Improvement of the YOLOv5 Model in the Optimization of the Brown Spot Disease Recognition Algorithm of Kidney Bean.

The kidney bean is an important cash crop whose growth and yield are severely affected by brown spot disease. Traditional target detection models cannot effectively screen out key features, resulting in model overfitting and weak generalization ability. In this study, a Bi-Directional Feature Pyramid Network (BiFPN) and Squeeze and Excitation (SE) module were added to a YOLOv5 model to improve the multi-scale feature fusion and key feature extraction abilities of the improved model. The results show that the BiFPN and SE modules show higher heat in the target location region and pay less attention to irrelevant environmental information in the non-target region. The detection Precision, Recall, and mean average Precision (mAP@0.5) of the improved YOLOv5 model are 94.7%, 88.2%, and 92.5%, respectively, which are 4.9% higher in Precision, 0.5% higher in Recall, and 25.6% higher in the mean average Precision compared to the original YOLOv5 model. Compared with the YOLOv5-SE, YOLOv5-BiFPN, FasterR-CNN, and EfficientDet models, detection Precision improved by 1.8%, 3.0%, 9.4%, and 9.5%, respectively. Moreover, the rate of missed and wrong detection in the improved YOLOv5 model is only 8.16%. Therefore, the YOLOv5-SE-BiFPN model can more effectively detect the brown spot area of kidney beans.

Systematic metabolomic studies identified adult adiposity biomarkers with acetylglycine associated with fat loss in vivo.

Obesity is associated with various adverse health outcomes. Body fat (BF) distribution is recognized as an important factor of negative health consequences of obesity. Although metabolomics studies, mainly focused on body mass index (BMI) and waist circumference, have explored the biological mechanisms involved in the development of obesity, these proxy composite measures are not accurate and cannot reflect BF distribution, and thus may hinder accurate assessment of metabolic alterations and differential risk of metabolic disorders among individuals presenting adiposity differently throughout the body. Thus, the exact relations between metabolites and BF remain to be elucidated. Here, we aim to examine the associations of metabolites and metabolic pathways with BF traits which reflect BF distribution. We performed systematic untargeted serum metabolite profiling and dual-energy X-ray absorptiometry (DXA) whole body fat scan for 517 Chinese women. We jointly analyzed DXA-derived four BF phenotypes to detect cross-phenotype metabolite associations and to prioritize important metabolomic factors. Topology-based pathway analysis was used to identify important BF-related biological processes. Finally, we explored the relationships of the identified BF-related candidate metabolites with BF traits in different sex and ethnicity through two independent cohorts. Acetylglycine, the top distinguished finding, was validated for its obesity resistance effect through in vivo studies of various diet-induced obese (DIO) mice. Eighteen metabolites and fourteen pathways were discovered to be associated with BF phenotypes. Six of the metabolites were validated in varying sex and ethnicity. The obesity-resistant effects of acetylglycine were observed to be highly robust and generalizable in both human and DIO mice. These findings demonstrate the importance of metabolites associated with BF distribution patterns and several biological pathways that may contribute to obesity and obesity-related disease etiology, prevention, and intervention. Acetylglycine is highlighted as a potential therapeutic candidate for preventing excessive adiposity in future studies.

Non-destructive monitoring of maize LAI by fusing UAV spectral and textural features.

Leaf area index (LAI) is an essential indicator for crop growth monitoring and yield prediction. Real-time, non-destructive, and accurate monitoring of crop LAI is of great significance for intelligent decision-making on crop fertilization, irrigation, as well as for predicting and warning grain productivity. This study aims to investigate the feasibility of using spectral and texture features from unmanned aerial vehicle (UAV) multispectral imagery combined with machine learning modeling methods to achieve maize LAI estimation. In this study, remote sensing monitoring of maize LAI was carried out based on a UAV high-throughput phenotyping platform using different varieties of maize as the research target. Firstly, the spectral parameters and texture features were extracted from the UAV multispectral images, and the Normalized Difference Texture Index (NDTI), Difference Texture Index (DTI) and Ratio Texture Index (RTI) were constructed by linear calculation of texture features. Then, the correlation between LAI and spectral parameters, texture features and texture indices were analyzed, and the image features with strong correlation were screened out. Finally, combined with machine learning method, LAI estimation models of different types of input variables were constructed, and the effect of image features combination on LAI estimation was evaluated. The results revealed that the vegetation indices based on the red (650 nm), red-edge (705 nm) and NIR (842 nm) bands had high correlation coefficients with LAI. The correlation between the linearly transformed texture features and LAI was significantly improved. Besides, machine learning models combining spectral and texture features have the best performance. Support Vector Machine (SVM) models of vegetation and texture indices are the best in terms of fit, stability and estimation accuracy (R2 = 0.813, RMSE = 0.297, RPD = 2.084). The results of this study were conducive to improving the efficiency of maize variety selection and provide some reference for UAV high-throughput phenotyping technology for fine crop management at the field plot scale. The results give evidence of the breeding efficiency of maize varieties and provide a certain reference for UAV high-throughput phenotypic technology in crop management at the field scale.

Study on Hyperspectral Monitoring Model of Total Flavonoids and Total Phenols in Tartary Buckwheat Grains.

Tartary buckwheat is a common functional food. Its grains are rich in flavonoids and phenols. The rapid measurement of flavonoids and phenols in buckwheat grains is of great significance in promoting the development of the buckwheat industry. This study, based on multiple scattering correction (MSC), standardized normal variate (SNV), reciprocal logarithm (Lg), first-order derivative (FD), second-order derivative (SD), and fractional-order derivative (FOD) preprocessing spectra, constructed hyperspectral monitoring models of total flavonoids content and total phenols content in tartary buckwheat grains. The results showed that SNV, Lg, FD, SD, and FOD preprocessing had different effects on the original spectral reflectance and that FOD can also reflect the change process from the original spectrum to the integer-order derivative spectrum. Compared with the original spectrum, MSC, SNV, Lg, FD, and SD transformation spectra can improve the correlation between spectral data and total flavonoids and total phenols in varying degrees, while the correlation between FOD spectra of different orders and total flavonoids and total phenols in grains was different. The monitoring models of total flavonoids and total phenols in grains based on MSC, SNV, Lg, FD, and SD transformation spectra achieved the best accuracy under SD and FD transformation, respectively. Therefore, this study further constructed monitoring models of total flavonoids and total phenols content in grains based on the FOD spectrum and achieved the best accuracy under 1.6 and 0.6 order derivative preprocessing, respectively. The R2c, RMSEc, R2v, RMSEv, and RPD were 0.8731, 0.1332, 0.8384, 0.1448, and 2.4475 for the total flavonoids model, and 0.8296, 0.2025, 0.6535, 0.1740, and 1.6713 for the total phenols model. The model can realize the rapid measurement of total flavonoids content and total phenols content in tartary buckwheat grains, respectively.

Identification of structural variations related to drought tolerance in wheat (Triticum aestivum L.).

KEY MESSAGE: Structural variations are common in plant genomes, affecting meiotic recombination and distorted segregation in wheat. And presence/absence variations can significantly affect drought tolerance in wheat. Drought is a major abiotic stress limiting wheat production. Common wheat has a complex genome with three sub-genomes, which host large numbers of structural variations (SVs). SVs play critical roles in understanding the genetic contributions of plant domestication and phenotypic plasticity, but little is known about their genomic characteristics and their effects on drought tolerance. In the present study, high-resolution karyotypes of 180 doubled haploids (DHs) were developed. Signal polymorphisms between the parents involved with 8 presence-absence variations (PAVs) of tandem repeats (TR) distributed on the 7 (2A, 4A, 5A, 7A, 3B, 7B, and 2D) of 21 chromosomes. Among them, PAV on chromosome 2D showed distorted segregation, others transmit normal conforming to a 1:1 segregation ration in the population; and a PAVs recombination occurred on chromosome 2A. Association analysis of PAV and phenotypic traits under different water regimes, we found PAVs on chromosomes 4A, 5A, and 7B showed negative effect on grain length (GL) and grain width (GW); PAV.7A had opposite effect on grain thickness (GT) and spike length (SL), with the effect on traits differing under different water regimes. PAVs on linkage group 2A, 4A, 7A, 2D, and 7B associated with the drought tolerance coefficients (DTCs), and significant negative effect on drought resistance values (D values) were detected in PAV.7B. Additionally, quantitative trait loci (QTL) associated with phenotypic traits using the 90 K SNP array showed QTL for DTCs and grain-related traits in chromosomes 4A, and 5A, 3B were co-localized in differential regions of PAVs. These PAVs can cause the differentiation of the target region of SNP and could be used for genetic improvement of agronomic traits under drought stress via marker-assisted selection (MAS) breeding.

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Frequent occurrence of drought disaster will seriously affect the growth and development of winter wheat (Triticum aestivum). We set different water stress treatments (80%, 60%, 45%, 35%, 30% of field water capacity) to simulate the severity of drought disaster. We measured free proline content (Pro) of winter wheat, and investigated the responses of Pro to canopy spectral reflectance under water stress. Three methods, i.e., correlation analysis and stepwise multiple linear regression (CA+SMLR), partial least squares and stepwise multiple linear regression (PLS+SMLR), and successive projections algorithm (SPA) were used to extract the hyperspectral cha-racteristic region and characteristic band of proline. Furthermore, partial least square regression (PLSR) and multiple linear regression (MLR) methods were used to establish the predicted models. The results showed that Pro content of winter wheat was higher under water stress, and that the spectral reflectance of canopy changed regularly in different bands, indicating that Pro content of winter wheat was sensitive to water stress. The content of Pro was highly correlated with the red edge of canopy spectral reflectance, with the 754, 756 and 761 nm bands being sensitive to Pro change. The PLSR model performed good, followed by the MLR model, both showing good predictive ability and high model accuracy. In general, it was feasible to monitor Pro content of winter wheat by hyperspectral technique.

Nitrogen fertilizer application rates and ratios promote the biochemical and physiological attributes of winter wheat.

Improper optimization of the rates and ratios of nitrogen application reduces grain yields and increases the nitrogen loss, thereby affecting environmental quality. In addition, scarcer evidence exists on the integrative approach of nitrogen, which could have effects on the biochemical and physiological characteristics of wheat. Treatments were arranged as nitrogen (N) rates of 00, 75, 150, 225, and 300 kg ha-1 in the main plots, and different nitrogen ratios were organized in subplots at 5:5:0:0 and 6:4:0:0, which were applied at the sowing, jointing, flowering, and grain filling stages. The results revealed that 225 kg N ha-1 significantly enhanced the stomatal conductance (G s), photosynthetic rate (P n), intercellular CO2 (C i), transpiration rate (T r), and total chlorophyll by 28.5%, 42.3%, 10.0%, 15.2%, and 50%, receptively, at the jointing stage in comparison to the control (0 kg N ha-1). Nitrogen application of 225 kg ha-1 increased the soil-plant analysis development (SPAD) value and the chlorophyll a, chlorophyll b, and carotenoid contents of winter wheat under the 6:4:0:0 ratio. The trend of the photosynthetic characteristics was observed to be greater at the 6:4:0:0 fertilization ratio compared to that at 5:5:0:0. The photosynthetic rate was significantly associated with the biochemical and physiological characteristics of winter wheat. In conclusion, the nitrogen dose of 225 kg ha-1 and the ratio of 6:4:0:0 (quantity applied at the sowing, jointing, flowering, and grain filling stages) effectively promoted the photosynthetic and other physiological characteristics of winter wheat.

Improving Winter Wheat Photosynthesis, Nitrogen Use Efficiency, and Yield by Optimizing Nitrogen Fertilization.

Wheat is the third most producing crop in China after maize and rice. In order to enhance the nitrogen use efficiency (NUE) and grain yield of winter wheat, a two-year field experiment was conducted to investigate the effect of different nitrogen ratios and doses at various development stages of winter wheat (Triticum aestivum L.). A total of five N doses (0, N75, N150, N225, and N300 kg ha-1) as main plots and two N ratios were applied in split doses (50%:50% and 60%:40%, referring to 50% at sowing time and 50% at jointing stage, 50% at sowing time + 50% at flowering stage, 50% at sowing time + 50% at grain filling stage, and 60% + 40% N ratio applied as a 60% at sowing time and 40% at jointing stage, 60% at sowing time and 40% at flowering stage, and 60% at sowing time and 40% at grain filling stage in subplots). The results of this study revealed that a nitrogen dose of 225 kg ha-1 significantly augmented the plant height by 27% and above ground biomass (ABG) by 24% at the grain filling stage, and the leaf area was enhanced by 149% at the flowering stage under 60 + 40% ratios. Furthermore, the N225 kg ha-1 significantly prompted the photosynthetic rate by 47% at the jointing and flowering stages followed by grain filling stage compared to the control. The correlation analysis exhibited the positive relationship between nitrogen uptake and nitrogen content, chlorophyll, and dry biomass, revealing that NUE enhanced and ultimately increased the winter wheat yield. In conclusion, our results depicted that optimizing the nitrogen dose (N225 kg/ha-1) with a 60% + 40% ratio at jointing stage increased the grain yield and nitrogen utilization rate.

Excess dietary zinc drives a Cushing's-like syndrome in ovariectomized mice - Implications for postmenopausal obesity.

Postmenopausal women have an increased risk of obesity, but the underlying cause is not clear. We unexpectedly found that excess dietary zinc induced severe obesity and a Cushing's-like syndrome without increased food intake in ovariectomized (Ovx) but not in sham-operated mice. Zinc accumulated in the adrenal glands and inhibited adrenal 17,20-lyase activity and steroid synthesis. As adrenal steroids are the only source of estrogen in Ovx mice, estrogen deficiency induced adrenal hyperplasia, glucocorticoid overproduction, and consequent development of a Cushing's-like syndrome. Adrenal steroid supplementation prevented the effects of zinc. Plasma zinc was positively correlated with cortisol level and negatively correlated with the levels of adrenal steroids and estrogen in obese postmenopausal women. The finding of a link between dietary zinc, estrogen deficiency, and postmenopausal obesity, implies that postmenopausal obesity might be prevented by supplementation with a adrenal steroid and avoiding excess dietary zinc.

Monitoring Leaf Nitrogen Accumulation With Optimized Spectral Index in Winter Wheat Under Different Irrigation Regimes.

Rapid and non-destructive estimation of leaf nitrogen accumulation (LNA) is essential to field nitrogen management. Currently, many vegetation indices have been used for indicating nitrogen status. Few studies systematically analyzed the performance of vegetation indices of winter wheat in estimating LNA under different irrigation regimes. This study aimed to develop a new spectral index for LNA estimation. In this study, 2 years of field experiments with different irrigation regimes were conducted from 2015 to 2017. The original reflectance (OR) and three transformed spectra [e.g., the first derivative reflectance (FDR), logarithm of the reciprocal of the spectra (Log(1/R)), and continuum removal (CR)] were used to calculate two- and three-band spectral indices. Correlation analyses and univariate linear and non-linear regression between transformed-based spectral indices and LNA were performed. The performance of the optimal spectral index was evaluated with classical vegetation index. The results showed that FDR was the most stable transformation method, which can effectively enhance the relationships to LNA and improve prediction performance. With a linear relationship with LNA, FDR-based three-band spectral index 1 (FDR-TBI1) (451, 706, 688) generated the best performance with coefficient of determination (R 2) of 0.73 and 0.79, the root mean square error (RMSE) of 1.267 and 1.266 g/m2, and the ratio of performance to interquartile distance (RPIQ) of 2.84 and 2.71 in calibration and validation datasets, respectively. The optimized spectral index [FDR-TBI1 (451, 706, 688)] is more effective and might be recommended as an indicator for estimating winter wheat LNA under different irrigation regimes.

Growth, Yield and Photosynthetic Performance of Winter Wheat as Affected by Co-Application of Nitrogen Fertilizer and Organic Manures.

The application of organic manures was found to be beneficial, however, the integrated use of organic manures with chemical nitrogen fertilizers has proven more sustainable in increasing the photosynthetic attributes and grain yield of the winter-wheat crop. A multi-factor split-plot design was adopted, nitrogen and manure fertilizer treatments were set in the sub-plots, including nitrogen-gradient treatment of T1:0 kg N ha-1, T2:100 kg N ha-1, T3:200 kg N ha-1, and T4:300 kg N ha-1 (pure nitrogen -fertilizer application) The 25% reduction in nitrogen combined with the manure-fertilizer application includes T5:75 kg N ha-1 nitrogen and 25 kg N ha-1 manure, T6:150 kg N ha-1 nitrogen and 50 kg N ha-1 manure, and T7:225 kg N ha-1 nitrogen and 75 kg N ha-1 manure. The maximum results of the total chlorophyll content and photosynthetic rate were 5.73 mg/g FW and 68.13 m mol m-2 s-1, observed under T4 in Zhongmai 175, as compared to Jindong 22 at the heading stage. However, the maximum results of intercellular CO2 concentration were 1998.47 µmol mol-1, observed under T3 in Jindong 22, as compared to Zhongmai 175 at the tillering stage. The maximum results of LAI were 5.35 (cm2), observed under T7 in Jindong 22, as compared to Zhongmai 175 at the booting stage. However, the maximum results of Tr and Gs were 6.31 mmol H2O m-2 s-1 and 0.90 H2O mol m-2 s-1, respectively, observed under T7 in Zhongmai 175 as compared to Jindong 22 at the flowering stage. The results revealed that grain yield 8696.93 kg ha-1, grains spike-1 51.33 (g), and 1000-grain weight 39.27 (g) were significantly higher, under T3 in Zhongmai 175, as compared to Jindong 22. Moreover, the spike number plot-1 of 656.67 m2 was significantly higher in Jindong 22, as compared to Zhongmai 175. It was concluded from the study that the combined application of nitrogen and manure fertilizers in winter wheat is significant for enhancing seed at the jointing and flowering stages. For increased grain yield and higher economic return, Zhongmai 175 outperformed the other cultivars examined. This research brings awareness toward the nitrogen-fertilizer-management approach established for farmers' practice, which might be observed as an instruction to increase agricultural management for the winter-wheat-growth season.

Effects of Applying Different Doses of Selenite to Soil and Foliar at Different Growth Stage on Selenium Content and Yield of Different Oat Varieties.

(1) Background: With the increase in people's consumption of processed oat products, the production of selenium (Se)-enriched oat has become a possibility to supplement the human body with Se. Therefore, the effects of various factors on the Se-enriched ability and yield of different oat varieties were comprehensively studied. (2) Methods: cv."Pinyan 5" and cv."Bayou 18" were applied at the stem-elongation stage and heading stage in the Jinzhong (JZ), and cv."Bayou 1" and cv."Jinyan 18" were applied at the heading stage and flowering stage in the northwestern Shanxi (JXB) with different doses of Na2SeO3 (0, 5.48, 10.96, 21.92, 43.84, 65.76, 98.64, 0, 5.48, 10.96, 21.92, 43.84, 65.76, 98.64, 147.96 g hm-2) by soil application and foliar spraying. (3) Results: The grain Se content and yield of oat were affected by the variety, Se application dose, stage and method of Se supplementation. Additionally, the Se content in oat grain was positively correlated with the Se application dose while the yield of oat first increased and then decreased with the Se application dose. (4) Conclusions: In the JZ and JXB, 21.92 g hm-2 and 43.84 g hm-2 Se was sprayed on the leaves of cv."Bayou 18" and cv."Bayou 1" at the heading stage, respectively, was the most effective Se biofortification program.

Effects of selenium application concentration, period and method on the selenium content and grain yield of Tartary buckwheat of different varieties.

BACKGROUND: As a potential selenium-enriched crop, it is of great significance to study the selenium application of Tartary buckwheat. Therefore, to study the effects of selenium application concentration, variety, selenium application period and method on the grain selenium content and yield of Tartary buckwheat, an orthogonal experimental design was used to carry out field experiments in the Jinzhong and Northwest Shanxi ecological regions at the same time. Heifeng 1 and Jinqiao 2 were applied at the branching stage and flowering stage in the Jinzhong, and Heifeng 1 and Jinqiao 6 were applied at the early flowering stage and peak flowering stage in the Northwest Shanxi with different concentrations of sodium selenite (0, 1.37, 2.74, 5.48, 8.22, 12.33, 18.495, 27.7425 g hm-2 ) by foliar spraying and soil application. RESULTS: The results showed that the selenium content in Tartary buckwheat grains was positively correlated with the selenium application concentration and increased with increasing selenium application concentration, while the yield of Tartary buckwheat first increased and then decreased with the selenium application concentration. The grain selenium content and yield of Tartary buckwheat were affected by the selenium application concentration, variety and application method. CONCLUSION: The most effective selenium biofortification program was spraying 2.32 g hm-2 sodium selenite on the leaves of Heifeng 1 at the early flowering stage in the Jinzhong. In the Northwest Shanxi, spraying 11.01 g hm-2 sodium selenite on the leaves of Jinqiao 6 at the flowering stage was the most effective selenium biofortification program. © 2022 Society of Chemical Industry.

Modeling of the potential geographical distribution of naked oat under climate change.

Introduction: Naked oat (Avena sativa L.), is an important miscellaneous grain crop in China, which is rich in protein, amino acids, fat and soluble dietary fiber. The demand for functional foods is gradually increasing as living standards rise, and the output of minor cereals in China is increasing annually. The planting layout of naked oat is scattered and lacks planning, which seriously restricts the development of the naked oat industry. The increase in miscellaneous grain production will not only be impacted by cultivation methods and management techniques, but the potential impact of global climate change needs to be considered. North China is the main area for naked oat production, worldwide. Methods: In this study, the potential distribution range of naked oat in North China was forecast based on historical distribution data and the Maxent model under climate change conditions. The performance of the model was relatively high. Results: The results indicated that the most suitable area for the potential geographic distribution of naked oat in North China was 27.89×104 km2, including central and northeastern Shanxi, and northeastern and western Hebei and Beijing, gradually moving northward. The core suitable area increased, and the distribution of naked oat had an obvious regional response to climate warming; the main environmental factors affecting the potential geographic distribution were precipitation factor variables (precipitation seasonality (variation coefficient)), terrain factor variables (elevation) and temperature factor variables (temperature seasonality (Standard Deviation*100)). Discussion: In this study, the Maxent model was used to analyze and predict suitable areas for naked oat in North China, and the distribution of suitable areas was accurately divided, and the main climatic factors affecting the distribution of naked oat were identified. This research provides data support and theoretical support for the optimal planting zone of naked oat in North China.

Optimizing nitrogen supply promotes biomass, physiological characteristics and yield components of soybean (Glycine max L. Merr.).

Avoidable or inappropriate nitrogen (N) fertilizer rates harmfully affect the yield production and ecological value. Therefore, the aims of this study were to optimize the rate and timings of N fertilizer to maximize yield components and photosynthetic parameter of soybean. This field experiment consists of five fertilizer N rates: 0, 75, 150, 225 and 300 kg N ha-1 arranged in main plots and four N fertilization timings: V5 (trifoliate leaf), R2 (full flowering stage) and R4 (full poding stage), and R6 (full seeding stage) growth stages organized as subplots. Results revealed that 225 kg N ha-1 significantly enhanced grain yield components, total chlorophyll (Chl), photosynthetic rate (P N), and total dry biomass and N accumulation by 20%, 16%, 28%, 7% and 12% at R4 stage of soybean. However, stomatal conductance (g s ), leaf area index (LAI), intercellular CO2 concentration (Ci) and transpiration rate (E) were increased by 12%, 88%, 10%, 18% at R6 stage under 225 kg N ha-1. Grain yield was significantly associated with photosynthetic characteristics of soybean. In conclusion, the amount of nitrogen 225 kg ha-1 at R4 and R6 stages effectively promoted the yield components and photosynthetic characteristics of soybean.

Study on hyperspectral estimation model of soil organic carbon content in the wheat field under different water treatments.

Hyperspectral remote sensing technology can be used to monitor the soil nutrient changes in a rapid, real-time, and non-destructive manner, which is of great significance to promote the development of precision agriculture. In this paper, 225 soil samples were studied. The effects of different water treatments on soil organic carbon (SOC) content, and the relationship between SOC content and spectral reflectance (350-2500 nm) were studied. 17 kinds of preprocessing algorithm were performed on the original spectral (R), and the five allocation ratios of calibration to verification sets were set. Finally, the model was constructed by partial least squares regression (PLSR). The results showed that the effects of water treatment on SOC content were different in different growth stages of winter wheat. Results of correlation analysis showed that the differential transformation can refine the spectral characteristics, and improve the correlation between SOC content and spectral reflectance. Results of model construction showed that the models constructed by second-order differential transformation were not good. But the ratio of standard deviation to the standard prediction error (RPD) values of the models were constructed by simple mathematical transformation (T0-T5) and first-order differential transformation (T6-T11) can reach more than 1.4. The simple mathematical transformation (T0-T2, T4-T5) and the first-order differential transformation (T6-T10) resulted in the highest RPD in mode 5 and mode 2, respectively. Among all the models, the model of T7 in mode 2 reach the highest accuracy with a RPD value of 1.9861. Therefore, it is necessary to consider the data preprocessing algorithm and allocation ratio in the process of constructing the hyperspectral monitoring model of SOC.

Agronomical traits associated with yield and yield components of winter wheat as affected by nitrogen managements.

Nitrogen fertilizer is one of the key elements to increase the yield and significance of winter wheat. The experiment was established in the split zone design and was repeated three times. The nitrogen application level is set to 4 treatments, 75, 150, 225 and 300 kg ha-1 are arranged in the main plot, and different nitrogen application ratios are arranged in the sub-plots, respectively 5:5 (50%+50%) and 6: 4 (60%) + 40%). Nitrogen fertilizer was applied before sowing, jointing stage, flowering stage and filling stage. The experimental plot is 12 m2 (3 m × 4 m). The results showed that under the conditions of 225 kg/hm2 nitrogen application and 60%+40% nitrogen application rate, the yield of Jintai 182 was the highest compared with other treatment groups. With the increase of nitrogen application rate, the number of ears, grains per ear, thousand-grain weight and grain yield all increase first and then decrease. Each factor reached the highest 225 N kg / hm2, 417.17, 30.74, 40.96 g and 6182.11 kg / hm2. Compared with 75 kg/hm2 topdressing fertilizer, 225 kg/hm2 is a more suitable nitrogen fertilizer application rate for winter wheat. Within a reasonable range of nitrogen fertilizer application, there is a significant positive correlation between nitrogen content and winter wheat yield. By studying the amount of nitrogen fertilizer and a reasonable ratio of base fertilizer to topdressing, the utilization rate of nitrogen fertilizer can be maximized and excessive application of nitrogen fertilizer can be avoided.

SPTBN1 Prevents Primary Osteoporosis by Modulating Osteoblasts Proliferation and Differentiation and Blood Vessels Formation in Bone.

Osteoporosis is a common systemic skeletal disorder that leads to increased bone fragility and increased risk of fracture. Although ßII-Spectrin (SPTBN1) has been reported to be involved in the development of various human cancers, the function and underlying molecular mechanisms of SPTBN1 in primary osteoporosis remain unclear. In this study, we first established a primary osteoporosis mouse model of senile osteoporosis and postmenopausal osteoporosis. The results showed that the expression of SPTBN1 was significantly downregulated in primary osteoporosis mice model compared with the control group. Furthermore, silencing of SPTBN1 led to a decrease in bone density, a small number of trabecular bones, wider gap, decreased blood volume fraction and number of blood vessels, as well as downregulation of runt-related transcription factor 2 (Runx2), Osterix (Osx), Osteocalcin (Ocn), and vascular endothelial growth factor (VEGF) in primary osteoporosis mice model compared with the control group. Besides, the silencing of SPTBN1 inhibited the growth and induced apoptosis of mouse pre-osteoblast MC3T3-E1 cells compared with the negative control group. Moreover, the silencing of SPTBN1 significantly increased the expression of TGF-ß, Cxcl9, and the phosphorylation level STAT1 and Smad3 in MC3T3-E1 cells compared with the control group. As expected, overexpression of SPTBN1 reversed the effect of SPTBN1 silencing in the progression of primary osteoporosis both in vitro and in vivo. Taken together, these results suggested that SPTBN1 suppressed primary osteoporosis by facilitating the proliferation, differentiation, and inhibition of apoptosis in osteoblasts via the TGF-ß/Smad3 and STAT1/Cxcl9 pathways. Besides, overexpression of SPTBN1 promoted the formation of blood vessels in bone by regulating the expression of VEGF. This study, therefore, provided SPTBN1 as a novel therapeutic target for osteoporosis.

Potential of Multivariate Statistical Technique Based on the Effective Spectra Bands to Estimate the Plant Water Content of Wheat Under Different Irrigation Regimes.

Real-time, nondestructive, and accurate estimation of plant water status is important to the precision irrigation of winter wheat. The objective of this study was to develop a method to estimate plant water content (PWC) by using canopy spectral proximal sensing data. Two experiments under different water stresses were conducted in 2014-2015 and 2015-2016. The PWC and canopy reflectance of winter wheat were collected at different growth stages (the jointing, booting, heading, flowering, and filling stages in 2015 and the jointing, booting, flowering, and filling stages in 2016). The performance of different spectral transformation approaches was further compared. Based on the optimal pretreatment, partial least squares regression (PLSR) and four combination methods [i.e., PLSR-stepwise regression (SR), PLSR-successive projections algorithm (SPA), PLSR-random frog (RF), and PLSR-uninformative variables elimination (UVE)] were used to extract the sensitive bands of PWC. The results showed that all transformed spectra were closely correlated to PWC. The PLSR models based on the first derivative transformation method exhibited the best performance (coefficient of determination in calibration, R 2 C = 0.96; root mean square error in calibration, RMSEC = 20.49%; ratio of performance to interquartile distance in calibration, RPIQC = 9.19; and coefficient of determination in validation, R 2 V = 0.86; root mean square error in validation, RMSEV = 46.27%; ratio of performance to interquartile distance in validation, RPIQV = 4.34). Among the combination models, the PLSR model established with the sensitive bands from PLSR-RF demonstrated a good performance for calibration and validation (R 2 C = 0.99, RMSEC = 11.53%, and RPIQC = 16.34; and R 2 V = 0.84, RMSEV = 44.40%, and RPIQV = 4.52, respectively). This study provides a theoretical basis and a reference for estimating PWC of winter wheat by using canopy spectral proximal sensing data.

Canopy hyperspectral characteristics and yield estimation of winter wheat (Triticum aestivum) under low temperature injury.

To evaluate the effect of low-temperature stress in winter wheat during the early growth stages, the response regularity of the canopy spectral reflectance was evaluated. Besides, winter wheat yield during the maturation stage and the relationship between yield and canopy spectral reflectance were also analyzed. Two multivariate methods, namely, the successive projections algorithm (SPA) and multiple linear regression (MLR), were combined to explore the relationship between the spectral reflectance and yield. Our results showed that the green peak and red valley in visible wavelengths altered obviously and the red edge gradually moved towards blue wavebands. The canopy spectral reflectance in the near-infrared wavebands increased with an increase in low-temperature stress intensity. Moreover, the reflectance proved that the red edge region under low-temperature stress is related to winter wheat yield, and approximately 38% of extracted wavebands were concentrated in the red edge region (680-780 nm). Compared with the predictive MLR models, the model calibrated during the flowering period of winter wheat (25 days post low-temperature treatment) had better performance in predicting crop yield. Whole-spectrum predictive models based on the principle component regression (PCR) method and Normalized Difference Vegetation Index (NDVI) models based on MLR were also established. Moreover, the performance of three kinds of calibration methods and the validation result of the field test were compared to select the optimal monitoring stage and technique to estimate the yield in the early growth stage of winter wheat under low-temperature stress. This study could provide a theoretical basis and practical reference for hyperspectral assessment of yield in winter wheat during low-temperature stress.