Plant Methods

Leaf water content (LWC) significantly affects rice growth and development. Real-time monitoring of rice leaf water status is essential to obtain high yield and water use efficiency of rice plants with precise irrigation regimes in rice fields. Hyperspectral remote sensing technology is widely used in monitoring crop water status because of its rapid, nondestructive, and real-time characteristics. Recently, multi-source data have been attempted to integrate into a monitored model of crop water status based on spectral indices. However, there are fewer studies using spectral index model coupled with multi-source data for monitoring LWC in rice plants. Therefore, 2-year field experiments were conducted with three irrigation regimes using four rice cultivars in this study. The multi-source data, including canopy ecological factors and physiological parameters, were incorporated into the vegetation index to accurately predict LWC in rice plants. The results presented that the model accuracy of rice LWC estimation after combining data from multiple sources improved by 6–44% compared to the accuracy of a single spectral index normalized difference index (ND). Additionally, the optimal prediction accuracy of rice LWC was produced using a machine algorithm of gradient boosted decision tree (GBDT) based on the combination of ND(1287,1673) and crop water stress index (CWSI) (R2 = 0.86, RMSE = 0.01). The machine learning estimation model constructed based on multi-source data fully utilizes the spectral information and considers the environmental changes in the crop canopy after introducing multi-source data parameters, thus improving the performance of spectral technology for monitoring rice LWC. The findings may be helpful to the water status diagnosis and accurate irrigation management of rice plants.

Crop breeding should be accelerated to address global warming and climate change. Wheat (Triticum aestivum L.) is a major food crop. Speed breeding (SB) and speed vernalization (SV) techniques for spring and winter wheat have recently been established. However, there are few practical examples of these strategies being used economically and efficiently in breeding programs. We aimed to establish and evaluate the performance of a breeder-friendly and energy-saving generation acceleration system by modifying the SV + SB system. In this study, a four-generation advancement system for wheat (regardless of its growth habits) was established and evaluated using an energy-efficient extended photoperiod treatment. A glasshouse with a 22-hour photoperiod that used 10 h of natural sunlight and 12 h of LED lights, and minimized temperature control during the winter season, was successful in accelerating generation. Even with one or two field tests, modified speed breeding (mSB) combined with a speed vernalization system (SV + mSB) reduced breeding time by more than half compared to traditional field-based methods. When compared to the existing SV + SB system, the SV + mSB system reduced energy use by 80% to maintain a 22-hour photoperiod. Significant correlations were found between the SV + mSB and field conditions in the number of days to heading (DTH) and culm length (CL). Genetic resources, recombinant inbred lines, and breeding materials that exhibited shorter DTH and CL values under SV + mSB conditions showed the same pattern in the field. The results of our SV + mSB model, as well as its practical application in wheat breeding programs, are expected to help breeders worldwide incorporate generation acceleration systems into their conventional breeding programs.

We developed and characterised a highly mutagenised TILLING population of the barley (Hordeum vulgare) cultivar Golden Promise. Golden Promise is the ‘reference’ genotype for barley transformation and a primary objective of using this cultivar was to be able to genetically complement observed mutations directly in order to prove gene function. Importantly, a reference genome assembly of Golden Promise has also recently been developed. As our primary interest was to identify mutations in genes involved in meiosis and recombination, to characterise the population we focused on a set of 46 genes from the literature that are possible meiosis gene candidates. Sequencing 20 plants from the population using whole exome capture revealed that the mutation density in this population is high (one mutation every 154 kb), and consequently even in this small number of plants we identified several interesting mutations. We also recorded some issues with seed availability and germination. We subsequently designed and applied a simple two-dimensional pooling strategy to identify mutations in varying numbers of specific target genes by Illumina short read pooled-amplicon sequencing and subsequent deconvolution. In parallel we assembled a collection of semi-sterile mutants from the population and used a custom exome capture array targeting the 46 candidate meiotic genes to identify potentially causal mutations. We developed a highly mutagenised barley TILLING population in the transformation competent cultivar Golden Promise. We used novel and cost-efficient screening approaches to successfully identify a broad range of potentially deleterious variants that were subsequently validated by Sanger sequencing. These resources combined with a high-quality genome reference sequence opens new possibilities for efficient functional gene validation.

Litchi chinensis Sonn. is an economically important fruit tree in tropical and subtropical regions. However, litchi functional genomics is severely hindered due to its recalcitrance to regeneration and stable transformation. Agrobacterium rhizogenes-mediated hairy root transgenic system provide an alternative to study functional genomics in woody plants. However, the hairy root transgenic system has not been established in litchi. In this study, we report a rapid and highly efficient A. rhizogenes-mediated co-transformation system in L. chinensis using Green Fluorescent Protein (GFP) gene as a marker. Both leaf discs and stem segments of L. chinensis cv. ‘Fenhongguiwei’ seedlings were able to induce transgenic hairy roots. The optimal procedure involved the use of stem segments as explants, infection by A. rhizogenes strain MSU440 at optical density (OD600) of 0.7 for 10 min and co-cultivation for 3 days, with a co-transformation efficiency of 9.33%. Furthermore, the hairy root transgenic system was successfully used to validate the function of the key anthocyanin regulatory gene LcMYB1 in litchi. Over-expression of LcMYB1 produced red hairy roots, which accumulated higher contents of anthocyanins, proanthocyanins, and flavonols. Additionally, the genes involving in the flavonoid pathway were strongly activated in the red hairy roots. We first established a rapid and efficient transformation system for the study of gene function in hairy roots of litchi using A. rhizogenes strain MSU440 by optimizing parameters. This hairy root transgenic system was effective for gene function analysis in litchi using the key anthocyanin regulator gene LcMYB1 as an example.

Synchrotron imaging is widely used for research in many scientific disciplines. This article introduces the characteristics of synchrotron X-ray imaging and its applications in agriculture and food science research. The agriculture and food sector are a vast area that comprises of plants, seeds, animals, food and their products; soils with thriving microbial communities; and natural resources such as water, fertilizers, and organic matter. These entities have unique internal features, structures and compositions which differentiate them from each other in varieties, species, grades, and types. The use of a bright and tuneable monochromatic source of synchrotron imaging techniques enables researchers to study the internal features and compositions of plants, seeds, soil and food in a quick and non-destructive way to enhance their use, conservation and productivity. Synchrotron’s different X-ray imaging techniques offer a wide domain of applications, which make them perfect to enhance the understanding of structures of raw and processed food products to promote food safety and security. Therefore, this paper summarizes the results of major experiments carried out with seeds, plants, soil, food and relevant areas of agricultural sciences with more emphasis on two synchrotron X-ray imaging techniques: absorption and phase-contrast imaging and computed tomography.

Computer-based phenotyping of plants has risen in importance in recent years. Whilst much software has been written to aid phenotyping using image analysis, to date the vast majority has been only semi-automatic. However, such interaction is not desirable in high throughput approaches. Here, we present a system designed to analyse plant images in a completely automated manner, allowing genuine high throughput measurement of root traits. To do this we introduce a new set of proxy traits. We test the system on a new, automated image capture system, the Microphenotron, which is able to image many 1000s of roots/h. A simple experiment is presented, treating the plants with differing chemical conditions to produce different phenotypes. The automated imaging setup and the new software tool was used to measure proxy traits in each well. A correlation matrix was calculated across automated and manual measures, as a validation. Some particular proxy measures are very highly correlated with the manual measures (e.g. proxy length to manual length, r2 > 0.9). This suggests that while the automated measures are not directly equivalent to classic manual measures, they can be used to indicate phenotypic differences (hence the term, proxy). In addition, the raw discriminative power of the new proxy traits was examined. Principal component analysis was calculated across all proxy measures over two phenotypically-different groups of plants. Many of the proxy traits can be used to separate the data in the two conditions. The new proxy traits proposed tend to correlate well with equivalent manual measures, where these exist. Additionally, the new measures display strong discriminative power. It is suggested that for particular phenotypic differences, different traits will be relevant, and not all will have meaningful manual equivalent measures. However, approaches such as PCA can be used to interrogate the resulting data to identify differences between datasets. Select images can then be carefully manually inspected if the nature of the precise differences is required. We suggest such flexible measurement approaches are necessary for fully automated, high throughput systems such as the Microphenotron.

Abstract Background Quantitative Real Time RT-PCR (q2(RT)PCR) is a maturing technique which gives researchers the ability to quantify and compare very small amounts of nucleic acids. Primer design and optimization is an essential yet time consuming aspect of using q2(RT)PCR. In this paper we describe the design and empirical optimization of primers to amplify and quantify plastid RNAs from Zea mays that are robust enough to use with other closely related species. Results Primers were designed and successfully optimized for 57 of the 104 reported genes in the maize plastome plus two nuclear genes. All 59 primer pairs produced single amplicons after end-point reverse transcriptase polymerase chain reactions (RT-PCR) as visualized on agarose gels and subsequently verified by q2(RT)PCR. Primer pairs were divided into several categories based on the optimization requirements or the uniqueness of the target gene. An in silico test suggested the majority of the primer sets should work with other members of the Poaceae family. An in vitro test of the primer set on two unsequenced species (Panicum virgatum and Miscanthus sinensis) supported this assumption by successfully producing single amplicons for each primer pair. Conclusion Due to the highly conserved chloroplast genome in plant families it is possible to utilize primer pairs designed against one genomic sequence to detect the presence and abundance of plastid genes or transcripts from genomes that have yet to be sequenced. Analysis of steady state transcription of vital system genes is a necessary requirement to comprehensively elucidate gene expression in any organism. The primer pairs reported in this paper were designed for q2(RT)PCR of maize chloroplast genes but should be useful for other members of the Poaceae family. Both in silico and in vitro data are presented to support this assumption.

Proteins in the plant apoplast are essential for many physiological processes. We have analysed and compared six different infiltration solutions for proteins contained in the apoplast to recognize the most suitable method for leaves and to establish proteome maps for each extraction. The efficiency of protocols was evaluated by comparing the protein patterns resolved by 1-DE and 2-DE, and revealed distinct characteristics for each infiltration solution. Nano-LC-ESI-Q-TOF MS analysis of all fractions was applied to cover all proteins differentially extracted by infiltration solutions and led to the identification of 328 proteins in total in apoplast preparations. The predicted subcellular protein localisation distinguished the examined infiltration solutions in those with high or low amounts of intracellular protein contaminations, and with high or low quantities of secreted proteins. All tested infiltration solution extracted different subsets of proteins, and those implications on apoplast-specific studies are discussed.