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Summary Hybrid crop varieties have been repeatedly demonstrated to produce significantly higher yields than their parental lines; however, the low efficiency and high cost of hybrid seed production has limited the broad exploitation of heterosis for cotton production. One option for increasing the yield of hybrid seed is to improve pollination efficiency by insect pollinators. Here, we report the molecular cloning and characterization of a semidominant gene, Beauty Mark (BM), which controls purple spot formation at the base of flower petals in the cultivated tetraploid cotton species Gossypium barbadense. BM encodes an R2R3 MYB113 transcription factor, and we demonstrate that GbBM directly targets the promoter of four flavonoid biosynthesis genes to positively regulate petal spot development. Introgression of a GbBM allele into G. hirsutum by marker‐assisted selection restored petal spot formation, which significantly increased the frequency of honeybee visits in G. hirsutum. Moreover, field tests confirmed that cotton seed yield was significantly improved in a three‐line hybrid production system that incorporated the GbBM allele. Our study thus provides a basis for the potentially broad application of this gene in improving the long‐standing problem of low seed production in elite cotton hybrid lines.

Red clover (Trifolium pratense L.) is an important forage legume grown in many of the temperate regions around the world. In order to evaluate possible causes for the low seed yield in particular in tetraploid red clover, we surveyed 71 studies of red clover seed production published from 1948 to 2019, reviewing seed yield components, pollination and reproductive traits. Seed yield components are recorded to contribute to and improve our understanding of the complex processes leading to the red clover seed yield. However, the measurement approaches varied largely among the studies, depending on whether the seed yield components are directly measured or calculated. Red clover seed production is dependent on insect pollen transfer. However, much uncertainty of pollination and reproductive success remains. Pollination conditions were often neglected: one third of the papers did not mention pollination conditions. The information that connects pollination and seed set are lacking, very few studies measured traits in floral morphology, ovule fertilisation and seed maturation. We suggest that consistent and comprehensive evaluation of pollination and reproductive success are required to improve our understanding of reasons for the low seed yield in red clover and hence the possibilities for future improvement.

Background One significant abiotic stressor that harms sesame productivity globally is drought. This investigation used six sesame genotypes to measure variance in many variables under irrigated and terminal drought stress environments. Growth characteristics (plant height, fruiting zone length, branches’ number), yield-related parameters (capsules’ number per plant, capsule’s length, 1000 seeds’ weight, seed yield per plant, and seed yield per feddan) and physiological characters (relative water content, chlorophyll A content, chlorophyll B content, chlorophyll A + B content, and proline concentration) of sesame were measured. Six drought indices (geometric mean productivity (GMP), mean productivity (MP), stress tolerance index (STI), tolerance index (TOL), stress susceptibility index (SSI) and, yield stability index (YSI)) were derived using seed yield per feddan. This study was aimed to investigate the effects of drought stress on the physiological and yield-related characteristics of the sesame genotypes and to find the qualities that were most helpful in selecting drought-resistant genotypes. Results The analysis of variance revealed significant differences in genotypes and water depletion ratios, as well as their interactions, for all growth variables, except the interaction between genotypes and water depletion ratios for plant height and relative water content. Line 13 (H. 102) had the highest branches’ number (6.85), capsules’ number per plant (239.33) and capsule’s length (3.35 cm) attributes under normal circumstances. Line 31 (H. 68) produced the maximum yield per plant (33.45 g) and feddan (679.83) and had the highest weight of 1000 seeds (3.9 g) under normal circumstances. Under the level (80% water depletion ratio), H. 68 had the highest amounts of chlorophyll A (5.73) and chlorophyll A + B (17.37) whereas H. 102 exhibited the highest concentration of chlorophyll B (5.73). The genotype H. 68 of sesame was found to have the greatest MP (650.35), GMP (649.32) and YI (1.16) indices followed by genotype H. 102. The Shandaweell 3 genotype resulted in the lowest SSI (36.92) and TOL (0.55) indices. Line 26 (H132) exhibited the highest average YSI values. Conclusions These data revealed that genotypes H. 102, H. 68 and Shandaweell 3 are the most drought-tolerant among the genotypes utilized in this study. These results may contribute to developing effective breeding techniques for drought-stressed sesame in the future.

Seed yield (SY) is the most important trait in rapeseed, is determined by multiple seed yield-related traits (SYRTs) and is also easily subject to environmental influence. Many quantitative trait loci (QTLs) for SY and SYRTs have been reported in Brassica napus; however, no studies have focused on seven agronomic traits simultaneously affecting SY. Genome-wide QTL analysis for SY and seven SYRTs in eight environments was conducted in a doubled haploid population containing 348 lines. Totally, 18 and 208 QTLs for SY and SYRTs were observed, respectively, and then these QTLs were integrated into 144 consensus QTLs using a meta-analysis. Three major QTLs for SY were observed, including cqSY-C6-2 and cqSY-C6-3 that were expressed stably in winter cultivation area for 3 years and cqSY-A2-2 only expressed in spring rapeseed area. Trait-by-trait meta-analysis revealed that the 144 consensus QTLs were integrated into 72 pleiotropic unique QTLs. Among them, all the unique QTLs affected SY, except for uq.A6-1, including uq.A2-3, uq.C1-2, uq.C1-3, uq.C6-1, uq.C6-5, and uq.C6-6 could also affect more than two SYRTs. According to the constructed high-density consensus map and QTL comparison from literatures, 36 QTLs from five populations were co-localized with QTLs identified in this study. In addition, 13 orthologous genes were observed, including five each gene for SY and thousand seed weight, and one gene each for biomass yield, branch height, and plant height. The genomic information of these QTLs will be valuable in hybrid cultivar breeding and in analyzing QTL expression in different environments.

Background Kentucky bluegrass ( Poa pratensis L.) panicle development is a coordinated process of cell proliferation and differentiation with distinctive phases and architectural changes that are pivotal to determine seed yield. Cytokinin (CK) is a key factor in determining seed yield that might underpin the second “Green Revolution”. However, whether there is a difference between endogenous CK content and seed yields of Kentucky bluegrass, and how CK-related genes are expressed to affect enzyme regulation and downstream seed yield in Kentucky bluegrass remains enigmatic. Results In order to establish a potential link between CK regulation and seed yield, we dissected and characterized the Kentucky bluegrass young panicle, and determined the changes in nutrients, 6 types of endogenous CKs, and 16 genes involved in biosynthesis, activation, inactivation, re-activation and degradation of CKs during young panicle differentiation of Kentucky bluegrass. We found that high seed yield material had more meristems compared to low seed yield material. Additionally, it was found that seed-setting rate (SSR) and lipase activity at the stage of spikelet and floret primordium differentiation (S3), as well as 1000-grain weight (TGW) and zeatin-riboside (ZR) content at the stages of first bract primordium differentiation (S1) and branch primordium differentiation (S2) showed a significantly positive correlation in the two materials. And zeatin, ZR, dihydrozeatin riboside, isopentenyl adenosine and isopentenyl adenosine riboside contents were higher in seed high yield material than those in seed low yield material at S3 stage. Furthermore, the expressions of PpITP3 , PpITP5 , PpITP8 and PpLOG1 were positively correlated with seed yield, while the expressions of PpCKX2 , PpCKX5 and PpCKX7 were negatively correlated with seed yield in Kentucky bluegrass. Conclusions Overall, our study established a relationship between CK and seed yield in Kentucky bluegrass. Perhaps we can increase SSR and TGW by increasing lipase activity and ZR content. Of course, using modern gene editing techniques to manipulate CK related genes such as PpITP3/5/8 , PpLOG1 and PpCKX2/5/7 , will be a more direct and effective method in Kentucky bluegrass, which requires further trial validation.

Soybean (Glycine max [L.] Merr) is an important crop, as both food for humans and feed for livestock in Cambodia, but the yields are low, due to use of low yielding genotypes and limited use of inputs. This study aimed to investigate the effects of different genotypes and different N and P fertilizer sources on growth, seed yield, and seed protein of soybean. Five genotypes (Sbung, Hongry, 98C81, ACS1, and Kaiabi) were grown under different N (90 kg N ha−1 from urea, nano-n, Nitroplus, and without N application as control) and P fertilizers (50 kg P ha−1 from Inorganic P, nano-p, Mykovam, and without P application as control) in two screenhouse experiments. Shoot, root, and nodulation traits, as well as seed yield and protein, were significantly affected by genotypes and different N and/or P fertilizer sources. Notably, while genotypes Sbung and 98C81 showed the highest yields among the genotypes, regardless of different N and P fertilizers, only Sbung had the highest seed protein. The application of different N and/or P sources significantly increased seed yield, compared to non-N and -P application. Specifically, seed yield and seed protein were higher when treated with nano-n or urea, and number of nodules, root biomass, and nodule dry weight was increased with Nitroplus, whereas seed yield and protein were higher with nano-p, Mykovam, and inorganic P. Application rate of 90 kg N ha−1 and 50 kg P ha−1 produced higher seed yield and its components and seed protein. We conclude that N and P application as well as Nitroplus inoculation can help increase seed yield of soybean in Cambodia.

The alpine meadows of the Tibetan Plateau play a crucial role in the grassland ecosystem. However, due to the rapid growth and strong competitiveness of broad-leaved grasses, the nutritional resources and living space available for Gramineae species are severely restricted in this region. Broad-leaved grasses and noxious weeds have evolved into dominant population, severely limiting grassland production in alpine meadows. A shortage of premium seeds limits grassland ecosystem restoration efforts. is regarded as a pioneer plant for restoring degraded grassland into meadows dominated by grasses, and for developing cultivated grassland in the Tibetan Plateau region, and the demand for native seeds of is increasing. Therefore, this study investigated the effect of combinations of four levels of a broad-leaved grass inhibitor (0, 0.9, 1.5, and 2.1 kg·hm ) crossed with four levels of nitrogen fertilizer (0, 75, 150, and 225 kg·hm ) on seed production of in Gannan alpine meadow of the Qinghai-Tibet Plateau. We observed that the grass inhibitor significantly ( < 0.05) influenced on fertile tillers (FT), spikelets per fertile tiller (SFT), seeds per spikelet (SS) and panicle length (PL), but not florets per spikelet (FS) ( = 0.145). Nitrogen fertilizer significantly influenced on FT, FS, SS, and PL ( < 0.001), but not SFT ( = 0.068). The interaction of the grass inhibitor and nitrogen fertilizer had no significant effect on any of these seed yield components ( > 0.05). Both the grass inhibitor and nitrogen fertilizer significantly influenced all indicators of seed production ( < 0.001), increasing their values in a dose-dependent manner. Moreover, their interaction proved significant for all indicators ( < 0.001), except for actual seed yield ( > 0.05), demonstrating their synergistic effects. The maximum thousand seed weight (4.66 g) and actual seed yield (365 kg·hm ) were observed at the highest doss of 2.1 kg·hm of grass inhibitor and 225 kg·hm of nitrogen fertilizer, which were 1.85-fold and 2.94-fold of the control, respectively. Furthermore, significantly positive correlations were observed among seed yield and all yield components. Pathway analysis showed that FT made significant direct contributions to the seed yield. This approach (using broad-leaved grass inhibitors and nitrogen fertilizer) effectively reduced competition from broad-leaved grasses and increased the proportion of in the plant community composition, thus alleviating the shortage of seeds for grassland ecological restoration.

In plants, green non-foliar organs are able to perform photosynthesis just as leaves do, and the seed-enclosing pod acts as an essential photosynthetic organ in legume and Brassica species. To date, the contribution of pod photosynthesis to seed yield and related components still remains largely unexplored, and in Arabidopsis thaliana, the photosynthetic activity of the silique (pod) is unknown. In this study, an Arabidopsis glk1/glk2 mutant defective in both leaf and silique photosynthesis was used to create tissue-specific functional complementation lines. These lines were used to analyze the contribution of silique wall photosynthesis to seed yield and related traits, and to permit the comparison of this contribution with that of leaf photosynthesis. Our results showed that, together with leaves, the photosynthetic assimilation of the silique wall greatly contributed to total seed yield per plant. As for individual components of yield traits, leaf photosynthesis alone contributed to the seed number per silique and silique length, while silique wall photosynthesis alone contributed to thousand-seed weight. In addition, enhancing the photosynthetic capacity of the silique wall by overexpressing the photosynthesis-related RCA gene in this tissue resulted in significantly increased seed weight and oil content in the wild-type (WT) background. These results reveal that silique wall photosynthesis plays an important role in seed-related traits, and that enhancing silique photosynthesis in WT plants can further improve seed yield-related traits and oil production. This finding may have significant implications for improving the seed yield and oil production of oilseed crops and other species with pod-like organs.

Background Studying the relationships between rapeseed seed yield (SY) and its yield-related traits can assist rapeseed breeders in the efficient indirect selection of high-yielding varieties. However, since the conventional and linear methods cannot interpret the complicated relations between SY and other traits, employing advanced machine learning algorithms is inevitable. Our main goal was to find the best combination of machine learning algorithms and feature selection methods to maximize the efficiency of indirect selection for rapeseed SY. Results To achieve that, twenty-five regression-based machine learning algorithms and six feature selection methods were employed. SY and yield-related data from twenty rapeseed genotypes were collected from field experiments over a period of 2 years (2019–2021). Root mean square error (RMSE), mean absolute error (MAE), and determination coefficient (R 2 ) were used to evaluate the performance of the algorithms. The best performance with all fifteen measured traits as inputs was achieved by the Nu-support vector regression algorithm with quadratic polynomial kernel function (R 2  = 0.860, RMSE = 0.266, MAE = 0.210). The multilayer perceptron neural network algorithm with identity activation function (MLPNN-Identity) using three traits obtained from stepwise and backward selection methods appeared to be the most efficient combination of algorithms and feature selection methods (R 2  = 0.843, RMSE = 0.283, MAE = 0.224). Feature selection suggested that the set of pods per plant and days to physiological maturity along with plant height or first pod height from the ground are the most influential traits in predicting rapeseed SY. Conclusion The results of this study showed that MLPNN-Identity along with stepwise and backward selection methods can provide a robust combination to accurately predict the SY using fewer traits and therefore help optimize and accelerate SY breeding programs of rapeseed.

Sesame is an important and specific oilseed crop with high quality. Here, we systematically investigated the relationships between plant seed yield (PSY) and nine related traits in 369 sesame core accessions under five environments. The PSY and related traits had general heritability ranging from 14% for PSY to 72% for height to the first capsule (FCH) and final flowering stage (FFS). Correlation analysis suggested that seven yield-related traits, including capsule number per plant (CNP, r = 0.67), capsule stem length (CSL, 0.56), thousand-seed weight (TSW, 0.26), plant height (PH, 0.24), FFS (0.17), initial flowering stage (IFS, − 0.16) and FCH (− 0.14) were the key factors associated with seed yield in sesame ( P  < 0.01). For the uniculm and branching groups, CNP, CSL, and TSW were the common key factors. Path analysis showed similar direct effects of these key factors on PSY. Association mapping identified 13 simple sequence repeat (SSR) markers significantly associated with the nine seed yield-related traits ( P  < 0.001). Among these, three SSR markers were repeatedly detected in two environments. Marker Hs635 was associated with the seed number per capsule (SNC). Hs345 was associated with the CNP. Hs618 was associated with the IFS in uniculm accessions. These results provide insights into the traits that influence PSY and their genetics in sesame.