according to the proposed method and data collected from sensors inside the greenhouse was y = 0.8550x + 99.10 with the evaluation parameters of R2 = 0.9123, rRMSE = 8.8%, RMSE = 40.4 mL plant−1, and MAE = 31.5 mL plant−1. The results also indicate that this method is more effective. Additionally, its accuracy decreases as cloud cover increases. The performance is due to the LMS filter’s low pass characteristic that smooth the fluctuations. Furthermore, the LMS filter can be easily implemented on low cost processors. Therefore, the adoption of the proposed method is useful to improve the solar radiation sensing in CSGs with more accuracy and less expense

The Effects of Rice Straw and Biochar Applications on the Microbial Community in a Soil with a History of Continuous Tomato Planting History

Soil microbial abundance and diversity change constantly in continuous cropping systems, resulting in the prevalence of soil-borne pathogens and a decline in crop yield in solar greenhouses. To investigate the effects of rice straw and biochar on soil microbial abundance and diversity in soils with a history of continuous planting, three treatments were examined: mixed rice straw and biochar addition (RC), rice straw addition (R), and biochar addition (C). The amount of C added in each treatment group was 3.78 g kg−1 soil. Soil without rice straw and biochar addition was treated as a control (CK). Results showed that RC treatment significantly increased soil pH, available nitrogen (AN), available phosphorus (AP), and potassium (AK) by 40.3%, 157.2%, and 24.2%, respectively, as compared to the CK soil. The amount of soil labile organic carbon (LOC), including readily oxidizable organic carbon (ROC), dissolved organic carbon (DOC), and light fraction organic carbon (LFOC), was significantly greater in the RC, R, and C treatment groups as compared to CK soil. LOC levels with RC treatment were higher than with the other treatments. Both rice straw and biochar addition significantly increased bacterial and total microbial abundance, whereas rice straw but not biochar addition improved soil microbial carbon metabolism and diversity. Thus, the significant effects of rice straw and biochar on soil microbial carbon metabolism and diversity were attributed to the quantity of DOC in the treatments. Therefore, our results indicated that soil microbial diversity is directly associated with DOC. Based on the results of this study, mixed rice straw and biochar addition, rather than their application individually, might be key to restoring degraded soil

Heavy Metal Pollution in a Soil-Rice System in the Yangtze River Region of China

Heavy metals are regarded as toxic trace elements in the environment. Heavy metal pollution in soil or rice grains is of increasing concern. In this study, 101 pairs of soil and rice samples were collected from the major rice-producing areas along the Yangtze River in China. The soil properties and heavy metal (i.e., Cd, Hg, Pb and Cr) concentrations in the soil and rice grains were analyzed to evaluate the heavy metal accumulation characteristics of the soil-rice systems. The results showed that the Cd, Hg, Pb and Cr concentrations in the soil ranged from 0.10 to 4.64, 0.01 to 1.46, 7.64 to 127.56, and 13.52 to 231.02 mg·kg−1, respectively. Approximately 37%, 16%, 60% and 70% of the rice grain samples were polluted by Cd, Hg, Pb, and Cr, respectively. The degree of heavy metal contamination in the soil-rice systems exhibited a regional variation. The interactions among the heavy metal elements may also influence the migration and accumulation of heavy metals in soil or paddy rice. The accumulation of heavy metals in soil and rice grains is related to a certain extent to the pH and soil organic matter (SOM). This study provides useful information regarding heavy metal accumulation in soil to support the safe production of rice in China. The findings from this study also provide a robust scientific basis for risk assessments regarding ecological protection and food safety

Estimating the Light Interception and Photosynthesis of Greenhouse-Cultivated Tomato Crops under Different Canopy Configurations

Understanding the spatial heterogeneity of light and photosynthesis distribution within a canopy is crucial for optimizing plant growth and yield, especially in the context of greenhouse structures. In previous studies, we developed a 3D functional-structural plant model (FSPM) of the Chinese solar greenhouse (CSG) and tomato plants, in which the greenhouse was reconstructed as a 3D mockup and implemented in the virtual scene. This model, which accounts for various environmental factors, allows for precise calculations of radiation, temperature, and photosynthesis at the organ level. This study focuses on elucidating optimal canopy configurations for mechanized planting in greenhouses, building upon the commonly used north–south (N–S) orientation by exploring the east–west (E–W) orientation. Investigating sixteen scenarios with varying furrow distance (1 m, 1.2 m, 1.4 m, 1.6 m) and row spacing (0.3 m, 0.4 m, 0.5 m, 0.6 m), corresponding to 16 treatments of plant spacing, four planting patterns (homogeneous row, double row, staggered row, incremental row) and two orientations were investigated. The results show that in Shenyang city, an E–W orientation with the path width = 0.5 (furrow distance + row distance) = 0.8 m (homogeneous row), and a plant distance of 0.32 m, is the optimal solution for mechanized planting at a density of 39,000 plants/ha. Our findings reveal a nuanced understanding of how altering planting configurations impacts the light environment and photosynthesis rate within solar greenhouses. Looking forward, these insights not only contribute to the field of CSG mechanized planting, but also provide a basis for enhanced CSG planting management. Future research could further explore the broader implications of these optimized configurations in diverse geographic and climatic conditions

The Variation of Soil Phosphorus Fractions and Microbial Community Composition under Consecutive Cucumber Cropping in a Greenhouse

The distribution of phosphorus (P) fractions in soil plays a decisive role in soil P bioavailability; however, the characteristics of soil P fractions under consecutive cropping in a solar greenhouse remain unclear. To evaluate the effects of the long-term successive vegetable cropping on soil P fractions and the microbial community composition in greenhouse soil, a continuous long-term cropping experiment was conducted using cucumber (Cucumis sativus L.) in a solar greenhouse starting from 2006 to 2018. Soil P fractions and the microbial community composition were determined using the Hedley continuous extraction method and the phospholipid fatty acid (PLFA) method, respectively, in the 1st, 9th, 13th, and 21st rounds of cultivation. The soil total phosphorus (TP) content increased from 0.90 g·kg−1 in the 1st round to 3.07 g·kg−1 in the 21st round of cucumber cultivation. With an increase in continuous cropping rounds, soil available phosphorus (AP) increased and the phosphorus activation coefficient (PAC) decreased, with no significant difference between the 13th and 21st rounds. After 21 rounds of continuous cropping, the soil organic matter (SOM) content was 16.34 g·kg−1, 1.42 times that of the 1st round. The abundance of soil bacteria, actinomycetes, Gram-negative bacteria (G−), Gram-positive bacteria (G+), and total PLFAs initially increased with continuous cropping rounds, but then decreased significantly, and the ratios of fungi:bacteria (F/B) and G+/G− bacteria also increased significantly with continuous cropping rounds. The contents of soil labile P, moderately labile P, and non-labile P increased significantly over 21 continuous cropping rounds. Together, these results demonstrate that long-term continuous cropping can directly lead to the accumulation of P fractions, but it can also affect the abundance of actinomycetes through SOM enrichment, which indirectly leads to the accumulation of non-labile P. This study provides a theoretical basis for future soil P fertilizer management and vegetable production sustainability

The Variation of Soil Phosphorus Fractions and Microbial Community Composition under Consecutive Cucumber Cropping in a Greenhouse

The distribution of phosphorus (P) fractions in soil plays a decisive role in soil P bioavailability; however, the characteristics of soil P fractions under consecutive cropping in a solar greenhouse remain unclear. To evaluate the effects of the long-term successive vegetable cropping on soil P fractions and the microbial community composition in greenhouse soil, a continuous long-term cropping experiment was conducted using cucumber (Cucumis sativus L.) in a solar greenhouse starting from 2006 to 2018. Soil P fractions and the microbial community composition were determined using the Hedley continuous extraction method and the phospholipid fatty acid (PLFA) method, respectively, in the 1st, 9th, 13th, and 21st rounds of cultivation. The soil total phosphorus (TP) content increased from 0.90 g·kg−1 in the 1st round to 3.07 g·kg−1 in the 21st round of cucumber cultivation. With an increase in continuous cropping rounds, soil available phosphorus (AP) increased and the phosphorus activation coefficient (PAC) decreased, with no significant difference between the 13th and 21st rounds. After 21 rounds of continuous cropping, the soil organic matter (SOM) content was 16.34 g·kg−1, 1.42 times that of the 1st round. The abundance of soil bacteria, actinomycetes, Gram-negative bacteria (G−), Gram-positive bacteria (G+), and total PLFAs initially increased with continuous cropping rounds, but then decreased significantly, and the ratios of fungi:bacteria (F/B) and G+/G− bacteria also increased significantly with continuous cropping rounds. The contents of soil labile P, moderately labile P, and non-labile P increased significantly over 21 continuous cropping rounds. Together, these results demonstrate that long-term continuous cropping can directly lead to the accumulation of P fractions, but it can also affect the abundance of actinomycetes through SOM enrichment, which indirectly leads to the accumulation of non-labile P. This study provides a theoretical basis for future soil P fertilizer management and vegetable production sustainability