A new image-based tool for the high throughput phenotyping of pollen viability: evaluation of inter- and intra-cultivar diversity in grapevine

Pollen viability, longevity, and function in angiosperms: key drivers and prospects for improvement

Pollen grains are central to sexual plant reproduction and their viability and longevity/storage are critical for plant physiology, ecology, plant breeding, and many plant product industries. Our goal is to present progress in assessing pollen viability/longevity along with recent advances in our understanding of the intrinsic and environmental factors that determine pollen performance: the capacity of the pollen grain to be stored, germinate, produce a pollen tube, and fertilize the ovule. We review current methods to measure pollen viability, with an eye toward advancing basic research and biotechnological applications. Importantly, we review recent advances in our understanding of how basic aspects of pollen/stigma development, pollen molecular composition, and intra- and intercellular signaling systems interact with the environment to determine pollen performance. Our goal is to point to key questions for future research, especially given that climate change will directly impact pollen viability/longevity. We find that the viability and longevity of pollen are highly sensitive to environmental conditions that affect complex interactions between maternal and paternal tissues and internal pollen physiological events. As pollen viability and longevity are critical factors for food security and adaptation to climate change, we highlight the need to develop further basic research for better understanding the complex molecular mechanisms that modulate pollen viability and applied research on developing new methods to maintain or improve pollen viability and longevity.

Identification of two mutant JASON-RELATED genes associated with unreduced pollen production in potato

KEY MESSAGE

Multiple QTLs control unreduced pollen production in potato. Two major-effect QTLs co-locate with mutant alleles of genes with homology to AtJAS, a known regulator of meiotic spindle orientation. In diploid potato the production of unreduced gametes with a diploid (2n) rather than a haploid (n) number of chromosomes has been widely reported. Besides their evolutionary important role in sexual polyploidisation, unreduced gametes also have a practical value for potato breeding as a bridge between diploid and tetraploid germplasm. Although early articles argued for a monogenic recessive inheritance, the genetic basis of unreduced pollen production in potato has remained elusive. Here, three diploid full-sib populations were genotyped with an amplicon sequencing approach and phenotyped for unreduced pollen production across two growing seasons. We identified two minor-effect and three major-effect QTLs regulating this trait. The two QTLs with the largest effect displayed a recessive inheritance and an additive interaction. Both QTLs co-localised with genes encoding for putative AtJAS homologs, a key regulator of meiosis II spindle orientation in Arabidopsis thaliana. The function of these candidate genes is consistent with the cytological phenotype of mis-oriented metaphase II plates observed in the parental clones. The alleles associated with elevated levels of unreduced pollen showed deleterious mutation events: an exonic transposon insert causing a premature stop, and an amino acid change within a highly conserved domain. Taken together, our findings shed light on the natural variation underlying unreduced pollen production in potato and will facilitate interploidy breeding by enabling marker-assisted selection for this trait.

RootPainter: deep learning segmentation of biological images with corrective annotation

Convolutional neural networks (CNNs) are a powerful tool for plant image analysis, but challenges remain in making them more accessible to researchers without a machine-learning background. We present RootPainter, an open-source graphical user interface based software tool for the rapid training of deep neural networks for use in biological image analysis. We evaluate RootPainter by training models for root length extraction from chicory (Cichorium intybus L.) roots in soil, biopore counting, and root nodule counting. We also compare dense annotations with corrective ones that are added during the training process based on the weaknesses of the current model. Five out of six times the models trained using RootPainter with corrective annotations created within 2 h produced measurements strongly correlating with manual measurements. Model accuracy had a significant correlation with annotation duration, indicating further improvements could be obtained with extended annotation. Our results show that a deep-learning model can be trained to a high accuracy for the three respective datasets of varying target objects, background, and image quality with < 2 h of annotation time. They indicate that, when using RootPainter, for many datasets it is possible to annotate, train, and complete data processing within 1 d.

Inflorescence Traits and Floral Quality Parameters in Promising Olive Clones (cv Leccino): Influence of the Canopy Position

In olive (Olea europaea L.), the floral quality is a key feature affecting the final fruit crop. The aim of this study was to evaluate the inflorescence traits and the floral quality parameters of three clones of Leccino cultivar (L 1.3, L 1.4, L 1.9). To assess a possible effect of light limitations on these parameters two canopy zones, internal (IZ) and external (EZ), were considered. The inflorescences were collected over two consecutive years in order to establish: (i) the characteristics of inflorescences (length, flowers per inflorescence) and flowers (open and perfect flowers); (ii) the ovary structure by histological analysis; and (iii) the viability and germination of pollen grains by in vitro culture. The preliminary results highlighted some differences among clones. The L 1.9 was the less affected by the canopy position for inflorescence morphological traits, and the presence of ovaries with at least three fully developed ovules denoting a high female fertility. Regardless of the canopy position, L 1.4 showed the highest pollen viability, suggesting its possible use as pollinator. The lower sensitivity of female and male floral organs to partial shading of L 1.9 and L 1.4 needs further investigations aimed at evaluating their suitability in high-density olive orchards.

CAND1 is required for pollen viability in Arabidopsis thaliana-a test of the adaptive exchange hypothesis

The dynamic assembly of SKP1•CUL1•F-box protein (SCF) ubiquitin ligases is important for protein ubiquitination and degradation. This process is enabled by CAND1, which exchanges F-box proteins associated with the common CUL1 scaffold, and thereby, recycles the limited CUL1 core and allows diverse F-box proteins to assemble active SCFs. Previous human cell biological and computational studies have led to the adaptive exchange hypothesis, which suggests that the CAND1-mediated exchange confers plasticity on the SCF system, allowing cells to tolerate large variations in F-box protein expression. Here, we tested this hypothesis using Arabidopsis thaliana, a multicellular organism expressing hundreds of F-box protein genes at variable levels in different tissues. The cand1 null mutant in Arabidopsis is viable but produce almost no seeds. Bioinformatic, cell biological, and developmental analyses revealed that the low fertility in the cand1 mutant is associated with cell death in pollen, where the net expression of F-box protein genes is significantly higher than any other Arabidopsis tissue. In addition, we show that the transmission efficiency of the cand1 null allele was reduced through the male but not the female gametophyte. Our results suggest that CAND1 activity is essential in cells or tissues expressing high levels of F-box proteins. This finding is consistent with the proposed adaptive exchange hypothesis, demonstrating the necessity of the evolutionarily conserved CAND1-mediated exchange system in the development of a multicellular organism.

Genetic variation and association analyses identify genes linked to fruit set-related traits in grapevine

Grapevine is one of the most valuable fruit crops in the world. Adverse environmental conditions reduce fruit quality and crop yield, so understanding the genetic and molecular mechanisms determining crop yield components is essential to optimize grape production. The analysis of a diverse collection of grapevine cultivars allowed us to evaluate the relationship between fruit set-related components of yield, including the incidence of reproductive disorders such as coulure and millerandage. The collection displayed a great phenotypic variation that we surveyed in a genetics association study using 15,309 single nucleotide polymorphisms (SNPs) detected in the sequence of 289 candidate genes scattered across the 19 grapevine linkage groups. After correcting statistical models for population structure and linkage disequilibrium effects, 164 SNPs from 34 of these genes were found to associate with fruit set-related traits, supporting a complex polygenic determinism. Many of them were found in the sequence of different putative MADS-box transcription factors, a gene family related with plant reproductive development control. In addition, we observed an additive effect of some of the associated SNPs on the phenotype, suggesting that advantageous alleles from different loci could be pyramided to generate superior cultivars with optimized fruit production.

Somatic variants for seed and fruit set in grapevine

BACKGROUND

Grapevine reproductive development has direct implications on yield. It also impacts on berry and wine quality by affecting traits like seedlessness, berry and bunch size, cluster compactness and berry skin to pulp ratio. Seasonal fluctuations in yield, fruit composition and wine attributes, which are largely driven by climatic factors, are major challenges for worldwide table grape and wine industry. Accordingly, a better understanding of reproductive processes such as gamete development, fertilization, seed and fruit set is of paramount relevance for managing yield and quality. With the aim of providing new insights into this field, we searched for clones with contrasting seed content in two germplasm collections.

RESULTS

We identified eight variant pairs that seemingly differ only in seed-related characteristics while showing identical genotype when tested with the GrapeReSeq_Illumina_20K_SNP_chip and several microsatellites. We performed multi-year observations on seed and fruit set deriving from different pollination treatments, with special emphasis on the pair composed by Sangiovese and its seedless variant locally named Corinto Nero. The pollen of Corinto Nero failed to germinate in vitro and gave poor berry set when used to pollinate other varieties. Most berries from both open- and cross-pollinated Corinto Nero inflorescences did not contain seeds. The genetic analysis of seedlings derived from occasional Corinto Nero normal seeds revealed that the few Corinto Nero functional gametes are mostly unreduced. Moreover, three genotypes, including Sangiovese and Corinto Nero, were unexpectedly found to develop fruits without pollen contribution and occasionally showed normal-like seeds. Five missense single nucleotide polymorphisms were identified between Corinto Nero and Sangiovese from transcriptomic data.

CONCLUSIONS

Our observations allowed us to attribute a seedlessness type to some variants for which it was not documented in the literature. Interestingly, the VvAGL11 mutation responsible for Sultanina stenospermocarpy was also discovered in a seedless mutant of Gouais Blanc. We suggest that Corinto Nero parthenocarpy is driven by pollen and/or embryo sac defects, and both events likely arise from meiotic anomalies. The single nucleotide polymorphisms identified between Sangiovese and Corinto Nero are suitable for testing as traceability markers for propagated material and as functional candidates for the seedless phenotype.

Reproductive Biology of Olive Trees (Arbequina cultivar) at the Northern Limit of Their Distribution Areas

In recent years, North-western Spain has experienced an increase in the cultivated area of olive trees. The main propitious areas for olive groves are the Miño and Sil basins, as a consequence of their Oceanic climate with Mediterranean influence. The objective of this study is to determine the characteristics of reproductive biology, phenological and aerobiological behaviour of olive trees in the most northerly new plantation areas of the Iberian Peninsula. The study was carried out in an olive grove growing Olea europaea L. cv. ‘Arbequina’ located in Quiroga (Lugo) from 2016 to 2018. The phenological observations were based upon the main growth stages following the Biologische Bundesanstalt Bundessortenamt and Chemical industry (BBCH) scale. To predict the onset of flowering, a thermal time model was used in order to quantify the chill requirements, and growing degree-days were applied to determine the heat requirement. The production, viability and germination rates of Olea pollen were evaluated from samples selected in nine individual trees for the phenological survey. The aerobiological study was conducted by means of a Hirst-type pollen trap located in the centre of the olive grove. The vegetative period of the olive tree in the study area lasted an average of 259 days. The important phenological stage 6 (flowering) was the shortest stage. An average of 704 Chilling Hours (CH) with a threshold of 2.5 °C was required to overcome the chilling period, 1139 Growing Degree Days (GDD) for the beginning of flowering, and 4463 GDD for harvest. The pollen production per anther was 82589 grains (± 14084 pollen grains), with a rate of 81% viability and 12% pollen tube germination. The main pollen season started on average on May 20th and ended on June 16th with an average duration of 27 days and an annual pollen integral of 833 pollen grains. The low pollen concentrations could be a consequence of the Northern location of the forest, in a bioclimatic transition zone between the Eurosiberian and the Mediterranean areas, at the limit of olive tree distribution.

Hazelnut Pollen Phenotyping Using Label-Free Impedance Flow Cytometry

Impedance flow cytometry (IFC) is a versatile lab-on-chip technology which enables fast and label-free analysis of pollen grains in various plant species, promising new research possibilities in agriculture and plant breeding. Hazelnut is a monoecious, anemophilous species, exhibiting sporophytic self-incompatibility. Its pollen is dispersed by wind in midwinter when temperatures are still low and relative humidity is usually high. Previous research found that hazelnut can be characterized by high degrees of pollen sterility following a reciprocal chromosome translocation occurring in some cultivated genotypes. In this study, IFC was used for the first time to characterize hazelnut pollen biology. IFC was validated via dye exclusion in microscopy and employed to (i) follow pollen hydration over time to define the best pre-hydration treatment for pollen viability evaluation; (ii) test hazelnut pollen viability and sterility on 33 cultivars grown in a collection field located in central Italy, and two wild hazelnuts. The accessions were also characterized by their amount and distribution of catkins in the tree canopy. Pollen sterility rate greatly varied among hazelnut accessions, with one main group of highly sterile cultivars and a second group, comprising wild genotypes and the remaining cultivars, producing good quality pollen. The results support the hypothesis of recurring reciprocal translocation events in Corylus avellana cultivars, leading to the observed gametic semi-sterility. The measured hazelnut pollen viability was also strongly influenced by pollen hydration (R adj 2 = 0.83, P ≤ 0.0001) and reached its maximum at around 6 h of pre-hydration in humid chambers. Viable and dead pollen were best discriminated at around the same time of pollen pre-hydration, suggesting that high humidity levels are required for hazelnut pollen to maintain its functionality. Altogether, our results detail the value of impedance flow cytometry for high throughput phenotyping of hazelnut pollen. Further research is required to clarify the causes of pollen sterility in hazelnut, to confirm the role of reciprocal chromosome translocations and to investigate its effects on plant productivity.

Quantitative methods in microscopy to assess pollen viability in different plant taxa

High-quality pollen is a prerequisite for plant reproductive success. Pollen viability and sterility can be routinely assessed using common stains and manual microscope examination, but with low overall statistical power. Current automated methods are primarily directed towards the analysis of pollen sterility, and high throughput solutions for both pollen viability and sterility evaluation are needed that will be consistent with emerging biotechnological strategies for crop improvement. Our goal is to refine established labelling procedures for pollen, based on the combination of fluorescein (FDA) and propidium iodide (PI), and to develop automated solutions for accurately assessing pollen grain images and classifying them for quality. We used open-source software programs (CellProfiler, CellProfiler Analyst, Fiji and R) for analysis of images collected from 10 pollen taxa labelled using FDA/PI. After correcting for image background noise, pollen grain images were examined for quality employing thresholding and segmentation. Supervised and unsupervised classification of per-object features was employed for the identification of viable, dead and sterile pollen. The combination of FDA and PI dyes was able to differentiate between viable, dead and sterile pollen in all the analysed taxa. Automated image analysis and classification significantly increased the statistical power of the pollen viability assay, identifying more than 75,000 pollen grains with high accuracy (R² = 0.99) when compared to classical manual counting. Overall, we provide a comprehensive set of methodologies as baseline for the automated assessment of pollen viability using fluorescence microscopy, which can be combined with manual and mechanized imaging systems in fundamental and applied research on plant biology. We also supply the complete set of pollen images (the FDA/PI pollen dataset) to the scientific community for future research.

SpaTemHTP: A Data Analysis Pipeline for Efficient Processing and Utilization of Temporal High-Throughput Phenotyping Data

The rapid development of phenotyping technologies over the last years gave the opportunity to study plant development over time. The treatment of the massive amount of data collected by high-throughput phenotyping (HTP) platforms is however an important challenge for the plant science community. An important issue is to accurately estimate, over time, the genotypic component of plant phenotype. In outdoor and field-based HTP platforms, phenotype measurements can be substantially affected by data-generation inaccuracies or failures, leading to erroneous or missing data. To solve that problem, we developed an analytical pipeline composed of three modules: detection of outliers, imputation of missing values, and mixed-model genotype adjusted means computation with spatial adjustment. The pipeline was tested on three different traits (3D leaf area, projected leaf area, and plant height), in two crops (chickpea, sorghum), measured during two seasons. Using real-data analyses and simulations, we showed that the sequential application of the three pipeline steps was particularly useful to estimate smooth genotype growth curves from raw data containing a large amount of noise, a situation that is potentially frequent in data generated on outdoor HTP platforms. The procedure we propose can handle up to 50% of missing values. It is also robust to data contamination rates between 20 and 30% of the data. The pipeline was further extended to model the genotype time series data. A change-point analysis allowed the determination of growth phases and the optimal timing where genotypic differences were the largest. The estimated genotypic values were used to cluster the genotypes during the optimal growth phase. Through a two-way analysis of variance (ANOVA), clusters were found to be consistently defined throughout the growth duration. Therefore, we could show, on a wide range of scenarios, that the pipeline facilitated efficient extraction of useful information from outdoor HTP platform data. High-quality plant growth time series data is also provided to support breeding decisions. The R code of the pipeline is available at https://github.com/ICRISAT-GEMS/SpaTemHTP.

High-throughput phenotyping of brachiaria grass seeds using free access tool for analyzing X-ray images

New approaches based on image analysis can assist in phenotyping of biological characteristics, serving as support for decision-making in modern agribusiness. The aim of this study was to propose a method of high-throughput phenotyping of free access for processing of 2D X-ray images of brachiaria grass (Brachiaria ruziziensis cv. Ruziziensis) seeds, as well as correlate the parameters linked to the physiological potential of the seeds. The study was carried out by means of automated analysis of X-ray images of seeds in which a macro, called PhenoXray, was developed, responsible for digital image processing, for which a series of descriptors were obtained. After the X-ray analysis, a germination test was performed on the seeds and, from this, variables related to the physiological quality of the seeds were obtained. The use of the macro PhenoXray allowed large-scale phenotyping of seed X-rays in a simple, rapid, robust, and totally free manner. This study confirmed that the methodology is efficient for obtaining morphometric data and tissue integrity data in Brachiaria ruziziensis seeds and that parameters such as relative density, integrated density, and seed filling are closely related to the physiological attributes of seed quality.

Optimizing pollencounter for high throughput phenotyping of pollen quality in tomatoes

The macro "PollenCounter" in ImageJ was initially developed to assess pollen viability in grapevine. We set out to see if PollenCounter could be used to assess pollen number and viability in tomatoes.•We tested different optimization scenarios by adjusting the pollen size (100-900, 200-900 pixel2) and circularity of pollen grains (0.4-1, 0.5-1, and 0.6-1) on 31 microscopic images of stained tomato pollen. Both total pollen number and proportion of viable pollen were positively and significantly correlated with the outputs from manual counting. The scenario with 100-900 pixel2 pollen size and 0.4-1 circularity had the highest association for pollen number (r = 0.99) and pollen viability (r = 0.86). PollenCounter is 32-fold faster than manual counting.•We added a command to the macro to automatically save the outputs containing the number of total and viable pollen, avoiding transcription errors inherent to manual counting.•We successfully applied the optimized PollenCounter to discriminate tomato genotypes based on pollen number and pollen viability under heat stress. Our results show that PollenCounter, as an open-access macro, can be customized and improved to meet users' needs. The use of PollenCounter can save time and money in pollen quality assessment. We outline the steps to optimize the macro for other samples or crop species. The optimized macro could allow efficient screening of a large germplasm collection for pollen thermo-tolerance and selection of best thermo-tolerant individuals in breeding programs.

An optimized histological proceeding to study the female gametophyte development in grapevine

BACKGROUND

Reproductive success in seed plants depends on a healthy fruit and seed set. Normal seed development in the angiosperms requires the production of functional female gametophytes. This is particularly evident in seedless cultivars where defects during megagametophyte's developmental processes have been observed through cytohistological analysis. Several protocols for embryo sac histological analyses in grapevine are reported in literature, mainly based on resin- or paraffin-embedding approaches. However their description is not always fully exhaustive and sometimes they consist of long and laborious steps. The use of different stains is also documented, some of them, such as hematoxylin, requiring long oxidation periods of the dye-solution before using it (from 2 to 6 months) and/or with a differentiation step not easy to handle. Paraffin-embedding associated to examination with light microscope is the simplest methodology, and with less requirements in terms of expertise and costs, achieving a satisfactory resolution for basic histological observations. Safranin O and fast green FCF is an easy staining combination that has been applied in embryological studies of several plant species.

RESULTS

Here we describe in detail a paraffin-embedding method for the examination of grapevine ovules at different phenological stages. The histological sample preparation process takes 1 day and a half. Sections of 5 µm thickness can be obtained and good contrast is achieved with the safranin O and fast green FCF staining combination. The method allows the observation of megasporogenesis and megagametogenesis events in the different phenological stages examined.

CONCLUSIONS

The histological sample preparation process proposed here can be used as a routine procedure to obtain embedded ovaries or microscope slides that would require further steps for examination. We suggest the tested staining combination as a simple and viable technique for basic screenings about the presence in grapevine of a normally and fully developed ovule with embryo sac cells, which is therefore potentially functional.

Maize tassels detection: a benchmark of the state of the art

BACKGROUND

The population of plants is a crucial indicator in plant phenotyping and agricultural production, such as growth status monitoring, yield estimation, and grain depot management. To enhance the production efficiency and liberate labor force, many automated counting methods have been proposed, in which computer vision-based approaches show great potentials due to the feasibility of high-throughput processing and low cost. In particular, with the success of deep learning, more and more deeper learning-based approaches are introduced to deal with agriculture automation. Since different detection- and regression-based counting models have distinct characteristics, how to choose an appropriate model given the target task at hand remains unexplored and is important for practitioners.

RESULTS

Targeting in-field maize tassels as a representative case study, the goal of this work is to present a comprehensive benchmark of state-of-the-art object detection and object counting methods, including Faster R-CNN, YOLOv3, FaceBoxes, RetinaNet, and the leading counting model of maize tassels-TasselNet. We create a Maize Tassel Detection Counting (MTDC) dataset by supplementing bounding box annotations to the Maize Tassels Counting (MTC) dataset to allow the training of detection models. We investigate key factors effecting the practical applications of the models, such as convergence behavior, scale robustness, speed-accuracy trade-off, as well as parameter sensitivity. Based on our benchmark, we summarise the advantages and limitations of each method and suggest several possible directions to improve current detection- and regression-based counting approaches to benefit next-generation intelligent agriculture.

CONCLUSIONS

Current state-of-the-art detection- and regression-based counting approaches can all achieve a relatively high degree of accuracy when dealing with in-field maize tassels, with at least 0.85 R 2 values and 28.2% rRMSE error. While detection-based methods are more robust than regression-based methods in scale variations and can infer extra information (e.g., object positions and sizes), the latter ones have significantly faster convergence behaviors and inference speed. To choose an appropriate in-filed plant counting method, accuracy, robustness, speed and some other algorithm-specific factors should be taken into account with the same priority. This work sheds light on different aspects of existing detection and counting approaches and provides guidance on how to tackle in-field plant counting. The MTDC dataset is made available at https://git.io/MTDC.

Accelerating Breeding for Heat Tolerance in Tomato (Solanum lycopersicum L.): An Integrated Approach

Heat stress is a major limiting factor for crop productivity. Tomato is highly sensitive to heat stress, which can result in a total yield loss. To adapt to current and future heat stress, there is a dire need to develop heat tolerant cultivars. Here, we review recent attempts to improve screening for heat tolerance and to exploit genetic and genomic resources in tomatoes. We provide key factors related to phenotyping environments and traits (morphological, physiological, and metabolic) to be considered to identify and breed thermo-tolerant genotypes. There is significant variability in tomato germplasm that can be harnessed to breed for thermo-tolerance. Based on our review, we propose that the use of advanced backcross populations and chromosome segments substitution lines is the best means to exploit variability for heat tolerance in non-cultivated tomato species. We applied a meta quantitative trait loci (MQTL) analysis on data from four mapping experiments to co-localize QTL associated with heat tolerance traits (e.g., pollen viability, number of pollen, number of flowers, style protrusion, style length). The analysis revealed 13 MQTL of which 11 were composed of a cluster of QTL. Overall, there was a reduction of about 1.5-fold in the confidence interval (CI) of the MQTL (31.82 cM) compared to the average CI of individual QTL (47.4 cM). This confidence interval is still large and additional mapping resolution approaches such as association mapping and multi-parent linkage mapping are needed. Further investigations are required to decipher the genetic architecture of heat tolerance surrogate traits in tomatoes. Genomic selection and new breeding techniques including genome editing and speed breeding hold promise to fast-track development of improved heat tolerance and other farmer- and consumer-preferred traits in tomatoes.

Prediction Method for Torrefied Rice Husk Based on Gray-scale Analysis

Torrefaction pretreatment has recently gained attention for the potential improvement in biomass properties. Otherwise, visible image-processing technology for analyzing properties of torrefied biomass was evaluated for possible use in the future online process control. In this study, torrefied rice husk from different torrefaction temperatures (180-330 °C) was obtained. After torrefaction, the biochar was characterized to determine the effects of torrefaction temperature on the properties, including the proximate analysis, solid yield (SY), and higher heating values. In addition, the color values, including red-green-blue (RGB) values, and grayscale (GS) of torrefied rice husk, were measured. The results show that the fixed carbon and ash increased from 17.39 to 35.13 and 7.06 to 38.41%, respectively, while volatile matters decreased from 71.47% to a minimum of 22.89% with the increase of torrefaction temperature from 105 to 330 °C. The SY remained higher than 46% even at the most severe torrefaction condition because of the high ash content and high remaining lignin. Moreover, the higher heating values of torrefied rice husk were increased from 14.80 to 17.82 MJ/kg when increased the pretreatment temperature. RGB values were decreased with the increase of torrefaction temperature. The GS analysis results show that the color of torrefied rice husk changed from yellow to brown at light torrefaction and black at severe torrefaction. GS of torrefied rice husk shows a good correlation (R = 0.9998) with torrefaction temperature. Prediction equations with higher fitting degree between GS and proximate analysis (R 2 > 0.9900), high heat values (R 2 = 0.9999), and SY (R 2 = 0.9979), which are developed to reflect the changing characteristics of torrefied rice husk. The results show that the prediction method based on GS is a promising technology to measure the properties of torrefied rice husk.

Phenotypic, Hormonal, and Genomic Variation Among Vitis vinifera Clones With Different Cluster Compactness and Reproductive Performance

Previous studies showed that the number of berries is a major component of the compactness level of the grapevine clusters. Variation in number of fruits is regulated by events occurring in the fruitset, but also before during the flower formation and pollination, through factors like the initial number of flowers or the gametic viability. Therefore, the identification of the genetic bases of this variation would provide an invaluable knowledge of the grapevine reproductive development and useful tools for managing yield and cluster compactness. We performed the phenotyping of four clones (two compact and two loose clones) of the Tempranillo cultivar with reproducible different levels of cluster compactness over seasons. Measures of reproductive performance included flower number per inflorescence, berry number per cluster, fruitset, coulure, and millerandage indices. Besides, their levels of several hormones during the inflorescence and flower development were determined, and their transcriptomes were evaluated at critical time points (just before the start and at the end of flowering). For some key reproductive traits, like number of berries per cluster and number of seeds per berry, clones bearing loose clusters showed differences with the compact clones and also differed from each other, indicating that each one follows different paths to produce loose clusters. Variation between clones was observed for abscisic acid and gibberellins levels at particular development stages, and differences in GAs could be related to phenotypic differences. Likewise, various changes between clones were found at the transcriptomic level, mostly just before the start of flowering. Several of the differentially expressed genes between one of the loose clones and the compact clones are known to be over-expressed in pollen, and many of them were related to cell wall modification processes or to the phenylpropanoids metabolism. We also found polymorphisms between clones in candidate genes that could be directly involved in the variation of the compactness level.