Identification of an Aux/IAA regulator for flesh firmness using combined GWAS and bulked segregant RNA-Seq analysis in watermelon

Watermelon is a highly cultivated fruit crop renowned for its quality properties of fruit flesh.Among various quality factors,fruit flesh firmness is a crucial quality parameter influencing the fruit texture,shelf life and its commercial value.The auxin/indole-3-acetic acid(Aux/IAA)plays a significant role in fruit development and ripening of non-climacteric fruits.However,the regulatory mechanism of Aux/IAA in controlling fruit flesh firmness and ripening in watermelon remains unknown.In this study,we employed an integrative approach combining genome-wide association study(GWAS)and bulked segregant RNA-Seq analysis(BSR-Seq)to identify an overlapping candidate region between 12776310 and 12968331 bp on chromosome 6,underlying an auxin-responsive gene(Aux/IAA)associated with flesh firmness in watermelon.Transcriptome analysis,followed by real-time quantitative reverse transcription PCR(qRT-PCR),confirmed that the expression of Aux/IAA was consistently higher in fruits with high flesh firmness.The sequence alignment revealed a single base mutation in the coding region of Aux/IAA.Furthermore,the concomitant Kompetitive/Competitive allele-specific PCR(KASP)genotyping data sets for F2 population and germplasm accessions identified Aux/IAA as a strong candidate gene associated with flesh firmness.Aux/IAA was enriched in the plant hormone signal transduction pathway,involving cell enlargement and leading to low flesh firmness.We determined the higher accumulation of abscisic acid(ABA)in fruits with low flesh firmness than hard flesh.Moreover,overexpression of Aux/IAA induced higher flesh firmness with an increased number of fruit flesh cells while reducing ABA content and flesh cell sizes.Additionally,the allelic variation in Aux/IAA for soft flesh firmness was found to exist in Citrullus mucosospermus and gradually fixed into Citrullus lanatus during domestication,indicating that soft flesh firmness was a domesticated trait.These findings significantly enhanced our understanding of watermelon fruit flesh firmness and consequently the watermelon fruit quality.

Variation and Probability Grading of Fruit Firmness in Peach Germplasm Resource

Objective The aim was to provide basis for further studies on fruit firmness in peach fruits and the standardization and standardization of peach germplasm resource. [ Method] The analysis of fruit firmness of peach germplasm resource was based on the improved firmness measurement, and the probability grading of characteristics was carried out on peach fruit firmness. [Result] The coefficient of variation of peach fruit firmness with skin was less than that of fruit firmness without skin; the fruit firmness with skin and fruit firmness without skin were both fitted the normal distribution; the probability grading of characteristics were divided into five series based on four points of （X-1. 281 8s）, （X-0. 524 6s）, （X＋0. 524 6s） and （X＋1.281 8s）, so that the probability of 1 -5 were 10%, 20%, 40%, 20% and 10%. [Conclusion] There was more abundant genetic basis in fruit firmness, which held a potential for greater choice.

Study on Inheritance Mechanism of Tomato Fruit Firmness

[Objective] This study aimed to investigate the inheritance mechanism of tomato fruit firmness.[Method] Two tomato cultivars significantly different in fruit firmness were selected for investigation of the inheritance mechanism of tomato fruit firmness using combination analysis of six generations （P1,P2,F1,F2,B1 and B2）.[Result] The results indicated that the heredity of tomato fruit firmness was consistent with the additive-dominant model controlled by one pair of major genes; the additive effect （d）,dominant effect （h） and degree of dominance （h/d） of major genes were 17.37,-7.96 and-0.46,respectively,showing positive additive effect and incompletely dominant-negative effect; the hereditability of major gene effect in B1,B2 and F2 generation was 88.59％,45.81％ and 85.62％,respectively.[Conclusion] The heredity of fruit firmness was controlled by one pair of major gene,showing significant additive effect and dominant effect.

Firmness evaluation of melon using its vibration characteristic and finite element analysis

The “Huang gua” melons were measured for their physical properties including firmness and static elastic modulus. The vibrational characteristics of fruits and vegetables are governed by their elastic modulus (firmness), mass, and geometry. Therefore, it is possible to evaluate firmness of fruits and vegetables based on their vibrational characteristics. Analysis of the vibration responses of a fruit is suggested for measuring elastic properties (Firmness) non-destructively. The impulse response method is often used to measure firmness of fruits. The fruit was excited using three types of balls (wooden, steel and rubber) and the vibration is detected by an accelerometer. The Instron device was used to measure the static elastic modulus of the inner, middle and outer portions of melon flesh. Finite element (FE) technique was used to determine the optimum excitation location of the chosen measurement sensor and to analyze the mode shape fruits. Four types of mode shapes (torsional or flexural mode shape, first-type, second-type spherical mode and breathing mode shape) were found. Finite element simulation results agreed well with experimental results. Correlation between the firmness and resonant frequency (r2=0.91) and between the resonant frequency and stiffness factor (r2=0.74) existed. The optimum location and suitable direction for excitation and response measurement on the fruit were suggested.

Prediction of kiwifruit firmness using fruit mineral nutrient concentration by artificial neural network(ANN) and multiple linear regressions(MLR)

Many properties of fruit are influenced by plant nutrition. Fruit firmness is one of the most important fruit characteristics and determines post-harvest life of the fruit, in recent decades, artificial intelligence systems were employed for developing predictive models to estimate and predict many agriculture processes. In the present study, the predictive capabilities of multiple linear regressions （MLR） and artificial neural networks （ANNs） are evaluated to estimate fruit firmness in six months, including each of nutrients concentrations （nitrogen （N）, potassium （K）, calcium （Ca） and magnesium （Mg）） alone （P1）, com- bination of nutrients concentrations （P2）, nutrient concentration ratios alone （P3）, and combination of nutrient concentrations and nutrient concentration ratios （P4）. The results showed that MLR model estimated fruit firmness more accuracy than ANN model in three datasets （P1, P2 and P4）. However, the application of P3 （N/Ca ratio） as the input dataset in ANN model improved the prediction of fruit firmness than the MLR model. Correlation coefficient and root mean squared error （RMSE） were 0.850 and 0.539 between the measured and the estimated data by the ANN model, respectively. Generally, the ANN model showed greater potential in determining the relationship between 6-mon-fruit firmness and nutrients concentration.

Application of NIR spectroscopy for firmness evaluation of peaches

The use of near infrared （NIR） spectroscopy was proved to be a useful tool for quality analysis of fruits. A bifurcated fiber type NIR spectrometer, with a detection range of 800-2500 nm by InGaAs detector, was used to evaluate the firmness of peaches. Anisotropy of NIR spectra and firmness of peaches in relation to detecting positions of different parts （including three latitudes and three longitudes） were investigated. Both spectra absorbency and firmness of peach were influenced by longitudes （i, ii, iii） and latitudes （A, B, C）. For modeling, two thirds of the samples were used as the calibration set and the remaining one third were used as the validation or prediction set. Partial least square regression （PLSR） models for different longitude and latitude spectra and for the whole fruit show that collecting several NIR spectra from different longitudes and latitudes of a fruit for NIR calibration modeling can improve the modeling performance. In addition, proper spectra pretreatments like scattering correction or derivative also can enhance the modeling performance. The best results obtained in this study were from the holistic model with multiplicative scattering correction （MSC） pretreatment, with correlation coefficient of cross-validation γcv=0.864, root mean square error of cross-validation RMSECV=6.71 N, correlation coefficient of calibration r=0.948, root mean square error of calibration RMSEC=4.21 N and root mean square error of prediction RMSEP=5.42 N. The results of this study are useful for further research and application that when applying NIR spectroscopy for objectives with anisotropic differences, spectra and quality indices are necessarily measured from several parts of each object to improve the modeling performance.

Game theory model of exit selection in pedestrian evacuation considering visual range and choice firmness

Exit choice is one of the most important pedestrian behaviors during evacuation.Distance to the exit is a generally recognized factor influencing expected moving time to the exit.Visual range determines how much information a pedestrian can perceive,thus the number of pedestrians within the visual field can be used to estimate waiting time at the exit.Besides,the choice firmness that reflects the degree to which a pedestrian would persist in his/her previous choice of exit is proposed.By integrating game theory into a cellular automata simulation framework,the pedestrian exit choice mechanism is investigated and explicitly modeled in this paper.A systematic analysis of the key factors influencing pedestrian evacuation is conducted,including visual radius and choice firmness of a pedestrian,initial crowd distribution of the room,exit layout as well as exit width.It is found that low choice firmness level can lead to unnatural pedestrian behavior such as wandering,which is adverse to evacuation.The longer the pedestrian's visual radius,the earlier the pedestrian can determine his/her final selection of the exit.Compared with the scenario where the pedestrians are randomly distributed,pedestrians clustered together in a corner of the room lead to high crowd density and imbalanced use of exits.Furthermore,the exit layout and exit width also have a certain influence on pedestrian evacuation process.The results of this paper may be of benefit to the formulation of behavioral rules in other pedestrian simulation models.

SLAF marker based QTL mapping of fruit-related traits reveals a major-effect candidate locus ff2.1 for flesh firmness in melon

Flesh firmness(FF) is an important and complex trait for melon breeders and consumers. However, the genetic mechanism underlying FF is unclear. Here, a soft fruit melon(P5) and a hard fruit melon(P10) were crossed to generate F2, and the FF and fruit-related traits were recorded for two years. By performing quantitative trait locus(QTL) specificlocus amplified fragment(SLAF)(QTL-SLAF) sequencing and molecular marker-linkage analysis, 112 844 SLAF markers were identified, and 5 919 SNPs were used to construct a genetic linkage map with a total genetic distance of1 356.49 cM. Ten FF-and fruit-related QTLs were identified. Consistent QTLs were detected for fruit length(FL) and fruit diameter(FD) in both years, and QTLs for single fruit weight(SFW) were detected on two separate chromosomes in both years. For FF, the consistent major locus(ff2.1) was located in a 0.17-Mb candidate region on chromosome 2. Using 429 F2individuals derived from a cross between P5 and P10, we refined the ff2.1 locus to a 28.3-kb region harboring three functional genes. These results provide not only a new candidate QTL for melon FF breeding but also a theoretical foundation for research on the mechanism underlying melon gene function.

Nondestructive determination of soluble solids and firmness in mix-cultivar melon using near-infrared CCD spectroscopy

Nondestructive evaluation of melon quality is in great need of comprehensive study.Soluble solids content(SSC)and firmness are the two indicators of melon internal quality that mostly a®ect consumer acceptance.To provide guidance for fruit classification,internal quality standards was preliminarily established through sensory test,as:Melon with SSC over 12
Brix,firmness 4–5.5 kgf·cm^(-2)2 were considered as satisfactory class sample;and SSC over 10
Brix,¯rmness 3.5–6.5 kgf·cm^(-2) as average class sample.The near infrared(NIR)nondestructive detection program was set as spectra collected from the stylar-end,Brix expressed by the average SSC of inner and outer mesocarp,each cultivar of melon was detected with its own optimum integration time,and the second derivative algorithm was used to equalize them.Using wavelength selected by genetic algorithms(GA),a robust SSC model of mix-cultivar melon was established,the root mean standard error of cross-validation(RMSECV)was 0.99 and the ratio performance deviation(RPD)nearly reached 3.0,which almost could meet the accuracy requirement of 1.5
Brix.Firmness model of mix-cultivar melon was acceptable but inferior.

Firmness measurement of peach by impact force response

The impact force response of a peach impacting on a metal flat-surface was considered as nondestructive determination of firmness. The objectives were to analyze the effect of firmness, drop height, fruit mass, and impact orientation on the impact force parameters, and to establish a relationship between the impact force parameter and firmness. The effect of fruit firmness, drop height and fruit mass on the impact force parameters (coefficient of restitution, percentage of energy absorbed, and coefficient of force-time) was evaluated. The study found that the coefficient of restitution, percentage of energy absorbed, and force-time impact coefficient were significantly affected by fruit ripeness, but not affected by drop height, impact position (fruit cheek), and mass. The percentage of absorbed energy increased with ripeness, while the force-time impact coefficient and coefficient of restitution decreased with ripeness. Relationships were obtained between the three impact characteristic parameters (force-time impact coefficient, coefficient of restitution, and percentage of energy absorbed) and peach firmness using a polynomial model (R2=0.932), S model (R2=0.910), and exponential model (R2=0.941), respectively.

Nondestructive methods for determining the firmness of apple fruit flesh

Nowadays,many researches have been accomplished on the attributed quality assessment of agricultural products.Fruits have significantly contributed to these researches because of their high production and consumption,worldwide.In this paper,the nondestructive instrumental researches in the field of firmness assessment for apple fruit discussed.These researches are important for all production and distribution chain activists such as farmers,insurance companies,packaging and transportation companies,wholesalers and retailers.These studies can be used for examining texture quality,predicting the right time to harvest fruits and classifying them according to the level of ripeness and detecting the apparent and internal defects of the fruit.The apple flesh firmness measurement methods consist of acoustic and mechanical vibration methods,optical methods such as hyperspectral scattering imaging,near infrared,ultrasound and other methods.The destructive puncture test method commonly used as a reference method.Nondestructive methods are accurate and quick that is suitable for online applications.Recently,the use of artificial intelligence methods and data fusion techniques to increase the accuracy of quality measuring of the products has been considered that in the future we will see further development of these methods in measuring the firmness of the apples.

Quantitative and qualitative measurement of pear firmness based on near infrared spectroscopy and chemometrics

Firmness is one of the most important characteristics to estimate fruit maturity and quality.The potential of near-infrared(NIR)diffuse reflectance spectroscopy as a nondestructive way for pear firmness evaluation of three varieties(‘Cuiguan’,‘Xueqing’and‘Xizilv’)was studied,both quantitatively and qualitatively.NIR models were established using partial least square(PLS)methods in the spectral range of 800 to 2500 nm.For quantitative analysis,the correlation coefficient r increased with more varieties involved in the model.Best results were obtained in the model for all three varieties:rcalwas 0.934,root mean square error of calibration(RMSEC)and root mean square error of prediction(RMSEP)were 2.06 N and 3.14 N,respectively.For qualitative analysis,the overall accuracies of discriminant PLS models for classifying pears into three firmness levels:low,medium and high firmness level were not so good,percentage of samples correctly classified ranged from 70.63%to 81.25%for calibration and from 56.25%to 74.38%for validation.The results indicate that NIR spectroscopy together with PLS chemometrics method is feasible for quantitative analysis of pear firmness,however,the classification accuracy is too low to put into practical application.

Classification of the firmness of peaches by sensor fusion

The objectives of this research were to compare the performance of each individual nondestructive sensor with the destructive sensor,and to apply sensor fusion technique to explore whether a combination of sensors would give better results than a single sensor for classification of peach firmness.Tests were carried out with four peach varieties namely Royal Glory,Caterina,Tirrenia and Suidring.In this research,the three nondestructive firmness sensors acoustic firmness,low-mass impact and micro-deformation impact were used to measure firmness.A Bayesian classifier was chosen to provide a classification into three categories,namely soft,intermediate and hard.High level fusion technique was performed by using identity declaration provided by each sensor.The data fusion system processed the information of the sensors to output the fused data.The result of the high level fusion was compared with the classification provided by an unsupervised algorithm based on destructive reference measurement.The fusion process of the nondestructive sensors provided some improvements in the firmness classification;the error rate varied from 25%to 19%for individual sensor.Furthermore,the results of fusion process by using three sensors decreased the error rate from 19%to 13%.This research demonstrated that the fused systems provided more complete and complementary information and,thus,were more effective than individual sensors in the firmness classification of peaches.

Non-destructive detection of the fruit firmness of Korla fragrant pear based on electrical properties

In order to achieve the non-destructive detection of the firmness of Korla fragrant pear during the ripening period,the characteristic variables integrating the parallel equivalent inductance(Lp),quality factor(Q),parallel equivalent capacitance(Cp),dissipation factor(D),parallel equivalent resistance(Rp)and impedance(Z)were formulated through principal component analysis(PCA).Further,based on the characteristic variables,the models were established for predicting the firmness of Korla fragrant pear by using the generalized regression neural network(GRNN)and back-propagation neural network(BPNN).The results showed that firmness has significant correlations with the six electrical parameters.The first two principal components(PCs)were selected as the characteristic variables of the electrical parameters.GRNN exhibited the best performance in predicting firmness(R2=0.9628,RMSE=0.383).The results could provide important references for non-destructive detection of the quality of Korla fragrant pear.

Detection of apple firmness with a novel loudspeaker-based excitation device

Firmness is one of the important indices to evaluate the internal quality of fruit.In this study,a noncontact loudspeaker-based detection system was developed to evaluate apple firmness.The structural parameters of the excitation device were modified in the single-factor experiments,and the best combination of structural parameters was that the inner diameter of the gasket was 40 mm;the distance between fruit surface and loudspeaker was 95 mm.Besides,the proper posture style was that the apple was placed with its stem upward.After the modification of the Laser Doppler Vibrometer(LDV)method,the vibration response signals of 48 apples were measured to establish the firmness prediction model.The results showed that the better prediction performance of stiffness was obtained in multiple models.The Back Propagation Neural Network(BPNN)model had the best prediction performance by using parameters of elasticity index(EI),the peak value at the second resonance frequency f_(2)(A_(2)),and peak area S,with a correlation coefficient of prediction(r_(p))of 0.914;root mean square error of prediction(RMSEP)of 0.491 N/mm.Therefore,the proposed detection system is feasible to nondestructively detect apple firmness,which has the potential to be applied in online detection.

不同超高压处理对DFD牛肉肉色及货架期的影响

为降低DFD(dark,firm and dry)牛肉初始菌落总数,延长真空包装DFD牛肉货架期并改善肉色,以不同压力(200、400、600 MPa)配合不同加压时间(5、10 min)的超高压处理为实验组,以空白处理为对照组,测定真空包装DFD牛肉在(2±2)℃条件下贮藏0、2、4、6、8、12、16 d后的肉色、表观肉色图像、pH值、微生物和3种肌红蛋白相对含量,探究超高压处理对DFD牛肉货架期及肉色的影响,进而探寻适合DFD牛肉肉色改善和货架期延长的超高压处理条件。结果表明:超高压能显著提高DFD牛肉的亮度值、红度值和黄度值(P<0.05),增加氧合肌红蛋白的相对含量,降低高铁肌红蛋白的相对含量,但过高压力(600 MPa)会使DFD牛肉呈现粉红色;超高压处理能显著降低DFD牛肉初始菌落总数(P<0.05),200 MPa(5、10 min)处理组使DFD牛肉初始菌落总数降低0.6、0.8(lg(CFU/g)),400 MPa(5、10 min)处理组降低1.1、1.3(lg(CFU/g)),600 MPa(5、10 min)处理组降低1.7、2.0(lg(CFU/g)),有效抑制了微生物在贮藏期间的生长;对照组在12 d时已腐败,200 MPa处理组在16 d时达到腐败限值,而冷藏16 d,400、600 MPa处理组均未腐败;400 MPa是有效改善DFD牛肉肉色、延长其货架期的最适压力,保压时间的延长对肉色和货架期的影响不显著(P>0.05)。综合考虑,400 MPa-10 min是超高压处理DFD牛肉的最适参数,能改善DFD牛肉肉色,同时将货架期至少延长5 d以上。

Innovation and Firm Co-ownership Network in China’s Electric Vehicle Industry

Firms are embedded in complex networks,where diverse ideas combine and generate new ideas.Shareholders of firms are of-ten seen as critical external resources that have significant influence on firm innovation.The current literature tends to focus on the rela-tionship between firms and their shareholders,while paying less attention to the connections between firms with the same shareholders.This article identifies two types of network spillover effects,intra-city network effect and inter-city network effect,by visualizing the co-ownership networks in China’s electric vehicle(EV)industry.We find that firms with the same shareholders,which are defined as co-owned EV firms,are more innovative than non-co-owned ones.Furthermore,there are two dominant types of firm co-ownership ties formed by corporate and financial institution shareholders.While corporate shareholders help exploiting local tacit knowledge,financial institutions are more active in bridging inter-city connections.The conclusion is confirmed at both firm and city levels.This paper theor-izes the firm co-ownership network as a new form of institutional proximity and tested the result empirically.For policy consideration,we have emphasized the importance of building formal or informal inter-firm network,and the government should further enhance the knowledge flow channel by institutional construction.

GHG Emissions of Italian Unlisted Firms and Bank Debt

In this paper I investigate the effect of the greenhouse gas emissions of a sample of 478 Italian unlisted firms on their bank debt,in the context of the growing attention and awareness for climate change issue.My findings show that unlisted firms generating low levels of greenhouse gas emissions borrow less long-term,short term,and total bank debt than unlisted firms generating high levels of greenhouse gas emissions,to finance their growth opportunities.Being the first work analyzing this topic,to the best of my knowledge,further empirical research could also investigate the impact of greenhouse gas emissions on the bank financing of unlisted firms of different countries,representing specific cultural and political approaches towards climate change problems.

The efficacy study of trinity permeation synergism on anti-aging

Background:More and more consumers are paying attention to skin rejuvenation.However,there is a lack of a non-invasive and efficient solution.Objective:To evaluate the efficacy of a trinity permeation synergism(TPS),which consists of a firming essence,an atomizer and a photoelectric penetrator,for facial anti-aging efficacy.Material and methods:In this work,in vitro cell experiments and human efficacy study were used to evaluate the firming and anti-wrinkle effects.Cell experiments were used to verify the effect of the firming essence on the cell proliferation,migration,and anti-inflammation in keratinocytes(HaCaT),and on the gene expression levels of type I and type III collagen(Col-1 and Col-3)and type I matrix metalloproteinase(MMP-1)in human skin fibroblasts(HSF).After in vitro test,60 women aged 35–60 years were enrolled in the randomized test,of which 30 subjects were randomly selected to be the experimental group and treated with the TPS system,while the left 30 subjects were treated with the firming essence only considered as control.After 28 days,skin elasticity,skin redness value,and skin wrinkles were measured to evaluate the efficacy of the TPS system.Results:Cell experiments showed that the firming essence can significantly improve the proliferation and the migration of HaCaT cells.It also promoted the expression level of Col-1 and Col-3 gene,and inhibited the expression level of MMP-1 gene in HSF cells.After confirming the efficacy of firming essence,the efficacy benefit of the TPS was further studied.The 28-day tests show that combined use firming essence with atomizer and penetrator can significantly increase skin elasticity,reduce skin hemoglobin value and skin wrinkles on Day 28.Moreover,all the mentioned improvements are significantly better than that in the control group.Conclusion:Through efficient delivery in the whole process,TPS boosts the efficacy of active components in the firming essence.TPS offers an efficient,non-invasive,and convenient way for enhanced facial rejuvenation efficacy.

Turning Dreams Into Reality China is committed to helping African countries to build their space capability

An important feature of China developing its aerospace industry is its insistence on self-reliance and independent innovation,because China firmly believes that aerospace is a hi-tech industry and high core technologies cannot be bought.Only by mastering core technologies can China firmly grasp the initiative in development.