High-quality Varieties Research Articles

High-Yield-Related Genes Participate in Mushroom Production.

In recent years, the increasing global demand for mushrooms has made the enhancement of mushroom yield a focal point of research. Currently, the primary methods for developing high-yield mushroom varieties include mutation- and hybridization-based breeding. However, due to the long breeding cycles and low predictability associated with these approaches, they no longer meet the demands for high-yield and high-quality varieties in the expansive mushroom market. Modern molecular biology technologies such as RNA interference (RNAi) and gene editing, including via CRISPR-Cas9, can be used to precisely modify target genes, providing a new solution for mushroom breeding. The high-yield genes of mushrooms can be divided into four categories based on existing research results: the genes controlling mycelial growth are very suitable for genetic modification; the genes controlling primordium formation are directly or indirectly regulated by the genes controlling mycelial growth; the genes controlling button germination are more difficult to modify; and the genes controlling fruiting body development can be regulated during the mycelial stage. This article reviews the current research status for the four major categories of high-yield-related genes across the different stages of mushroom growth stages, providing a foundation and scientific basis for using molecular biology to improve mushroom yield and promote the economic development of the global edible-mushroom industry.

Comprehensive Analysis of Phenotypic Traits in Chinese Cabbage Using 3D Point Cloud Technology

Studies on the phenotypic traits and their associations in Chinese cabbage lack precise and objective digital evaluation metrics. Traditional assessment methods often rely on subjective evaluations and experience, compromising accuracy and reliability. This study develops an innovative, comprehensive trait evaluation method based on 3D point cloud technology, with the aim of enhancing the precision, reliability, and standardization of the comprehensive phenotypic traits of Chinese cabbage. By using multi-view image sequences and structure-from-motion algorithms, 3D point clouds of 50 plants from each of the 17 Chinese cabbage varieties were reconstructed. Color-based region growing and 3D convex hull techniques were employed to measure 30 agronomic traits. Comparisons between 3D point cloud-based measurements of the plant spread, plant height, leaf area, and leaf ball volume and traditional methods yielded R2 values greater than 0.97, with root mean square errors of 1.27 cm, 1.16 cm, 839.77 cm3, and 59.15 cm2, respectively. Based on the plant spread and plant height, a linear regression prediction of Chinese cabbage weights was conducted, yielding an R2 value of 0.76. Integrated optimization algorithms were used to test the parameters, reducing the measurement time from 55 min when using traditional methods to 3.2 min. Furthermore, in-depth analyses including variation, correlation, principal component analysis, and clustering analyses were conducted. Variation analysis revealed significant trait variability, with correlation analysis indicating 21 pairs of traits with highly significant positive correlations and 2 pairs with highly significant negative correlations. The top six principal components accounted for 90% of the total variance. Using the elbow method, k-means clustering determined that the optimal number of clusters was four, thus classifying the 17 cabbage varieties into four distinct groups. This study provides new theoretical and methodological insights for exploring phenotypic trait associations in Chinese cabbage and facilitates the breeding and identification of high-quality varieties. Compared with traditional methods, this system provides significant advantages in terms of accuracy, speed, and comprehensiveness, with its low cost and ease of use making it an ideal replacement for manual methods, being particularly suited for large-scale monitoring and high-throughput phenotyping.

Exploring the Genetic Basis of Calonectria spp. Resistance in Eucalypts.

Selecting high-quality varieties with disease resistance by artificial crossbreeding is the most fundamental way to address the damage caused by Calonectria spp. in eucalypt plantations. However, understanding the mechanism of disease-resistant heterosis occurrence in eucalypts is crucial for successful crossbreeding. Two eucalypt hybrids, the susceptible EC333 (H1522 × unknown) and the resistant EC338 (W1767 × P9060), were screened through infection with Calonectria isolates, a pathogen that causes eucalypt leaf blight. RNA-Seq was performed on the susceptible hybrid, the disease-resistant hybrid, and their parents. The gene differential expression analysis showed that there were 3912 differentially expressed genes between EC333 and EC338, with 1631 up-regulated and 2281 down-regulated genes. The expression trends of the differential gene sets in P9060 and EC338 were similar. However, the expression trend of W1767 was opposite that of EC338. The similarity of the expression and the advantage of stress resistance in E. pellita suggested that genes with significant differences in expression likely relate to disease resistance. A GSEA based on GO annotations revealed that the carbohydrate binding pathway genes were differentially expressed between EC338 and EC333. The gene pathways that were differentially expressed between EC338 and EC333 revealed by the GSEA based on KEGG annotations were the sesquiterpenoid and triterpenoid biosynthesis pathways. The alternative splicing analysis demonstrated that an AS event between EC338 and EC333 occurred in LOC104426602. According to our SNP analysis, EC338 had 626 more high-impact mutation loci than the male parent P9060 and 396 more than the female parent W1767; W1767 had 259 more mutation loci in the downstream region than EC338, while P9060 had 3107 fewer mutation loci in the downstream region than EC338. Additionally, EC338 had 9631 more mutation loci in the exon region than EC333. Modules were found via WGCNA that were strongly and oppositely correlated with EC338 and EC333, such as module MEsaddlebrown, likely associated with leaf blight resistance. The present study provides a detailed explanation of the genetic basis of eucalypt leaf blight resistance, providing the foundation for exploring genes related to this phenomenon.

Genome-wide identification of kiwifruit K+ channel Shaker family members and their response to low-K+ stress

Background‘Hongyang’ kiwifruit (Actinidia chinensis cv ‘Hongyang’) is a high-quality variety of A. chinensis with the advantages of high yield, early ripening, and high stress tolerance. Studies have confirmed that the Shaker K+ genes family is involved in plant uptake and distribution of potassium (K+).ResultsTwenty-eight Shaker genes were identified and analyzed from the ‘Hongyang’ kiwifruit (A. chinensis cv ‘Hongyang’) genome. Subcellular localization results showed that more than one-third of the AcShaker genes were on the cell membrane. Phylogenetic analysis indicated that the AcShaker genes were divided into six subfamilies (I-VI). Conservative model, gene structure, and structural domain analyses showed that AcShaker genes of the same subfamily have similar sequence features and structure. The promoter cis-elements of the AcShaker genes were classified into hormone-associated cis-elements and environmentally stress-associated cis-elements. The results of chromosomal localization and duplicated gene analysis demonstrated that AcShaker genes were distributed on 18 chromosomes, and segmental duplication was the prime mode of gene duplication in the AcShaker family. GO enrichment analysis manifested that the ion-conducting pathway of the AcShaker family plays a crucial role in regulating plant growth and development and adversity stress. Compared with the transcriptome data of the control group, all AcShaker genes were expressed under low-K+stress, and the expression differences of three genes (AcShaker15, AcShaker17, and AcShaker22) were highly significant. The qRT-PCR results showed a high correlation with the transcriptome data, which indicated that these three differentially expressed genes could regulate low-K+ stress and reduce K+ damage in kiwifruit plants, thus improving the resistance to low-K+ stress. Comparison between the salt stress and control transcriptomic data revealed that the expression of AcShaker11 and AcShaker18 genes was significantly different and lower under salt stress, indicating that both genes could be involved in salt stress resistance in kiwifruit.ConclusionThe results showed that 28 AcShaker genes were identified and all expressed under low K+ stress, among which AcShaker22 was differentially and significantly upregulated. The AcShaker22 gene can be used as a candidate gene to cultivate new varieties of kiwifruit resistant to low K+ and provide a reference for exploring more properties and functions of the AcShaker genes.

Spatiotemporal expression analysis of jasmonic acid and saponin-related genes uncovers a potential biosynthetic regulation in Panax notoginseng.

Sanqi, the root of Panax notoginseng, has long been recognized for its therapeutic effects on cardiovascular diseases. Saponins, including ginsenosides and notoginsenosides, are the main bioactive components of P. notoginseng. The biosynthesis of saponins is closely related to the defense responses orchestrated by endogenous hormones. To provide new insights into the underlying role of phytohormone jasmonic acid (JA) in the synthesis and regulation of saponins, we performed an ultra-performance liquid chromatography analysis of different tissues of P. notoginseng aged 2-4 years. Moreover, by combined evaluation of saponin content and transcriptome profiling of each tissue, the spatial and temporal distribution of saponins was analyzed. N notoginsenoside R1, ginsenoside Rb1 and ginsenoside Rd accumulated in the underground tissues, including the root, tuqi, fibril and rhizome. In agreement with this data, the corresponding genes of the endogenous hormone JAs, especially coronatine insensitive 1 (COI1) and myelocytomatosis proteins 2 (MYC2), were predominantly expressed in the underground tissues. The tissue- and age-specific distribution of saponins was consistent with the expression of genes involved in JA biosynthetic, metabolic and signaling pathways. The present study has revealed the temporal and spatial effects of endogenous phtohormones in the synthesis and regulation of notoginsenosides, which will provide a significant impact on improving the ecological planting technology, cultivating new high-quality varieties and protecting the rare resources of medicinal P. notoginseng. © 2024 Society of Chemical Industry.

Phenotype identification and genome-wide association study of ear-internode vascular bundles in maize (Zea mays).

The vascular bundle in the ear-internode of maize is a key conduit for transporting photosynthetic materials between "source" and "sink", making it critically important to examine its micro-phenotypes and genetic architecture to identify advantageous characteristics and cultivate high-yielding and high-quality varieties. Unfortunately, the limited observation methods and scope of study precludes any comprehensive and systematic investigations into the microscopic phenotypes and genetic mechanisms of vascular bundle in maize ear-internode. In this study, 47 phenotypic traits were extracted in 495 maize inbred lines using micro computed tomography (Micro-CT) scanning technology and a deep learning-based phenotype acquisition method for stem vascular bundle, which included stem slice-related, epidermis zone-related, periphery zone-related, inner zone-related and vascular bundles-related traits. Phenotypic analysis indicated that there was extensive phenotypic variation of vascular bundle traits in ear-internode, especially that in the inner zone. Of these, 30 phenotypic traits with heritability greater than 0.70 were conducted for GWAS, and a total of 4,225 significant SNPs and 416 candidate genes with detailed functional annotations were identified. Furthermore, 20 genes were highly expressed in stem-related tissues, especially in maize internodes. Functional analysis of candidate genes indicated that the pathways obtained for candidate genes of different trait groups were distinct, mainly involved in vitamin synthesis and metabolism, transport of substances, carbohydrate derivative catabolic process, protein transport and localization, and anatomical structure development. The results of this study will help to further understand the phenotypic traits of stem vascular bundles and provide a reference for revealing the genetic mechanism of maize ear-internode vascular bundles.

Import Competition, Quality Upgrading, and Exporting: Evidence from the Peruvian Apparel Industry

Abstract This paper studies quality upgrading to escape competition from low-wage countries and proposes a new channel that does not rely on access to new inputs or markets. Informed by Peruvian apparel firms’ response to China’s WTO accession, I introduce factor specificity in a multi-product-firm model. Profitability losses due to competition in low-quality segments induce firms to reallocate specific factors to produce high-quality varieties for high-income countries. Gains from this channel are large. Using an observed quality measure, I show that import competition substantially increases domestic firms’ exports and high-quality export shares. Firms also reduce prices, resulting in additional welfare gains.

Adaptation of Farmers in Bengawan Solo Watershed in Facing Climate Change

Currently, climate change poses a threat to agriculture, including in the Bengawan Solo watershed. This study aims to explore farmers' perceptions of climate change and understand the adaptations they undertake. The study was conducted in Mejuwet Village, Sumberrejo Subdistrict, Bojonegoro Regency, using qualitative. This study involved six informants, consisting of three farmers and three farm laborers. The selection of informants was based on the criterion of having more than ten years of experience in farming. Data was collected using in-depth interview and observation. Subsequently, the data were analyzed using an interactive model. The study indicates that farmers have knowledge of and can articulate the climate changes they have encountered, albeit with some limitations in understanding, and they actively participate in adaptation efforts. Farmer adaptation encompasses technical modifications like establishing planting schedules and methods, and choosing high-quality varieties. Cultural adaptation encompasses traditions like the wiwitan ceremony. Social adaptation involves using social connections and prioritizing investments in children's schooling. Lastly, economic adaptation involves broadening job opportunities and liquidating assets.

Evaluation of Aromatic Characteristics and Potential Applications of Hemerocallis L. Based on the Analytic Hierarchy Process.

Hemerocallis L. possesses abundant germplasm resources and holds significant value in terms of ornamental, edible, and medicinal aspects. However, the quality characteristics vary significantly depending on different varieties. Selection of a high-quality variety with a characteristic aroma can increase the economic value of Hemerocallis flowers. The analytic hierarchy process (AHP) is an effective decision-making method for comparing and evaluating multiple characteristic dimensions. By applying AHP, the aromatic character of 60 varieties of Hemerocallis flowers were analyzed and evaluated in the present study. Headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS) was employed to identify volatile components in Hemerocallis flowers. Thirteen volatile components were found to contribute to the aroma of Hemerocallis flowers, which helps in assessing their potential applications in essential oil, aromatherapy, and medical treatment. These components include 2-phenylethanol, geraniol, linalool, nonanal, decanal, (E)-β-ocimene, α-farnesene, indole, nerolidol, 3-furanmethanol, 3-carene, benzaldehyde and benzenemethanol. The varieties with better aromatic potential can be selected from a large amount of data using an AHP model. This study provides a comprehensive understanding of the characteristics of the aroma components in Hemerocallis flowers, offers guidance for breeding, and enhances the economic value of Hemerocallis flowers.

Detection and Analysis of Quality Traits of Different Black Rice Varieties in the Southern Henan Rice Region

Using 14 black rice varieties imported from Southern Henan as experimental materials, the appearance quality, grinding quality, nutritional quality, cooking and eating quality of grain in Southern Henan were tested and analyzed by means of rice huller, rice mopping machine and near-infrared grain analyzer, combined with biochemical and physical analysis techniques. The results showed that there were abundant variation types in grain length, grain width, length-to-width ratio, brown rice rate, milled rice rate, head rice rate, soluble protein content, starch content, gelatinization temperature, gel consistency and viscosity of black rice. Particularly, grain type, starch content, gelatinization temperature, viscosity and other important quality traits in black rice materials have a large variation range. Therefore, our results provide important clues for developing new high-quality varieties of black rice.

Analysis of characteristic aromas of buckwheat with different germplasm using gas chromatography–mass spectrometry combined with chemometrics and multivariate statistical analysis

In this study, the volatile components in 40 samples of Tartary buckwheat and common buckwheat from 6 major producing areas in China were analyzed. A total of 77 volatile substances were identified, among which aldehydes and hydrocarbons were the main volatile components. Odor activity value analysis revealed 26 aromatic compounds, with aldehydes making a significant contribution to the aroma of buckwheat. Seven key compounds that could be used to distinguish Tartary buckwheat from common buckwheat were identified. The orthogonal partial least squares-discriminant analysis was effectively used to classify Tartary buckwheat and common buckwheat from different producing areas. This study provides valuable information for evaluating buckwheat quality, breeding high-quality varieties, and enhancing rational resource development.

BoPRR9, a pseudo-response regulator protein from cabbage, plays a negative regulatory role in the response to cold stress

Cold stress can adversely affect the growth, development, and yield of plants. Exploring the cabbage cold-stress-related genes and their regulatory mechanisms is crucial for cultivating high-quality varieties of cabbage. The PSEUDO RESPONSE REGULATOR (PRR) factor plays an important role in plant response to abiotic stress. However, cabbage BoPRRs in cold tolerance are rarely reported. In this study, the PRR family gene BoPRR9 was isolated from cabbage (Brassica oleracea var. capitata L) and functionally characterized in transgenic Arabidopsis and cabbage in cold stress response. BoPRR9 encodes a protein located in the nucleus. The gene was strongly induced by cold treatment, and the transcription level of BoPRR9 was up regulated under cold stress. Under cold stress, overexpression of BoPRR9 resulted in enhanced cold sensitivity in transgenic Arabidopsis and cabbage, lower antioxidant enzyme activity and maximum photosynthetic efficiency of photosystem II(Fv/Fm), and higher relative electrolyte leakage (REL) and malondialdehyde (MDA) content. Meanwhile, the ability of the transgenic plants to remove reactive oxygen species (ROS) was significantly reduced. Additionally, the expression levels of cold-related genes were downregulated in BoPRR9-overexpressing plants. The results showed that the BoPRR9 gene negatively regulates cold stress, which provides clues for further understanding of the molecular mechanism of PRR-mediated cold stress response.

Crop HTP Technologies: Applications and Prospects

In order to rapidly breed high-quality varieties, an increasing number of plant researchers have identified the functions of a large number of genes, but there is a serious lack of research on plants’ phenotypic traits. This severely hampers the breeding process and exacerbates the dual challenges of scarce resources and resource development and utilization. Currently, research on crop phenotyping has gradually transitioned from traditional methods to HTP technologies, highlighting the high regard scientists have for these technologies. It is well known that different crops’ phenotypic traits exhibit certain differences. Therefore, in rapidly acquiring phenotypic data and efficiently extracting key information from massive datasets is precisely where HTP technologies play a crucial role in agricultural development. The core content of this article, starting from the perspective of crop phenomics, summarizes the current research status of HTP technology, both domestically and internationally; the application of HTP technology in above-ground and underground parts of crops; and its integration with precision agriculture implementation and multi-omics research. Finally, the bottleneck and countermeasures of HTP technology in the current agricultural context are proposed in order to provide a new method for phenotype research. HTP technologies dynamically monitor plant growth conditions with multi-scale, comprehensive, and automated assessments. This enables a more effective exploration of the intrinsic “genotype-phenotype-environment” relationships, unveiling the mechanisms behind specific biological traits. In doing so, these technologies support the improvement and evolution of superior varieties.

Hyperspectral imaging combined with GA-SVM for maize variety identification.

The demand for identification of maize varieties has increased dramatically due to the phenomenon of mixed seeds and inferior varieties pretending to be high-quality varieties continuing to occur. It is urgent to solve the problem of efficient and accurate identification of maize varieties. A hyperspectral image acquisition system was used to acquire images of maize seeds. Regions of interest (ROI) with an embryo size of 10 × 10 pixel were extracted, and the average spectral information in the range of 949.43-1709.49 nm was intercepted for the subsequent study in order to eliminate random noise at both ends. Savitzky-Golay (SG) smoothing algorithm and multiple scattering correction (MSC) were used to pretreat the full-band spectrum. The feature wavelengths were screened by successive projection algorithms (SPA), competitive adaptive reweighted sampling (CARS) single screening, and two combinations of CARS-SPA and CARS + SPA, respectively. Support vector machines (SVMs) and models optimized based on genetic algorithm (GA), particle swarm optimization (PSO) were established by using full bands (FB) and feature bands as the model input. The results showed that the MSC-(CARS-SPA)-GA-SVM model had the best performance with 93.00% of the test set accuracy, 8 feature variables, and a running time of 24.45 s. MSC pretreatment can effectively eliminate the scattering effect of spectral data, and the feature wavelengths extracted by CARS-SPA can represent all wavelength information. The study proved that hyperspectral imaging combined with GA-SVM can realize the identification of maize varieties, which provided a theoretical basis for maize variety classification and authenticity identification.

ОЦЕНКА КАЧЕСТВА ПЛОДОВ ПЕРСПЕКТИВНЫХ ФОРМ ОРЕХА ГРЕЦКОГО ИЗ МЕСТНЫХ СЕМЕННЫХ ПОПУЛЯЦИЙ КРАСНОДАРСКОГО КРАЯ И БЕЛГОРОДСКОЙ ОБЛАСТИ

Recently, the task of updating the walnut assortment with new adaptive and high-quality varieties of domestic breeding has been solved, since foreign varieties cannot fully realize their biological potential in the conditions of the North Caucasus. In order to solve the issue of import substitution, it is necessary to create competitive, highly productive varieties with lateral fruiting, adaptive to unfavorable factors. At the same time, an extremely important characteristic of the variety is the quality of the fruit. The article presents the results of research on the search for promising forms of walnut. During the route trips, a preliminary assessment of the studied samples was carried out for the presence of lateral fruiting and fruit load, as a result of which 11 promising forms were identified for assessing the morphometric characteristics and quality of the fruits. All 11 selected forms of walnut are valuable for breeding and can serve as sources of economically useful traits (lateral fruiting, large fruit, high percentage of kernel yield, light, well-filled kernel, thin shell). Forms № 1, № 3, № 4, № 5, № 6, № 7, №. 8, № 10 can be considered the most promising in terms of the complex of phenotypic characteristics of fruits. These samples have an average (№ 1, № 5, № 7, № 8) and high (№ 3, № 4, № 6, № 11) percentage of kernel yield, good kernel extractability, kernel completion and can be used in breeding work, such as sources of economically valuable traits.

3-year results of hop hybrids testing

Chuvashia has long been the main hop producer in the Soviet Union. Today, the Tsivilsky district of Chuvashia is the northernmost point of the hop breeding process. To revive this crop in the hop farms of the Chuvash Research Institute of Agriculture, the study of hybrids of common hop (Humulus Lupulus L.), grown from seeds obtained from different combinations of varieties of the hop collection of the Chuvash Research Institute of Agriculture is being carried out. The aim of the work is to breed new high-yielding hop varieties of high quality, adapted to the agroclimatic conditions of Chuvashia. The planting of the selection and control nursery was carried out in 2015. The article presents the results of the research for 2020-2022. As a control, 2 varieties were taken. Standard 1 - Podvyazny, has long been the standard in terms of yield, quality, and stability. It belongs to the medium-maturing group of varieties. Standard 2 - Fakir, the best variety of the mid-early group from a series of recently developed varieties. Plants grown from seeds obtained from female plants of Saxon, Marinka, Late Cluster, Porphyry 16 and Plunscher were studied. Male plants of different varieties were used as pollinators by random pollination or by pollen mixture using isolators. A complex of economically useful traits was investigated. The main ones, yield and alpha acid content in cones, are given in the article. Depending on agroclimatic conditions during the years of research, separate hybrid combinations were assigned. Only two combinations - Porfir 16 × SR - 25.3 kg/ha, which showed itself as a medium-ripening variety with an alpha acid content of 5.2% and Saxon × SR - 33 kg/ha - showed itself as a medium-early variety with an alpha acid content of 6.1%. Several combinations also outperformed Podvyazny in some years, either in terms of yield or quality, but there was no consistent outperformance in all three years.

Detection of sweet corn seed viability based on hyperspectral imaging combined with firefly algorithm optimized deep learning.

The identification of sweet corn seed vitality is an essential criterion for selecting high-quality varieties. In this research, a combination of hyperspectral imaging technique and diverse deep learning algorithms has been utilized to identify different vitality grades of sweet corn seeds. First, the hyperspectral data of 496 seeds, including four viability-grade seeds, are extracted and preprocessed. Then, support vector machine (SVM) and extreme learning machine (ELM) are used to construct the classification models. Finally, the one-dimensional convolutional neural networks (1DCNN), one-dimensional long short-term memory (1DLSTM), the CNN combined with the LSTM (CNN-LSTM), and the proposed firefly algorithm (FA) optimized CNN-LSTM (FA-CNN-LSTM) are utilized to distinguish spectral images of sweet corn seeds viability grade. The findings from the experimental analysis indicate that the deep learning models exhibit a significant advantage over traditional machine learning approaches in the discrimination of seed vitality levels, boasting a classification accuracy exceeding 94.26% in test datasets and achieving an accuracy improvement of at least 3% compared to the best-performing machine learning model. Moreover, the performance of the FA-CNN-LSTM model proposed in this study demonstrated a slight superiority over the other three models. Besides, the FA-CNN-LSTM achieved a classification accuracy of 97.23%, representing a significant improvement of 2.97% compared to the lowest-performing CNN and a 1.49% enhancement over the CNN-LSTM. In summary, this study reveals the potential of integrating deep learning with hyperspectral imaging as a promising alternative for discriminating sweet corn seed vitality grade, showcasing its value in agricultural research and cultivar breeding.

Wheat cultivars grain yield and quality traits variability under conditions of southern Pannonian plain

In order to meet milling industry and grain producers' requirements, wheat grain needs to possess good technological quality, and high and stable grain production. This study analyzed 30 varieties of winter wheat over four growing seasons (2015/16, 2016/17, 2017/18, and 2018/19) at the location Rimski Šančevi, Serbia. The studied traits were under the control of genotype, environment, and their interaction. The analysis of variance (ANOVA) revealed that the influence of the factors varied depending on the studied trait. Thousand grain weight showed the highest variability depending on genotype influence, protein content and sedimentation value that were mostly affected by environmental conditions, while the genotype and environment interaction had the greatest impact on hectoliter weight and grain yield. Using principal component analysis significant positive relationship was observed between protein content and sedimentation value, and between thousand grain weight and hectoliter weight. It was also shown that yield and thousand grain weight, sedimentation value and hectoliter weight are positively related. A strong negative association was noted between grain yield and protein content. The protein content and hectoliter weight did not show any dependency. All analyzed traits are significant for breeding programs, emphasizing the importance of developing high-quality varieties with high yield potential and tolerance to adverse environmental conditions.

Efficiency and genotypic quality potential of winter wheat grain in the central chernozem region

Winter wheat in Russia occupies more than half of the sown areas of grain crops and more than 70% of winter crops. Advanced farms with a high culture of farming (crop rotations, fertilisers, soil treatment, etc.). The yield of this crop is more than 40 kg per 1 ha. One of the reasons is the lack of scientifically substantiated varietal technology of cultivation of this crop in relation to soil-climatic and regional zones. As subjects of research, promising varieties, Skipetr,Moscovskaya 56, and Zorro were used. The research was conducted in 2020-2022 in the conditions of the foothill zone of the farm “Dubovitskoe” Maloarkhangelsky district of Orel region. The paper considers the economic value of the variety, which is determined by the totality of biological and technological, food, and baking properties of high-quality varieties of agricultural crops. The choice of high-quality varieties of winter wheat and the use of the genetic resource of the variety is a decisive factor in increasing the yield of many agricultural crops, including winter wheat. When selecting the seed, it is worthwhile to assess it competently and understand all the risks of its cultivation. For many years, breeders around the world have been working on developing new productive and productive varieties. Much attention should be paid to the adaptive adaptation of varieties to external environmental conditions, which will depend on how much stable it will be possible to obtain for the programmed yield. The result of the work done shows that the new varieties under study are not inferior but superior to the control variety, which was required to be proved.

The influence of quince rootstock forms on the survival and growth of pear varieties in the nursery

Pear is an important cash crop, the quality, variety and types of which vary depending on the place of growth. It is believed that undersized rootstocks not only simplify the technology of its cultivation, but also accelerate the entry into fruiting. Currently, the selection of existing high-quality varieties compatible with low-growing rootstocks is a serious problem faced by gardeners growing this crop. The aim of the study was to identify the compatibility of local adaptive pear varieties with rootstock forms of quince and to study the biometric indicators of rootstock-graft combinations when grown in a nursery. The assessment of the impact of undersized quince rootstocks on the survival and development of local pear varieties in the nursery was carried out according to generally accepted methods from 2016 to 2022. The study of the parameters of accretion and development of the components of graft was evaluated visually. Biometric data were obtained by instrumental and computational methods from a random sample of healthy plants. The most promising variety – rootstock combinations in the nursery were identified, their biometric parameters were determined and a visual assessment of compatibility in the nursery was carried out. According to all the studied indicators, the best rootstock for pear varieties was the form of quince rootstock No. 1.