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Background The plant architecture traits of maize determine the yield. Plant height, ear position, leaf angle above the primary ear and internode length above the primary ear together determine the canopy structure and photosynthetic efficiency of maize and at the same time affect lodging and disease resistance. A flat and tall plant architecture confers an obvious advantage in the yield of a single plant but is not conducive to dense planting and results in high rates of lodging; thus, it has been gradually eliminated in production. Although using plants that are too compact, short and density tolerant can increase the yield per unit area to a certain extent, the photosynthetic efficiency of such plants is low, ultimately limiting yield increases. Genetic mapping is an effective method for the improvement of plant architecture to identify candidate genes for regulating plant architecture traits. Results To find the best balance between the yield per plant and the yield per unit area of maize, in this study, the F2:3 pedigree population and a RIL population with the same male parent were used to identify QTL for plant height (PH), ear height (EH), leaf angle and internode length above the primary ear (LAE and ILE) in Changchun and Gongzhuling for 5 consecutive years (2016–2020). A total of 11, 13, 23 and 13 QTL were identified for PH, EH, LAE, and ILE, respectively. A pleiotropic consistent QTL for PH overlapped with that for EH on chromosome 3, with a phenotypic variation explanation rate from 6.809% to 21.96%. In addition, there were major consistent QTL for LAE and ILE, and the maximum phenotypic contribution rates were 24.226% and 30.748%, respectively. Three candidate genes were mined from the three consistent QTL regions and were involved in the gibberellin-activated signal pathway, brassinolide signal transduction pathway and auxin-activated signal pathway, respectively. Analysis of the expression levels of the three genes showed that they were actively expressed during the jointing stage of vigorous maize growth. Conclusions In this study, three consistent major QTL related to plant type traits were identified and three candidate genes were screened. These results lay a foundation for the cloning of related functional genes and marker-assisted breeding of related functional genes.

Wheat grain yield is affected by plant height, which is the total length of spike, the uppermost internode, and other elongated internodes. In this study, a population of recombinant inbred lines generated from a cross between two advanced winter wheat breeding lines were phenotyped over four locations/years and genotyped by using markers of genotyping-by-sequencing (GBS) and Diversity Array Technology (DArT) for mapping of genes for three traits, including spike length, the uppermost internode length, and plant height. Five genomic regions or quantitative trait loci (QTLs) were associated with candidate genes for these traits. A major QTL was associated with Q5A , and two novel haplotypes of Q5A were identified, one for a single nucleotide polymorphism (SNP) at position -2,149 in promoter region and the other for copy number variation. Compared with one copy Q5A on chromosome 5A in Chinese Spring, the novel haplotype of Q5A with two copies Q5A was found to generate spikes that are extremely compacted. A major QTL was associated with allelic variation in the recessive vrn-A1 alleles involving in protein sequences, and this QTL was associated with increased uppermost internode length but not with plant height. A major QTL for plant height was associated with Rht-B1b on chromosome 4B, but its effects could be compromised by two new minor QTLs on chromosome 7. Collectively, the favorable alleles from the four loci can be used to establish the optimal plant height in wheat.

Seedling vigor in tomatoes determines the quality and growth of fruits and total plant productivity. It is well known that the salient effects of environmental stresses appear on the internode length; the length between adjoining main stem node (henceforth called node). In this study, we develop a method for internode length estimation using image processing technology. The proposed method consists of three steps: node detection, node order estimation, and internode length estimation. This method has two main advantages: (i) as it uses machine learning approaches for node detection, it does not require adjustment of threshold values even though seedlings are imaged under varying timings and lighting conditions with complex backgrounds; and (ii) as it uses affinity propagation for node order estimation, it can be applied to seedlings with different numbers of nodes without prior provision of the node number as a parameter. Our node detection results show that the proposed method can detect 72% of the 358 nodes in time-series imaging of three seedlings (recall = 0.72, precision = 0.78). In particular, the application of a general object recognition approach, Bag of Visual Words (BoVWs), enabled the elimination of many false positives on leaves occurring in the image segmentation based on pixel color, significantly improving the precision. The internode length estimation results had a relative error of below 15.4%. These results demonstrate that our method has the ability to evaluate the vigor of tomato seedlings quickly and accurately.

To ascertain the effect of low-light stress (80 μmol·m−2·s−1) on cucumbers, we report on improving and breeding low-light-tolerant varieties by mining genes related to low-light tolerance. In this study, the quantitative trait locus (QTL) mapping of cucumber plant height and internode length under low-light stress was conducted using the F2 population, employing specific-length amplified fragment sequencing (SLAF-seq) and phenotypic analysis. A genetic map with a total length of 1114.29 c M was constructed from 1,076,599 SNPs, and 2233 single-nucleotide polymorphism (SNP) markers were distributed on seven linked groups, with an average map distance of 0.50 c M. Two QTLs related to plant height, CsPlH5.1 and CsPlH6.1, were detected on Chr.5 and Chr.6, with a cumulative contribution rate of 16.33%. The contribution rate (PVE), max LOD value, additive effect (ADD), and dominant effect (DOM) of CsPlH5.1 were 9.446%, 4.013, 1.005, and 0.563, respectively. CsPlH5.1 was located between 4,812,907 and 5,159,042 in the Gy14_V2.0 genome of cucumber, with a genetic distance of 0.32 Mb; the interval contained 41 candidate genes, and CsPlH6.1 was found to be located between Marker537985 (171.10 c M) and Marker537984 (171.55 c M), a range containing only one candidate gene. A total of 42 candidate genes related to photosynthesis, chloroplast development, abiotic stress, and plant growth were found in the location range associated with plant height. Simultaneously, a QTL (Csnd2_NdL6.1) for the second internode length was detected, and the max LOD, ADD, and DOM values were 5.689, 0.384, and −0.19, respectively. Csnd2_NdL6.1 was located between 29,572,188 and 29,604,215, with 0.03 Mb on Chr.6 including seven candidate genes. The molecular function of the CsGy6G032300 gene is involved with the binding of calcium ions, which may be related to the elongation and growth of plants; however, the population needs to be further expanded for acceptable localization verification. The results of this study provide a preliminary basis for the mining of essential genes of cucumber’s low-light tolerance and identifying low-light-tolerance genes.

IntroductionThe industrial cultivation of tomato seedlings requires a high degree ofuniformity and consistency in grading. However, traditional grading methods based on phenotypictraits such as leaf area and canopy width are susceptible to environmental conditions, therebylimiting the accuracy and efficiency of grading. Since cumulative internode length is relativelystable and closely correlated with seedling vigor, this study aims to develop an accurate methodfor measuring and grading the cumulative internode length of tomato seedlings.MethodsA tomato seedling cumulative internode length detection method, termedDSH_(Y)OLO (Deformable Convolution-SIoU-Haar Wavelet Downsampling YOLO), wasproposed based on the YOLOv8-seg framework. First, deformable convolution was introducedinto the backbone to enhance feature extraction for curved stems and occluded regions. Second,the original loss function was replaced with SIoU to improve the alignment between predictedregions and the actual stem structure. Third, a Haar wavelet downsampling module was embeddedinto the backbone to preserve high-frequency detail information and reduce information loss underocclusion conditions. An intelligent grading system was further developed to verify the practicalapplicability of the proposed method.ResultsExperimental results showed that DSH_(Y)OLO achieved a Precision of 96.1%, aRecall of 94.3%, and an mAP@0.5 of 92.1%. Compared with the baseline YOLOv8 model, theproposed method substantially improved segmentation performance for cumulative internoderegions in tomato seedlings. In prototype validation, the intelligent grading system achieved anaverage grading success rate of 87.50%, with an average cumulative internode length error of 8.0mm.DiscussionThe results indicate that DSH_(Y)OLO and the grading system can meet therequirements for large-scale grading and detection of tomato seedlings, demonstrating highdetection accuracy and success rates. This approach can provide insights for grading other types ofseedlings during their growth stages and offer support for seedling production and thedevelopment of intelligent agricultural equipment.

Background Identification of loci for grain yield (GY) and related traits, and dissection of the genetic architecture are important for yield improvement through marker-assisted selection (MAS). Two genome-wide association study (GWAS) methods were used on a diverse panel of 166 elite wheat varieties from the Yellow and Huai River Valleys Wheat Zone (YHRVWD) of China to detect stable loci and analyze relationships among GY and related traits. Results A total of 326,570 single nucleotide polymorphism (SNP) markers from the wheat 90 K and 660 K SNP arrays were chosen for GWAS of GY and related traits, generating a physical distance of 14,064.8 Mb. One hundred and twenty common loci were detected using SNP-GWAS and Haplotype-GWAS, among which two were potentially functional genes underpinning kernel weight and plant height (PH), eight were at similar locations to the quantitative trait loci (QTL) identified in recombinant inbred line (RIL) populations in a previous study, and 78 were potentially new. Twelve pleiotropic loci were detected on eight chromosomes; among these the interval 714.4–725.8 Mb on chromosome 3A was significantly associated with GY, kernel number per spike (KNS), kernel width (KW), spike dry weight (SDW), PH, uppermost internode length (UIL), and flag leaf length (FLL). GY shared five loci with thousand kernel weight (TKW) and PH, indicating significantly affected by two traits. Compared with the total number of loci for each trait in the diverse panel, the average number of alleles for increasing phenotypic values of GY, TKW, kernel length (KL), KW, and flag leaf width (FLW) were higher, whereas the numbers for PH, UIL and FLL were lower. There were significant additive effects for each trait when favorable alleles were combined. UIL and FLL can be directly used for selecting high-yielding varieties, whereas FLW can be used to select spike number per unit area (SN) and KNS. Conclusions The loci and significant SNP markers identified in the present study can be used for pyramiding favorable alleles in developing high-yielding varieties. Our study proved that both GWAS methods and high-density genetic markers are reliable means of identifying loci for GY and related traits, and provided new insight to the genetic architecture of GY.

Summary MYB transcription factors (TFs) have been reported to regulate the biosynthesis of secondary metabolites, as well as to mediate plant adaption to abiotic stresses, including drought. However, the roles of MYB TFs in regulating plant architecture and yield potential remain poorly understood. Here, we studied the roles of the dehydration‐inducible GmMYB14 gene in regulating plant architecture, high‐density yield and drought tolerance through the brassinosteroid (BR) pathway in soybean. GmMYB14 was shown to localize to nucleus and has a transactivation activity. Stable GmMYB14‐overexpressing (GmMYB14‐OX) transgenic soybean plants displayed a semi‐dwarfism and compact plant architecture associated with decreased cell size, resulting in a decrease in plant height, internode length, leaf area, leaf petiole length and leaf petiole angle, and improved yield in high density under field conditions. Results of the transcriptome sequencing suggested the involvement of BRs in regulating GmMYB14‐OX plant architecture. Indeed, GmMYB14‐OX plants showed reduced endogenous BR contents, while exogenous application of brassinolide could partly rescue the phenotype of GmMYB14‐OX plants. Furthermore, GmMYB14 was shown to directly bind to the promoter of GmBEN1 and up‐regulate its expression, leading to reduced BR content in GmMYB14‐OX plants. GmMYB14‐OX plants also displayed improved drought tolerance under field conditions. GmBEN1 expression was also up‐regulated in the leaves of GmMYB14‐OX plants under polyethylene glycol treatment, indicating that the GmBEN1‐mediated reduction in BR level under stress also contributed to drought/osmotic stress tolerance of the transgenic plants. Our findings provided a strategy for stably increasing high‐density yield and drought tolerance in soybean using a single TF‐encoding gene.

Influences of planting density and nitrogen rate have been investigated frequently in targeted wheat (Triticum aestivum L.) research. Few studies have investigated interactions between these inputs. The objective was to determine the combine effect of N and seeding rates on culm morph‐physiological traits for lodging tolerance and grain yield. The experiment used a split‐split randomized block design using two wheat varieties ‘AnNong0711’ and ‘YanNong19’, split by four seeding (180, 240, 300, and 375 × 104 ha−1) and four N rates (0, 180, 240, and 300 kg ha−1). Lodging traits of plant height, culm height center of gravity, and internode length, increased (p < .05) however, stem diameter, wall thickness, and stem breaking strength decreased with increasing N and seeding rate. Stem breaking strength was negatively correlated with culm height center of gravity (r = −.869, p = .01), internode length (r = −.872, p < .01), and lignin (r = −.746, p < .01) but positively correlated with internode diameter (r = .715, p < .05) and wall thickness (r = .696, p < .05). Culm lodging index and cellulose showed positive correlation (r = .807 and .913 respectively) with lignin. Compared to YanNong19, AnNong0711 showed higher grain yield and culm lodging index of 9 and 20.49%, respectively. For improved grain yield, 180 plants m−2 was optimal in surface combinations with 210 kg N ha−1 for AnNong0711 and 200 kg N ha−1 for YanNong19. These combinations of seeding and N rates could successfully mitigate lodging and improve grain yield.

Sorghum cultivar 'Kazetachi' has a unique internode length pattern, with a wavy shape that changes depending on the cultivation environment. It is regarded as a suitable material for analyzing the environmental factors affecting internode elongation. This study was conducted to clarify the relation between the final internode length at harvest and the increment of stem growth to establish a method to elucidate stem growth during the growing season. To confirm the internode elongation pattern, we sampled plants when each leaf had just expanded. The leaf number, plant length, and collar height of plants in the field were measured during the growing season. The internode elongation pattern of 'Kazetachi' resembled that reported in sweet sorghum, indicating that the elongation period of each internode can be estimated by recording the leaf number during the growing period. By measuring the plant length and the collar height as an index of stem growth, we can easily estimate the rapid elongation period of internode, which can be a peak or a trough in the internode length pattern during the growing period. The collar height during the growing period can be estimated by measuring the leaf number in the growth stage and recording the length of internodes and leaf sheaths at harvest. Even the plant length can be estimated by adding the leaf blade length to these traits. However, the collar height seemed to be a better index of stem growth than the plant length.

Summary Maize height is determined by the number of nodes and the length of internodes. Node number is driven by intercalary meristem formation and internode length by intercalary cell elongation, respectively. However, mechanisms regulating establishment of nodes and internode growth are unclear. We screened EMS‐induced maize mutants and identified a dwarf mutant zm66, linked to a single base change in TERMINAL EAR 1 (ZmTE1). Detailed phenotypic analysis revealed that zm66 (zmte1‐2) has shorter internodes and increased node numbers, caused by decreased cell elongation and disordered intercalary meristem formation, respectively. Transcriptome analysis showed that auxin signalling genes are also dysregulated in zmte1‐2, as are cell elongation and cell cycle‐related genes. This argues that ZmTE1 regulates auxin signalling, cell division, and cell elongation. We found that the ZmWEE1 kinase phosphorylates ZmTE1, thus confining it to the nucleus and probably reducing cell division. In contrast, the ZmPP2Ac‐2 phosphatase promotes dephosphorylation and cytoplasmic localization of ZmTE1, as well as cell division. Taken together, ZmTE1, a key regulator of plant height, is responsible for maintaining organized formation of internode meristems and rapid cell elongation. ZmWEE1 and ZmPP2Ac‐2 might balance ZmTE1 activity, controlling cell division and elongation to maintain normal maize growth.