Estimation of Rice Aboveground Biomass by UAV Imagery with Photosynthetic Accumulation Models.

The effective and accurate aboveground biomass (AGB) estimation facilitates evaluating crop growth and site-specific crop management. Considering that rice accumulates AGB mainly through green leaf photosynthesis, we proposed the photosynthetic accumulation model (PAM) and its simplified version and compared them for estimating AGB. These methods estimate the AGB of various rice cultivars throughout the growing season by integrating vegetation index (VI) and canopy height based on images acquired by unmanned aerial vehicles (UAV). The results indicated that the correlation of VI and AGB was weak for the whole growing season of rice and the accuracy of the height model was also limited for the whole growing season. In comparison with the NDVI-based rice AGB estimation model in 2019 data (R2 = 0.03, RMSE = 603.33 g/m2) and canopy height (R2 = 0.79, RMSE = 283.33 g/m2), the PAM calculated by NDVI and canopy height could provide a better estimate of AGB of rice (R2 = 0.95, RMSE = 136.81 g/m2). Then, based on the time-series analysis of the accumulative model, a simplified photosynthetic accumulation model (SPAM) was proposed that only needs limited observations to achieve R2 above 0.8. The PAM and SPAM models built by using 2 years of samples successfully predicted the third year of samples and also demonstrated the robustness and generalization ability of the models. In conclusion, these methods can be easily and efficiently applied to the UAV estimation of rice AGB over the entire growing season, which has great potential to serve for large-scale field management and also for breeding.

Genome-Wide Association Mapping for Yield and Yield-Related Traits in Rice (Oryza Sativa L.) Using SNPs Markers.

Rice (Oryza sativa L.) is a staple food for more than 50% of the world's population. Rice cultivar improvement is critical in order to feed the world's growing population. Improving yield is one of the main aims of rice breeders. However, yield is a complex quantitative trait controlled by many genes. The presence of genetic diversity is the key factor to improve the yield hence, the presence of diversity in any germplasm is important for yield improvement. In the current study, the rice germplasm was collected from Pakistan and the United States of America and a panel of 100 diverse genotypes was utilized to identify important yield and yield-related traits. For this, a genome-wide association study (GWAS) was performed to identify the genetic loci related to yield. The GWAS on the diverse germplasm will lead to the identification of new genes which can be utilized in the breeding program for improvement of yield. For this reason, firstly, the germplasm was phenotypically evaluated in two growing seasons for yield and yield-related traits. The analysis of variance results showed significant differences among traits which showed the presence of diversity in the current germplasm. Secondly, the germplasm was also genotypically evaluated using 10K SNP. Genetic structure analysis showed the presence of four groups which showed that enough genetic diversity was present in the rice germplasm to be used for association mapping analysis. The results of GWAS identified 201 significant marker trait associations (MTAs. 16 MTAs were identified for plant height, 49 for days to flowering, three for days to maturity, four for tillers per plant, four for panicle length, eight for grains per panicle, 20 unfilled grains per panicle, 81 for seed setting %, four for thousand-grain weight, five for yield per plot and seven for yield per hectare. Apart from this, some pleiotropic loci were also identified. The results showed that panicle length (PL) and thousand-grain weight (TGW) were controlled by a pleiotropic locus OsGRb23906 on chromosome 1 at 10,116,371 cM. The loci OsGRb25803 and OsGRb15974 on chromosomes 4 and 8 at the position of 14,321,111 cM and 6,205,816 cM respectively, showed pleiotropic effects for seed setting % (SS) and unfilled grain per panicle (UG/P). A locus OsGRb09180 on chromosome 4 at 19,850,601 cM was significantly linked with SS and yield/ha. Furthermore, gene annotation was performed, and results indicated that the 190 candidate genes or QTLs that closely linked with studied traits. These candidate genes and novel significant markers could be useful in marker-assisted gene selection and QTL pyramiding to improve rice yield and the selection of potential parents, recombinants and MTAs which could be used in rice breeding programs to develop high-yielding rice varieties for sustainable food security.

Combining spectral and wavelet texture features for unmanned aerial vehicles remote estimation of rice leaf area index.

Estimating the crop leaf area index (LAI) accurately is very critical in agricultural remote sensing, especially in monitoring crop growth and yield prediction. The development of unmanned aerial vehicles (UAVs) has been significant in recent years and has been extensively applied in agricultural remote sensing (RS). The vegetation index (VI), which reflects spectral information, is a commonly used RS method for estimating LAI. Texture features can reflect the differences in the canopy structure of rice at different growth stages. In this research, a method was developed to improve the accuracy of rice LAI estimation during the whole growing season by combining texture information based on wavelet transform and spectral information derived from the VI. During the whole growth period, we obtained UAV images of two study areas using a 12-band Mini-MCA system and performed corresponding ground measurements. Several VI values were calculated, and the texture analysis was carried out. New indices were constructed by mathematically combining the wavelet texture and spectral information. Compared with the corresponding VIs, the new indices reduced the saturation effect and were less sensitive to the emergence of panicles. The determination coefficient (R2) increased for most VIs used in this study throughout the whole growth period. The results indicated that the estimation accuracy of LAI by combining spectral information and texture information was higher than that of VIs. The method proposed in this study used the spectral and wavelet texture features extracted from UAV images to establish a model of the whole growth period of rice, which was easy to operate and had great potential for large-scale auxiliary rice breeding and field management research.

Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery.

Identification of high Nitrogen Use Efficiency (NUE) phenotypes has been a long-standing challenge in breeding rice and sustainable agriculture to reduce the costs of nitrogen (N) fertilizers. There are two main challenges: (1) high NUE genetic sources are biologically scarce and (2) on the technical side, few easy, non-destructive, and reliable methodologies are available to evaluate plant N variations through the entire growth duration (GD). To overcome the challenges, we captured a unique higher NUE phenotype in rice as a dynamic time-series N variation curve through the entire GD analysis by canopy reflectance data collected by Unmanned Aerial Vehicle Remote Sensing Platform (UAV-RSP) for the first time. LY9348 was a high NUE rice variety with high Nitrogen Uptake Efficiency (NUpE) and high Nitrogen Utilization Efficiency (NUtE) shown in nitrogen dosage field analysis. Its canopy nitrogen content (CNC) was analyzed by the high-throughput UAV-RSP to screen two mixed categories (51 versus 42 varieties) selected from representative higher NUE indica rice collections. Five Vegetation Indices (VIs) were compared, and the Normalized Difference Red Edge Index (NDRE) showed the highest correlation with CNC (r = 0.80). Six key developmental stages of rice varieties were compared from transplantation to maturation, and the high NUE phenotype of LY9348 was shown as a dynamic N accumulation curve, where it was moderately high during the vegetative developmental stages but considerably higher in the reproductive developmental stages with a slower reduction rate. CNC curves of different rice varieties were analyzed to construct two non-linear regression models between N% or N% × leaf area index (LAI) with NDRE separately. Both models could determine the specific phenotype with the coefficient of determination (R 2) above 0.61 (Model I) and 0.86 (Model II). Parameters influencing the correlation accuracy between NDRE and N% were found to be better by removing the tillering stage data, separating the short and long GD varieties for the analysis and adding canopy structures, such as LAI, into consideration. The high NUE phenotype of LY9348 could be traced and reidentified across different years, locations, and genetic germplasm groups. Therefore, an effective and reliable high-throughput method was proposed for assisting the selection of the high NUE breeding phenotype.

Remote estimation of leaf area index (LAI) with unmanned aerial vehicle (UAV) imaging for different rice cultivars throughout the entire growing season.

BACKGROUND: Rice is one of the most important grain crops worldwide. The accurate and dynamic monitoring of Leaf Area Index (LAI) provides important information to evaluate rice growth and production. METHODS: This study explores a simple method to remotely estimate LAI with Unmanned Aerial Vehicle (UAV) imaging for a variety of rice cultivars throughout the entire growing season. Forty eight different rice cultivars were planted in the study site and field campaigns were conducted once a week. For each campaign, several widely used vegetation indices (VI) were calculated from canopy reflectance obtained by 12-band UAV images, canopy height was derived from UAV RGB images and LAI was destructively measured by plant sampling. RESULTS: The results showed the correlation of VI and LAI in rice throughout the entire growing season was weak, and for all tested indices there existed significant hysteresis of VI vs. LAI relationship between rice pre-heading and post-heading stages. The model based on the product of VI and canopy height could reduce such hysteresis and estimate rice LAI of the whole season with estimation errors under 24%, not requiring algorithm re-parameterization for different phenology stages. CONCLUSIONS: The progressing phenology can affect VI vs. LAI relationship in crops, especially for rice having quite different canopy spectra and structure after its panicle exsertion. Thus the models solely using VI to estimate rice LAI are phenology-specific and have high uncertainties for post-heading stages. The model developed in this study combines both remotely sensed canopy height and VI information, considerably improving rice LAI estimation at both pre- and post-heading stages. This method can be easily and efficiently implemented in UAV platforms for various rice cultivars during the entire growing season with no rice phenology and cultivar pre-knowledge, which has great potential for assisting rice breeding and field management studies at a large scale.

Integrative Transcriptomic and Proteomic Analysis Reveals an Alternative Molecular Network of Glutamine Synthetase 2 Corresponding to Nitrogen Deficiency in Rice (Oryza sativa L.).

Nitrogen (N) is an essential nutrient for plant growth and development. The root system architecture is a highly regulated morphological system, which is sensitive to the availability of nutrients, such as N. Phenotypic characterization of roots from LY9348 (a rice variety with high nitrogen use efficiency (NUE)) treated with 0.725 mM NH4NO3 (1/4N) was remarkable, especially primary root (PR) elongation, which was the highest. A comprehensive analysis was performed for transcriptome and proteome profiling of LY9348 roots between 1/4N and 2.9 mM NH4NO3 (1N) treatments. The results indicated 3908 differential expression genes (DEGs; 2569 upregulated and 1339 downregulated) and 411 differential abundance proteins (DAPs; 192 upregulated and 219 downregulated). Among all DAPs in the proteome, glutamine synthetase (GS2), a chloroplastic ammonium assimilation protein, was the most upregulated protein identified. The unexpected concentration of GS2 from the shoot to the root in the 1/4N treatment indicated that the presence of an alternative pathway of N assimilation regulated by GS2 in LY9348 corresponded to the low N signal, which was supported by GS enzyme activity and glutamine/glutamate (Gln/Glu) contents analysis. In addition, N transporters (NRT2.1, NRT2.2, NRT2.3, NRT2.4, NAR2.1, AMT1.3, AMT1.2, and putative AMT3.3) and N assimilators (NR2, GS1;1, GS1;2, GS1;3, NADH-GOGAT2, and AS2) were significantly induced during the long-term N-deficiency response at the transcription level (14 days). Moreover, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis demonstrated that phenylpropanoid biosynthesis and glutathione metabolism were significantly modulated by N deficiency. Notably, many transcription factors and plant hormones were found to participate in root morphological adaptation. In conclusion, our study provides valuable information to further understand the response of rice roots to N-deficiency stress.

Genome-Wide Identification and Expansion Patterns of SULTR Gene Family in Gramineae Crops and Their Expression Profiles under Abiotic Stress in Oryza sativa.

Sulfate transporters (SULTRs), also known as H+/SO42- symporters, play a key role in sulfate transport, plant growth and stress responses. However, the evolutionary relationships and functional differentiation of SULTRs in Gramineae crops are rarely reported. Here, 111 SULTRs were retrieved from the genomes of 10 Gramineae species, including Brachypodium disachyon, Hordeum vulgare, Setaria italica, Sorghum bicolor, Zea mays, Oryza barthii, Oryza rufipogon, Oryza glabbermia and Oryza sativa (Oryza sativa ssp. indica and Oryza sativa ssp. japonica). The SULTRs were clustered into five clades based on a phylogenetic analysis. Syntheny analysis indicates that whole-genome duplication/segmental duplication and tandem duplication events were essential in the SULTRs family expansion. We further found that different clades and orthologous groups of SULTRs were under a strong purifying selective force. Expression analysis showed that rice SULTRs with high-affinity transporters are associated with the functions of sulfate uptake and transport during rice seedling development. Furthermore, using Oryza sativa ssp. indica as a model species, we found that OsiSULTR10 was significantly upregulated under salt stress, while OsiSULTR3 and OsiSULTR12 showed remarkable upregulation under high temperature, low-selenium and drought stresses. OsiSULTR3 and OsiSULTR9 were upregulated under both low-selenium and high-selenium stresses. This study illustrates the expression and evolutionary patterns of the SULTRs family in Gramineae species, which will facilitate further studies of SULTR in other Gramineae species.

Remote estimation of rice LAI based on Fourier spectrum texture from UAV image.

BACKGROUND: The accurate estimation of rice LAI is particularly important to monitor rice growth status. Remote sensing, as a non-destructive measurement technology, has been proved to be useful for estimating vegetation growth parameters, especially at large scale. With the development of unmanned aerial vehicles (UAVs), this novel remote sensing platform has been widely used to provide remote sensing images which have much higher spatial resolution. Previous reports have shown that the spectral feature of remote sensing images could be an effective indicator to estimate vegetation growth parameters. However, the texture feature of high-resolution remote sensing images is rarely employed for this purpose. Besides, the physical mechanism between the texture feature and vegetation growth parameters is still unclear. RESULTS: In this study, a Fourier spectrum texture based on the UAV Image was developed to estimate rice LAI. And the relationship between Fourier spectrum texture and rice LAI was also analyzed. The results showed that Fourier spectrum texture could improve the accuracy of rice LAI estimation. CONCLUSIONS: In conclusion, the texture feature of high-resolution remote sensing images may be more effective in rice LAI estimation than the spectral feature.

Remote Estimation of Rice Yield With Unmanned Aerial Vehicle (UAV) Data and Spectral Mixture Analysis.

The accurate assessment of rice yield is crucially important for China's food security and sustainable development. Remote sensing (RS), as an emerging technology, is expected to be useful for rice yield estimation especially at regional scales. With the development of unmanned aerial vehicles (UAVs), a novel approach for RS has been provided, and it is possible to acquire high spatio-temporal resolution imagery on a regional scale. Previous reports have shown that the predictive ability of vegetation index (VI) decreased under the influence of panicle emergence during the later stages of rice growth. In this study, a new approach which integrated UAV-based VI and abundance information obtained from spectral mixture analysis (SMA) was established to improve the estimation accuracy of rice yield at heading stage. The six-band image of all studied rice plots was collected by a camera system mounted on an UAV at booting stage and heading stage respectively. And the corresponding ground measured data was also acquired at the same time. The relationship of several widely-used VIs and Rice Yield was tested at these two stages and a relatively weaker correlation between VI and yield was found at heading stage. In order to improve the estimation accuracy of rice yield at heading stage, the plot-level abundance of panicle, leaf and soil, indicating the fraction of different components within the plot, was derived from SMA on the six-band image and in situ endmember spectra collected for different components. The results showed that VI incorporated with abundance information exhibited a better predictive ability for yield than VI alone. And the product of VI and the difference of leaf abundance and panicle abundance was the most accurate index to reliably estimate yield for rice under different nitrogen treatments at heading stage with the coefficient of determination reaching 0.6 and estimation error below 10%.

Novel and Automatic Rice Thickness Extraction Based on Photogrammetry Using Rice Edge Features.

The dimensions of phenotyping parameters such as the thickness of rice play an important role in rice quality assessment and phenotyping research. The objective of this study was to propose an automatic method for extracting rice thickness. This method was based on the principle of binocular stereovision but avoiding the problem that it was difficult to directly match the corresponding points for 3D reconstruction due to the lack of texture of rice. Firstly, the shape features of edge, instead of texture, was used to match the corresponding points of the rice edge. Secondly, the height of the rice edge was obtained by way of space intersection. Finally, the thickness of rice was extracted based on the assumption that the average height of the edges of multiple rice is half of the thickness of rice. According to the results of the experiments on six kinds of rice or grain, errors of thickness extraction were no more than the upper limit of 0.1 mm specified in the national industry standard. The results proved that edge features could be used to extract rice thickness and validated the effectiveness of the thickness extraction algorithm we proposed, which provided technical support for the extraction of phenotyping parameters for crop researchers.

Remote estimation of rapeseed yield with unmanned aerial vehicle (UAV) imaging and spectral mixture analysis.

BACKGROUND: The accurate quantification of yield in rapeseed is important for evaluating the supply of vegetable oil, especially at regional scales. METHODS: This study developed an approach to estimate rapeseed yield with remotely sensed canopy spectra and abundance data by spectral mixture analysis. A six-band image of the studied rapeseed plots was obtained by an unmanned aerial vehicle (UAV) system during the rapeseed flowering stage. Several widely used vegetation indices (VIs) were calculated from canopy reflectance derived from the UAV image. And the plot-level abundance of flower, leaf and soil, indicating the fraction of different components within the plot, was retrieved based on spectral mixture analysis on the six-band image and endmember spectra collected in situ for different components. RESULTS: The results showed that for all tested indices VI multiplied by leaf-related abundance closely related to rapeseed yield. The product of Normalized Difference Vegetation Index and short-stalk-leaf abundance was the most accurate for estimating yield in rapeseed under different nitrogen treatments with the estimation errors below 13%. CONCLUSION: This study gives an important indication that spectral mixture analysis needs to be considered when estimating yield by remotely sensed VI, especially for the image containing obviously spectral different components or for crops which have conspicuous flowers or fruits with significantly different spectra from their leave.

Bph32, a novel gene encoding an unknown SCR domain-containing protein, confers resistance against the brown planthopper in rice.

An urgent need exists to identify more brown planthopper (Nilaparvata lugens Stål, BPH) resistance genes, which will allow the development of rice varieties with resistance to BPH to counteract the increased incidence of this pest species. Here, using bioinformatics and DNA sequencing approaches, we identified a novel BPH resistance gene, LOC_Os06g03240 (MSU LOCUS ID), from the rice variety Ptb33 in the interval between the markers RM19291 and RM8072 on the short arm of chromosome 6, where a gene for resistance to BPH was mapped by Jirapong Jairin et al. and renamed as "Bph32". This gene encodes a unique short consensus repeat (SCR) domain protein. Sequence comparison revealed that the Bph32 gene shares 100% sequence identity with its allele in Oryza latifolia. The transgenic introgression of Bph32 into a susceptible rice variety significantly improved resistance to BPH. Expression analysis revealed that Bph32 was highly expressed in the leaf sheaths, where BPH primarily settles and feeds, at 2 and 24 h after BPH infestation, suggesting that Bph32 may inhibit feeding in BPH. Western blotting revealed the presence of Pph (Ptb33) and Tph (TN1) proteins using a Penta-His antibody, and both proteins were insoluble. This study provides information regarding a valuable gene for rice defence against insect pests.

Application of resistance gene analog markers to analyses of genetic structure and diversity in rice.

Plant disease resistance gene analog (RGA) markers were designed according to the conserved sequence of known RGAs and used to map resistance genes. We used genome-wide RGA markers for genetic analyses of structure and diversity in a global rice germplasm collection. Of the 472 RGA markers, 138 were polymorphic and these were applied to 178 entries selected from the USDA rice core collection. Results from the RGA markers were similar between two methods, UPGMA and STRUCTURE. Additionally, the results from RGA markers in our study were agreeable with those previously reported from SSR markers, including cluster of ancestral classification, genetic diversity estimates, genetic relatedness, and cluster of geographic origins. These results suggest that RGA markers are applicable for analyses of genetic structure and diversity in rice. However, unlike SSR markers, the RGA markers failed to differentiate temperate japonica, tropical japonica, and aromatic subgroups. The restricted way for developing RGA markers from the cDNA sequence might limit the polymorphism of RGA markers in the genome, thus limiting the discriminatory power in comparison with SSR markers. Genetic differentiation obtained using RGA markers may be useful for defining genetic diversity of a suite of random R genes in plants, as many studies show a differentiation of resistance to a wide array of pathogens. They could also help to characterize the genetic structure and geographic distribution in crops, including rice, wheat, barley, and banana.

Phylogenetic, Molecular, and Biochemical Characterization of Caffeic Acid o-Methyltransferase Gene Family in Brachypodium distachyon.

Caffeic acid o-methyltransferase (COMT) is one of the important enzymes controlling lignin monomer production in plant cell wall synthesis. Analysis of the genome sequence of the new grass model Brachypodium distachyon identified four COMT gene homologs, designated as BdCOMT1, BdCOMT2, BdCOMT3, and BdCOMT4. Phylogenetic analysis suggested that they belong to the COMT gene family, whereas syntenic analysis through comparisons with rice and sorghum revealed that BdCOMT4 on Chromosome 3 is the orthologous copy of the COMT genes well characterized in other grass species. The other three COMT genes are unique to Brachypodium since orthologous copies are not found in the collinear regions of rice and sorghum genomes. Expression studies indicated that all four Brachypodium COMT genes are transcribed but with distinct patterns of tissue specificity. Full-length cDNAs were cloned in frame into the pQE-T7 expression vector for the purification of recombinant Brachypodium COMT proteins. Biochemical characterization of enzyme activity and substrate specificity showed that BdCOMT4 has significant effect on a broad range of substrates with the highest preference for caffeic acid. The other three COMTs had low or no effect on these substrates, suggesting that a diversified evolution occurred on these duplicate genes that not only impacted their pattern of expression, but also altered their biochemical properties.

Suppressor of sessile spikelets1 functions in the ramosa pathway controlling meristem determinacy in maize.

The spikelet, which is a short branch bearing the florets, is the fundamental unit of grass inflorescence architecture. In most grasses, spikelets are borne singly on the inflorescence. However, paired spikelets are characteristic of the Andropogoneae, a tribe of 1,000 species including maize (Zea mays). The Suppressor of sessile spikelets1 (Sos1) mutant of maize produces single instead of paired spikelets in the inflorescence. Therefore, the sos1 gene may have been involved in the evolution of paired spikelets. In this article, we show that Sos1 is a semidominant, antimorph mutation. Sos1 mutants have fewer branches and spikelets for two reasons: (1) fewer spikelet pair meristems are produced due to defects in inflorescence meristem size and (2) the spikelet pair meristems that are produced make one instead of two spikelet meristems. The interaction of Sos1 with the ramosa mutants, which produce more branches and spikelets, was investigated. The results show that Sos1 has an epistatic interaction with ramosa1 (ra1), a synergistic interaction with ra2, and an additive interaction with ra3. Moreover, ra1 mRNA levels are reduced in Sos1 mutants, while ra2 and ra3 mRNA levels are unaffected. Based on these genetic and expression studies, we propose that sos1 functions in the ra1 branch of the ramosa pathway controlling meristem determinacy.

Genetic and physical interaction suggest that BARREN STALK 1 is a target of BARREN INFLORESCENCE2 in maize inflorescence development.

SUMMARY: Organogenesis in plants is controlled by polar auxin transport. In maize (Zea mays), barren inflorescence2 (bif2) encodes a co-ortholog of the serine/threonine protein kinase PINOID (PID), which regulates auxin transport in Arabidopsis. In this paper, we report that the basic helix-loop-helix transcription factor BARREN STALK1 (BA1) is a putative target of BIF2, revealing a previously unknown function of BIF2 in the nucleus. Both bif2 and ba1 are required for axillary meristem initiation during inflorescence and vegetative development in maize. Using a yeast two-hybrid approach, we identified BA1 as an interacting partner with BIF2. We confirmed the interaction by in vitro pull-down assays, and demonstrated that BIF2 phosphorylates BA1 in vitro. Previously, RNA in situ hybridization showed that bif2 and ba1 are both expressed during axillary meristem initiation. Here, we heterologously expressed BIF2 and BA1, and found that they co-localize in the nucleus. Based on these findings, we propose that in addition to regulating auxin transport at the cell periphery, BIF2 also functions in the nucleus by interacting with BA1 to promote axillary meristem initiation. Double mutant analysis is consistent with these results, showing that bif2 and ba1 have overlapping as well as unique roles in inflorescence development.

barren inflorescence2 Encodes a co-ortholog of the PINOID serine/threonine kinase and is required for organogenesis during inflorescence and vegetative development in maize.

Organogenesis in plants is controlled by meristems. Axillary meristems, which give rise to branches and flowers, play a critical role in plant architecture and reproduction. Maize (Zea mays) and rice (Oryza sativa) have additional types of axillary meristems in the inflorescence compared to Arabidopsis (Arabidopsis thaliana) and thus provide an excellent model system to study axillary meristem initiation. Previously, we characterized the barren inflorescence2 (bif2) mutant in maize and showed that bif2 plays a key role in axillary meristem and lateral primordia initiation in the inflorescence. In this article, we cloned bif2 by transposon tagging. Isolation of bif2-like genes from seven other grasses, along with phylogenetic analysis, showed that bif2 is a co-ortholog of PINOID (PID), which regulates auxin transport in Arabidopsis. Expression analysis showed that bif2 is expressed in all axillary meristems and lateral primordia during inflorescence and vegetative development in maize and rice. Further phenotypic analysis of bif2 mutants in maize illustrates additional roles of bif2 during vegetative development. We propose that bif2/PID sequence and expression are conserved between grasses and Arabidopsis, attesting to the important role they play in development. We provide further support that bif2, and by analogy PID, is required for initiation of both axillary meristems and lateral primordia.

The role of auxin transport during inflorescence development in maize (Zea mays, Poaceae).

Axillary meristems play a fundamental role in inflorescence architecture. Maize (Zea mays) inflorescences are highly branched panicles because of the production of multiple types of axillary meristems. We used auxin transport inhibitors to show that auxin transport is required for axillary meristem initiation in the maize inflorescence. The phenotype of plants treated with auxin transport inhibitors is very similar to that of barren inflorescence2 (bif2) and barren stalk1 (ba1) mutants, suggesting that these genes function in the same auxin transport pathway. To dissect this pathway, we performed RNA in situ hybridization on plants treated with auxin transport inhibitors. We determined that bif2 is expressed upstream and that ba1 is expressed downstream of auxin transport, enabling us to integrate the genetic and hormonal control of axillary meristem initiation. In addition, treatment of maize inflorescences with auxin transport inhibitors later in development results in the production of single instead of paired spikelets. Paired spikelets are a key feature of the Andropogoneae, a group of over 1000 grasses that includes maize, sorghum, and sugarcane. Because all other grasses bear spikelets singly, these results implicate auxin transport in the evolution of inflorescence architecture. Furthermore, our results provide insight into mechanisms of inflorescence branching that are relevant to all plants.