Determinant Of Grain Yield Research Articles

Data-driven identification of environmental variables influencing phenotypic plasticity to facilitate breeding for future climates.

Phenotypic plasticity describes a genotype's ability to produce different phenotypes in response to different environments. Breeding crops that exhibit appropriate levels of plasticity for future climates will be crucial to meeting global demand, but knowledge of the critical environmental factors is limited to a handful of well-studied major crops. Using 727 maize (Zea mays L.) hybrids phenotyped for grain yield in 45 environments, we investigated the ability of a genetic algorithm and two other methods to identify environmental determinants of grain yield from a large set of candidate environmental variables constructed using minimal assumptions. The genetic algorithm identified pre- and postanthesis maximum temperature, mid-season solar radiation, and whole season net evapotranspiration as the four most important variables from a candidate set of 9150. Importantly, these four variables are supported by previous literature. After calculating reaction norms for each environmental variable, candidate genes were identified and gene annotations investigated to demonstrate how this method can generate insights into phenotypic plasticity. The genetic algorithm successfully identified known environmental determinants of hybrid maize grain yield. This demonstrates that the methodology could be applied to other less well-studied phenotypes and crops to improve understanding of phenotypic plasticity and facilitate breeding crops for future climates.

Rain and potential evapotranspiration are the main drivers of yield for wheat and barley in southern Australia: insights from 12 years of National Variety Trials

Context Water is widely assumed to be the factor most limiting the growth of annual crops in rainfed environments, but this is rarely tested at sub-continental scale. Aims Our study aimed to determine the key environmental and management variables influencing the yield of wheat and barley in the grain-production regions of southern Australia, using data from National Variety Trials. Methods We used generalised additive models to determine the importance of climatic and management variables on wheat and barley grain yield. We determined the effects of the best one, two or three variables and their interactions. Key results The aridity index, defined as the ratio of cumulative rainfall to potential evapotranspiration, was the single strongest determinant of grain yield for both crops. Model performance was further improved by separating the aridity index into pre-seasonal and seasonal components. Interestingly, other variables that might be expected to influence yield, such as nitrogen fertilisation and extreme temperatures, had relatively minor effects. A comparison between data collected over two 6-year periods showed that there had been yield gains and increased water-use efficiency with time, especially in wetter environments. Conclusions Our findings illustrate the importance of water availability for grain production in this region and suggest opportunities for benchmarking and yield prediction through use of readily available climate data. Implications Our study reinforces the importance of factors such as water-use efficiency and drought tolerance as goals for cultivar development and agronomic research in wheat and barley. It also highlights the potential of National Variety Trial data as a resource for understanding grain production systems and climate resilience. Further work could explore the value of additional variables and improved weather data.

Grain and shoot iron (Fe) content and root phytosiderophore release are the major determinants of Fe-deficiency tolerance index (FeDTI) and the reliable screening markers to breed Fe-efficient rice (Oryza sativa L.)

There is a need to exploit the genetic variability in rice to improve the Fe deficiency tolerance, particularly under aerobic conditions, and to improve the Fe uptake and accumulation in the grain to facilitate biofortification. The present research was conducted to ascertain the regulators and determinants of Fe-deficiency tolerance in rice. Fifty-seven diverse genotypes were investigated under Fe-deficient (1 µM, FDS, -Fe) and Fe-sufficient (100 µM, FSS, +Fe) nutrient solution cultures for growth and physiological attributes, Fe uptake and accumulation and root release of phytosiderophores (PS), etc., and Fe-deficiency tolerance index (FeDTI). A strong positive correlation was observed between root traits and the PS release. Further, a higher release of PS was evidenced as a major determinant of shoot Fe and grain Fe in rice particularly under Fe deficiency. Based on FeDTI, a total of ten rice genotypes were identified, and their Fe deficiency response was further validated on Fe deficient (∼2.1 ppm Fe, FeDS) and Fe-sufficient soils (∼10 ppm Fe, FeSS) in pot culture. Maintenance of high active Fe content and consequently a higher leaf chlorophyll content throughout the plant growth were extremely important determinants of grain yield and grain Fe fortification in rice under Fe deficiency than under the Fe sufficient condition. Based on the FeDTI, this study further identifies the Fe-deficiency tolerant rice genotypes which can be exploited through conventional and molecular breeding approaches to improve the Fe uptake efficiency and grain Fe content of the high-yielding rice genotypes.

Leaf photosynthetic performance is not a key factor affecting grain yield in spring wheat subjected to heat and combined heat and drought stresses

AbstractThe yield traits and physiological responses of three wheat genotypes were studied when subjected to heat and combined heat and drought stress at anthesis under either aCO2 (400 ppm) or eCO2 (800 ppm) in a greenhouse. The heat treatment was 7‐days at day/night 35/28°C, and the combined heat and drought was withholding irrigation from the heat‐stressed plants until the photosynthetic rate reached <5 μmol m−2 s−1. The LM62 genotype had higher photosynthetic rate compared with LM19, though no significant difference in grain yield was found. eCO2 increased photosynthesis at 35°C and significantly lowered the electron transport rate at high intercellular CO2 concentrations. Maximum velocity of Rubisco carboxylation (Vcmax) and the maximum velocity of RuBP regeneration in leaves (Jmax) increased in 35°C compared with 25°C, though when normalized to 25°C both Vcmax and Jmax decreased in the heat‐stressed plants, indicating that an inhibition had occurred. The maximum photochemical efficiency of photosystem II (Fv/Fm) decreased under heat, which correlated with the yield loss caused by the stress. Fv/Fm also decreased under combined heat and drought, though it did not related to the declined yield. A small leaf area prolonged the drying period of Gladius, and it was the genotype with the lowest decrease in yield because of stress. It is concluded that the effects of heat and combined heat and drought stress on the gas exchange and photosynthetic capacity on leaf area basis are not directly linked to the yield performance among wheat genotypes, while the morphological characteristics of the plants are important determinants of grain yield in response to those abiotic stresses.

Dissecting the effect of heat stress on durum wheat under field conditions.

Heat stress negatively affects wheat production in several ways, mainly by reducing growth rate, photosynthetic capacity and reducing spike fertility. Modeling stress response means analyzing simultaneous relationships among traits affecting the whole plant response and determinants of grain yield. The aim of this study was to dissect the diverse impacts of heat stress on key yield traits and to identify the most promising sources of alleles for heat tolerance. We evaluated a diverse durum wheat panel of 183 cultivars and breeding lines from worldwide, for their response to long-term heat stress under field conditions (HS) with respect to non stress conditions (NS), considering phenological traits, grain yield (GY) and its components as a function of the timing of heat stress and climatic covariates. We investigated the relationships among plant and environmental variables by means of a structural equation model (SEM) and Genetic SEM (GSEM). Over two years of experiments at CENEB, CIMMYT, the effects of HS were particularly pronounced for the normalized difference vegetation index, NDVI (-51.3%), kernel weight per spike, KWS (-40.5%), grain filling period, GFP (-38.7%), and GY (-56.6%). Average temperatures around anthesis were negatively correlated with GY, thousand kernel weight TKW and test weight TWT, but also with spike density, a trait determined before heading/anthesis. Under HS, the correlation between the three major determinants of GY, i.e., fertile spike density, spike fertility and kernel size, were of noticeable magnitude. NDVI measured at medium milk-soft dough stage under HS was correlated with both spike fertility and grain weight while under NS it was less predictive of grain weight but still highly correlated with spike fertility. GSEM modeling suggested that the causal model of performance under HS directly involves genetic effects on GY, NDVI, KWS and HD. We identified consistently suitable sources of genetic resistance to heat stress to be used in different durum wheat pre-breeding programs. Among those, Desert Durums and CIMMYT'80 germplasm showed the highest degree of adaptation and capacity to yield under high temperatures and can be considered as a valuable source of alleles for adaptation to breed new HS resilient cultivars.

GW9 determines grain size and floral organ identity in rice.

Grain weight is an important determinant of grain yield. However, the underlying regulatory mechanisms for grain size remain to be fully elucidated. Here, we identify a rice mutant grain weight 9 (gw9), which exhibits larger and heavier grains due to excessive cell proliferation and expansion in spikelet hull. GW9 encodes a nucleus-localized protein containing both C2H2 zincfinger (C2H2-ZnF) and VRN2-EMF2-FIS2-SUZ12 (VEFS) domains, serving as a negative regulator of grain size and weight. Interestingly, the non-frameshift mutations in C2H2-ZnF domain result in increased plant height and larger grain size, whereas frameshift mutations in both C2H2-ZnF and VEFS domains lead to dwarf and malformed spikelet. These observations indicated the dual functions of GW9 in regulating grain size and floral organ identity through the C2H2-ZnF and VEFS domains, respectively. Further investigation revealed the interaction between GW9 and the E3 ubiquitin ligase protein GW2, with GW9 being the target of ubiquitination by GW2. Genetic analyses suggest that GW9 and GW2 function in a coordinated pathway controlling grain size and weight. Our findings provide a novel insight into the functional role of GW9 in the regulation of grain size and weight, offering potential molecular strategies for improving rice yield.

Unraveling the genetic basis of grain number-related traits in a wheat-Agropyron cristatum introgressed line through high-resolution linkage mapping

BackgroundGrain number per spike (GNS) is a pivotal determinant of grain yield in wheat. Pubing 3228 (PB3228), a wheat-Agropyron cristatum germplasm, exhibits a notably higher GNS.ResultsIn this study, we developed a recombinant inbred line (RIL) population derived from PB3228/Gao8901 (PG-RIL) and constructed a high-density genetic map comprising 101,136 loci, spanning 4357.3 cM using the Wheat 660 K SNP array. The genetic map demonstrated high collinearity with the wheat assembly IWGSC RefSeq v1.0. Traits related to grain number and spikelet number per spike were evaluated in seven environments for quantitative trait locus (QTL) analysis. Five environmentally stable QTLs were detected in at least three environments. Among these, two major QTLs, QGns-4A.2 and QGns-1A.1, associated with GNS, exhibited positive alleles contributed by PB3228. Further, the conditional QTL analysis revealed a predominant contribution of PB3228 to the GNS QTLs, with both grain number per spikelet (GNSL) and spikelet number per spike (SNS) contributing to the overall GNS trait. Four kompetitive allele-specific PCR (KASP) markers that linked to QGns-4A.2 and QGns-1A.1 were developed and found to be effective in verifying the QTL effect within a diversity panel. Compared to previous studies, QGns-4A.2 exhibited stability across different trials, while QGns-1A.1 represents a novel QTL. The results from unconditional and conditional QTL analyses are valuable for dissecting the genetic contribution of the component traits to GNS at the individual QTL level and for understanding the genetic basis of the superior grain number character in PB3228. The KASP markers can be utilized in marker-assisted selection for enhancing GNS.ConclusionsFive environmentally stable QTLs related to grain number and spikelet number per spike were identified. PB3228 contributed to the majority of the QTLs associated with GNS.

Assessing the yield difference of double-cropping rice in South China driven by radiation use efficiency

Double-cropping rice in South China continues to break the total yield record, but the yield potential of single-cropping rice is not being realized. Radiation use efficiency (RUE) has been singled out as an important determinant of grain yield in many cereal species. However, there is no information on whether the yield gaps in double-cropping rice involve differences in RUE. Field experiments were performed over two years to evaluate the effects of intercepted radiation (IP) and RUE on the above-ground biomass production, crop growth rate (CGR), and harvest index (HI), in four representative rice varieties, i.e., Xiangyaxiangzhan (XYXZ), Meixiangzhan 2 (MXZ2), Nanjingxiangzhan (NJXZ), and Ruanhuayoujinsi (RHYJS), during the early and late seasons of rice cultivation in South China. The results revealed that grain yield in the early season was 8.2% higher than in the late season. The yield advantage in the early season was primarily due to higher spikelets per panicle and above-ground biomass resulting from a higher RUE. The spikelets per panicle in the early season were 6.5, 8.3, 6.9, and 8.5% higher in XYXZ, MXZ2, NJXZ, and RHYJS, respectively, than in the late season. The higher early season grain yield was more closely related to RUE in the middle tillering stage (R2=0.34), panicle initiation (R2=0.16), and maturation stage (R2=0.28), and the intercepted photosynthetically active radiation (IPAR) in the maturation stage (R2=0.28), while the late season grain yield was more dependent on IPAR in the middle tillering stage (R2=0.31) and IPAR at panicle initiation (R2=0.23). The results of this study conclusively show that higher RUE contributes to the yield progress of early season rice, while the yield improvement of late season rice is attributed to higher radiation during the early reproductive stage. Rationally allocating the RUE of double-cropping rice with high RUE varieties or adjustments of the sowing period merits further study.

Fine mapping and characterization of a major QTL for grain length, QGl.cau-2D.1, that has pleiotropic effects in synthetic allohexaploid wheat

Grain size is one of the determinants of grain yield, and identifying the genetic loci that control grain size will be helpful for increasing grain yield. In our previous study, a quantitative trait locus (QTL) for grain length (GL), QGl.cau-2D.1, was identified from an F2 population developed from the cross between the natural (TAA10) and synthetic (XX329) allohexaploid wheat. In the present study, we mainly fine mapped and validated its genetic effects. To this end, multiple near-isogenic lines (NILs) were obtained through marker-assisted selection with TAA10 as the recurrent parent. The secondary populations derived from 25 heterozygous recombinants were used for fine mapping of QGl.cau-2D.1, and the allele from XX329 significantly increased GL, thousand-grain weight (TGW), total spikelet number per spike (TSN) and spike compactness (SC). Using NILs for XX329 (2D+) and TAA10 (2D−), we determined the genetic and pleiotropic effects of QGl.cau-2D.1. The target sequences were aligned with the wheat reference genome RefSeq v2.1 and spanned an ~0.9 Mb genomic region. TraesCS2D03G0114900 (ortholog of Os03g0594700) was predicted as the candidate gene based on whole-genome re-sequencing and expression analyses. In summary, the map-based cloning of QGl.cau-2D.1 will be useful for improving grain weight with enhanced GL and TSN.

GR5 acts in the G protein pathway to regulate grain size in rice

Grain size is an important determinant of grain yield in rice. Although dozens of grain size genes have been reported, the molecular mechanisms that control grain size remain to be fully clarified. Here, we report the cloning and characterization of GR5 (GRAIN ROUND 5), which is allelic to SMOS1/SHB/RLA1/NGR5 and encodes an AP2 transcription factor. GR5 acts as a transcriptional activator and determines grain size by influencing cell proliferation and expansion. We demonstrated that GR5 physically interacts with five Gγ subunit proteins (RGG1, RGG2, DEP1, GS3, and GGC2) and acts downstream of the G protein complex. Four downstream target genes of GR5 in grain development (DEP2, DEP3, DRW1, and CyCD5;2) were revealed and their core T/CGCAC motif identified by yeast one-hybrid, EMSA, and ChIP–PCR experiments. Our results revealed that GR5 interacts with Gγ subunits and cooperatively determines grain size by regulating the expression of downstream target genes. These findings provide new insight into the genetic regulatory network of the G protein signaling pathway in the control of grain size and provide a potential target for high-yield rice breeding.

Estimation of flowering time and its effect on grain yield of photoperiod sensitive varieties in rainfed lowland rice in Northeast Thailand

Flowering time of photoperiod sensitive varieties is an important determinant of grain yield of rainfed lowland rice, and is affected by the growing environment. The present study aimed to quantify variety specific flowering time response to photoperiod under irrigated conditions and demonstrate the usefulness of delay in flowering observed in rainfed lowland fields as an index of severity of water deficit affecting yield. Both irrigated on-station and rainfed lowland on-farm experiments were conducted with 4 popular photoperiod sensitive varieties in Northeast Thailand. The irrigated experiment was conducted with 12 sowing times throughout a year and flowering time was quantified with prevailing daylength and temperature. Among the 4 varieties, the minimum time to flowering varied from 68 to 77 days, and maximum daylength required for panicle initiation varied from 12 hrs 21 min to 12 hrs 39 min. Flowering time of all varieties was delayed in 3–4 sowings due to cold during vegetative stage; these sowings did not coincide with farmers’ common sowing time. On-farm flowering time and yield data were obtained from 108 crops grown under rainfed lowland conditions across 8 provinces in Northeast Thailand in 2013–2015, and were used for validating flowering time and grain yield simulation based on the sequential sowing experiment. Both curvilinear and linear equations to estimate time to flowering from sowing time gave a similar result. Delay in flowering due to water deficit observed on-farm was estimated as the difference between the observed on-farm and simulated flowering time under irrigated conditions, and the estimated delay was related to grain yield reduction due to water deficit. It is concluded that simulated flowering time under irrigated conditions together with observed flowering time in farmer’s fields can be used to determine flowering delay under rainfed conditions, and the delay is an indication of the severity of water deficit reducing yield. Extension material may be developed in which estimated flowering time of key varieties under well-watered conditions may be tabulated for various sowing times and locations in the region, and then farmers can determine delay in flowering and likely yield reduction for their own and neighboring crops.

Genome-wide association mapping in elite winter wheat breeding for yield improvement

Increased grain yield (GY) is the primary breeding target of wheat breeders. We performed the genome-wide association study (GWAS) on 168 elite winter wheat lines from an ongoing breeding program to identify the main determinants of grain yield. Sequencing of Diversity Array Technology fragments (DArTseq) resulted in 19,350 single-nucleotide polymorphism (SNP) and presence-absence variation (PAV) markers. We identified 15 main genomic regions located in ten wheat chromosomes (1B, 2B, 2D, 3A, 3D, 5A, 5B, 6A, 6B, and 7B) that explained from 7.9 to 20.3% of the variation in grain yield and 13.3% of the yield stability. Loci identified in the reduced genepool are important for wheat improvement using marker-assisted selection. We found marker-trait associations between three genes involved in starch biosynthesis and grain yield. Two starch synthase genes (TraesCS2B03G1238800 and TraesCS2D03G1048800) and a sucrose synthase gene (TraesCS3D03G0024300) were found in regions of QGy.rut-2B.2, QGy.rut-2D.1, and QGy.rut-3D, respectively. These loci and other significantly associated SNP markers found in this study can be used for pyramiding favorable alleles in high-yielding varieties or to improve the accuracy of prediction in genomic selection.

Effect of Cropping Systems and Environment on Phenolic Acid Profiles and Yielding of Hybrid Winter Wheat Genotypes

Wheat is of significant economic importance due to its high yield potential and high nutritional value as well as the technological usefulness of the grain. Field experiments were carried out in the years 2015–2018 in southeastern Poland. A three-factor experiment was used to study the influence of wheat cultivars (hybrid—cvs. Hybred and Hymack; common—cv. Batuta), cultivation systems (organic—ORG, integrated—INT, conventional—CON) and of environmental conditions (using two different locations: Dukla and Nowy Lubliniec) on wheat grains’ phenolic acid (PA) content and grain yield. The research confirms the genetic determinants of grain yield and PA composition in wheat grains, and their different accumulation levels of ferulic acid and other PAs—with the exception of sinapic, p-coumaric, and salicilic—with hybrid cultivars performing better than common cultivars. The ORG system, compared to the INT and CON systems, caused a larger increase in total acids (TPAs)—especially of ferulic, vanillic, and syringic acids—in grains of cv. Hybred, and of caffeic acid in cv. Hymack, compared to cv. Batuta. The lack of interaction between the cultivation systems and the cultivars indicates that similar reactions to increases in grain yield due to increases in the intensity of cultivation take place in cultivars. The more favourable environmental conditions in Dukla favoured the accumulation of ferulic, p-coumaric, vanillic, syringic, p-hydroxybenzoic, and protocatechuic acids in the grains. TPAs were higher by 4.3% and the grain yield by 4.0% on average. Variable conditions in the season 2015/2016 resulted in higher yields of hybrid cvs. grains than of common cv., which proves the greater yielding stability of these cultivars in years with adverse weather conditions. The season 2016/2017 had less rainfall and faced high temperatures during grain ripening, favouring a higher PA content and TPAs, especially in the grains of cv. Hybred. This suggests a need to further assess the genetic progress of hybrid wheat cultivars cultivated under different environmental conditions in terms of their PA composition and content.

Responses of wheat kernel weight to diverse allelic combinations under projected climate change conditions.

In wheat, kernel weight (KW) is a key determinant of grain yield (GY). However, it is often overlooked when improving wheat productivity under climate warming. Moreover, little is known about the complex effects of genetic and climatic factors on KW. Here, we explored the responses of wheat KW to diverse allelic combinations under projected climate warming conditions. To focus on KW, we selected a subset of 81 out of 209 wheat varieties with similar GY, biomass, and kernel number (KN) and focused on their thousand-kernel weight (TKW). We genotyped them at eight kompetitive allele-specific polymerase chain reaction markers closely associated with TKW. Subsequently, we calibrated and evaluated the process-based model known as Agricultural Production Systems Simulator (APSIM-Wheat) based on a unique dataset including phenotyping, genotyping, climate, soil physicochemistry, and on-farm management information. We then used the calibrated APSIM-Wheat model to estimate TKW under eight allelic combinations (81 wheat varieties), seven sowing dates, and the shared socioeconomic pathways (SSPs) designated SSP2-4.5 and SSP5-8.5, driven by climate projections from five General Circulation Models (GCMs) BCC-CSM2-MR, CanESM5, EC-Earth3-Veg, MIROC-ES2L, and UKESM1-0-LL. The APSIM-Wheat model reliably simulated wheat TKW with a root mean square error (RMSE) of < 3.076g TK-1 and R2 of > 0.575 (P < 0.001). The analysis of variance based on the simulation output showed that allelic combination, climate scenario, and sowing date extremely significantly affected TKW (P < 0.001). The impact of the interaction allelic combination × climate scenario on TKW was also significant (P < 0.05). Meanwhile, the variety parameters and their relative importance in the APSIM-Wheat model accorded with the expression of the allelic combinations. Under the projected climate scenarios, the favorable allelic combinations (TaCKX-D1b + Hap-7A-1 + Hap-T + Hap-6A-G + Hap-6B-1 + H1g + A1b for SSP2-4.5 and SSP5-8.5) mitigated the negative effects of climate change on TKW. The present study demonstrated that optimizing favorable allelic combinations can help achieve high wheat TKW. The findings of this study clarify the responses of wheat KW to diverse allelic combinations under projected climate change conditions. Additionally, the present study provides theoretical and practical reference for marker-assisted selection of high TKW in wheat breeding.

Production maximization of rainy season rice (Oryza sativa) through effective use of water and solar radiation under modified system of rice intensification in Assam

A field experiment was conducted in a farmers’ field at Nepalikhuti, Golaghat, Assam during the rainy (kharif) season of 2016 and 2017, to find out the effect of different transplanting dates and hill densities of rice (Oryza sativa L.) under system of rice intensification (SRI) which was compared with conventional rice cultivation (CRC). The experiment was designed in factorial split-plot with 2 crop-establishment methods (SRI and CRC) and 3 transplanting dates (26 June, 10 and 25 July) in the main plot; and 4 different hill densities (20 cm × 10 cm, 20 cm × 20 cm, 25 cm × 20 cm and 25 cm × 25 cm) in the subplots and replicated thrice. With an increased grain yield of 5.71 t/ha, SRI-establishment showed a significant yield advantage of 0.83 t/ha coupled with 2.64% more consumptively used water and 1.29 kg/ha-mm more water-use efficiency over CRC. Results showed strong positive correlation (0.95**) between water-use efficiency (WUE) and yield attributes primarily the effective tillers/m2. Regression analysis revealed that irrespective of establishment methods, the consumptive use (CU) of water, accumulated incident photosynthetically active radiation (AIPAR), radiation-use efficiency (RUE) and heat-use efficiency (HUE) greatly influenced the grain yield. However, in SRI, WUE appeared to be an additional key determinant of grain yield. Between 2 establishment methods, SRI was found to be more competent in utilizing water and solar radiation owing to its ideal canopy environment.

Development of image-based wheat spike counter through a Faster R-CNN algorithm and application for genetic studies

Spike number (SN) per unit area is one of the major determinants of grain yield in wheat. Development of high-throughput techniques to count SN from large populations enables rapid and cost-effective selection and facilitates genetic studies. In the present study, we used a deep-learning algorithm, i.e., Faster Region-based Convolutional Neural Networks (Faster R-CNN) on Red-Green-Blue (RGB) images to explore the possibility of image-based detection of SN and its application to identify the loci underlying SN. A doubled haploid population of 101 lines derived from the Yangmai 16/Zhongmai 895 cross was grown at two sites for SN phenotyping and genotyped using the high-density wheat 660K SNP array. Analysis of manual spike number (MSN) in the field, image-based spike number (ISN), and verification of spike number (VSN) by Faster R-CNN revealed significant variation (P < 0.001) among genotypes, with high heritability ranged from 0.71 to 0.96. The coefficients of determination (R2) between ISN and VSN was 0.83, which was higher than that between ISN and MSN (R2 = 0.51), and between VSN and MSN (R2 = 0.50). Results showed that VSN data can effectively predict wheat spikes with an average accuracy of 86.7% when validated using MSN data. Three QTL Qsnyz.caas-4DS, Qsnyz.caas-7DS, and QSnyz.caas-7DL were identified based on MSN, ISN and VSN data, while QSnyz.caas-7DS was detected in all the three data sets. These results indicate that using Faster R-CNN model for image-based identification of SN per unit area is a precise and rapid phenotyping method, which can be used for genetic studies of SN in wheat.

Phenotyping diverse wheat genotypes under terminal heat stress reveal canopy temperature as critical determinant of grain yield

Phenotyping diverse wheat genotypes under terminal heat stress reveal canopy temperature as critical determinant of grain yield

CRISPR/Cas9 gene editing and natural variation analysis demonstrate the potential for HvARE1 in improvement of nitrogen use efficiency in barley.

Nitrogen is a major determinant of grain yield and quality. As excessive use of nitrogen fertilizer leads to environmental pollution and high production costs, improving nitrogen use efficiency (NUE) is fundamental for a sustainable agriculture. Here, we dissected the role of the barley abnormal cytokinin response1 repressor 1 (HvARE1) gene, a candidate for involvement in NUE previously identified in a genome-wide association study, through natural variation analysis and clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9)-mediated gene editing. HvARE1 was predominantly expressed in leaves and shoots, with very low expression in roots under low nitrogen conditions. Agrobacterium-mediated genetic transformation of immature embryos (cv. Golden Promise) with single guide RNAs targeting HvARE1 generated 22 T0 plants, from which four T1 lines harbored missense and/or frameshift mutations based on genotyping. Mutant are1 lines exhibited an increase in plant height, tiller number, grain protein content, and yield. Moreover, we observed a 1.5- to 2.8-fold increase in total chlorophyll content in the flag leaf at the grain filling stage. Delayed senescence by 10-14 d was also observed in mutant lines. Barley are1 mutants had high nitrogen content in shoots under low nitrogen conditions. These findings demonstrate the potential of ARE1 in NUE improvement in barley.

Quantifying morpho-physiological traits that describe canopy and biomass formation and partitioning processes for spring wheat genotypes grown under contrasting nitrogen supply

ABSTRACT Radiation interception, radiation use efficiency (RUE) and harvest index (HI) are the key determinants of grain yield in cereal species. However, little is known about how these traits affect grain yield among spring wheat genotypes grown under low and optimum nitrogen (N) fertiliser supply. We used two experiments, in a field (Experiment 1; 2017–2018) and glasshouse (Experiment 2; 2018–2019) to investigate the effects of these traits on grain yield. Grain yield increased by 35% with increasing N fertiliser supply to 8.80 t/ha in Experiment 1 and 151% to 8.33 t/ha in Experiment 2. Grain yield was lowest for ‘Reliance’ and highest for ‘Discovery’ in both experiments. Differences in grain yield were not associated with HI. As the RUE did not differ among genotypes, the yield differences were attributed to the different amounts of radiation intercepted; a result of the faster leaf area expansion rate (LAER) and subsequent higher maximum green leaf area index (GLAI), and a longer leaf area duration (LAD). The differences in LAER and maximum GLAI among the genotypes were associated with a differences in specific leaf area (cm2/g). Our results suggest that improved grain yields in spring wheat can be achieved by focusing breeding efforts on canopy characteristics to increase radiation interception.

Identification and Analysis of Genes Involved in Double Fertilization in Rice.

Double fertilization is a key determinant of grain yield, and the failure of fertilization during hybridization is one important reason for reproductive isolation. Therefore, fertilization has a very important role in the production of high-yield and well-quality hybrid of rice. Here, we used RNA sequencing technology to study the change of the transcriptome during double fertilization with the help of the mutant fertilization barrier (feb) that failed to finish fertilization process and led to seed abortion. The results showed that 1669 genes were related to the guided growth of pollen tubes, 332 genes were involved in the recognition and fusion of the male–female gametes, and 430 genes were associated with zygote formation and early free endosperm nuclear division. Among them, the genes related to carbohydrate metabolism; signal transduction pathways were enriched in the guided growth of pollen tubes, the genes involved in the photosynthesis; fatty acid synthesis pathways were activated by the recognition and fusion of the male–female gametes; and the cell cycle-related genes might play an essential role in zygote formation and early endosperm nuclear division. Furthermore, among the 1669 pollen tube-related genes, it was found that 7 arabinogalactan proteins (AGPs), 1 cysteine-rich peptide (CRP), and 15 receptor-like kinases (RLKs) were specifically expressed in anther, while 2 AGPs, 7 CRPs, and 5 RLKs in pistil, showing obvious unequal distribution which implied they might play different roles in anther and pistil during fertilization. These studies laid a solid foundation for revealing double fertilization mechanism of rice and for the follow-up investigation.