Diverse Cultivars Research Articles

EVALUATION OF OAT VARIETIES UNDER SUFFICIENT AND INSUFFICIENT IRRIGATION

This study was aimed to investigate the genetic variations of Oat cultivars under in sufficient of irrigation. A field experiment was carried out at the fields of with College of Agricultural Engineering Sciences ;University of Baghdad - Al-Jadriya during 2020-2021 seasons. The experiment was carried out using a Completely Block designwithin split-plot arrangement using three replicates under two treatments (verities and irrigation intervals). The main plots were irrigation intervals with moisture(50%, 25%, and 10%), while sub-plots were the varieties (Genzania, Anatolia, Plmula, Algoda, and Al-Shifa).The results showed that the third irrigation level had 75% flowering at highest averages93.67 days , and the V4 variety had the lowest average to weight of 250 grains about (7.67 g ).While there was a significant differencesamong irrigation interval 75% flowering compared with other traits ( 22.8) ,(24.6 )and ( 7.75) respectively. While the Alogoda produced the highest yield (7.49 ton .h-1) compared with the lowest Plmula gave (5.83 ton h-1)There are differences among of varieties under irrigation intervals. The highest genotypic coefficient to yield (94.7%) and the highest value of heritability was (98.75%).to the flowering.

SSR-BASED ASSESSMENT OF GENETIC DIVERSITY IN TOMATO CULTIVARS AND LINES GROWN IN KAZAKHSTAN

Tomato (Solanum lycopersicum L.) is a versatile crop known for its nutritional value and health benefits, thriving in diverse climates worldwide. Nevertheless, regional variations persist in tomato yield, with Kazakhstan serving as an example of lower productivity in contrast to global averages. Closing this disparity requires comprehensive genetic studies and breeding efforts. This study is focused on the genetic diversity of 49 tomato cultivars and hybrids sourced from Kazakh Research Institute of Fruit and Vegetable Growing (Almaty), employing 10 SSR markers associated with important agronomic traits. SSR genotyping unveiled polymorphisms across 6 markers with variable allele numbers. Genetic diversity metrics highlighted significant genetic diversity within both outdoor and greenhouse tomato cultivars and lines. Bayesian clustering, Neighbor-joining (NJ) clustering, and principal coordinate analysis (PCoA) delineated genetic differentiation between outdoor and greenhouse tomatoes with small admixture, indicating distinct breeding directions for these two types. Highly polymorphic SSRs (PIC > 0.5) associated with essential fruit traits emerge as promising targets for marker-assisted selection (MAS) that can be used to enhance tomato breeding efficiency in Kazakhstan. According to 8 SSRs, 22 out of 30 outdoor accessions and 8 greenhouse tomato accessions were genetically uniform. This study offers comprehensive insights into the genetic diversity and population structure of tomato cultivars and lines in Kazakhstan, laying the foundation for informed breeding endeavors aimed at bolstering yield and resilience in tomato crops.

Morphometric Analysis of Grape Seeds: Looking for the Origin of Spanish Cultivars

The Vitis IMIDRA collection contains 3699 entries, representing a significant percentage of the variation in traditional and commercial Vitis cultivars used in Spain. The classification and identification of new entries are currently conducted based on ampelography and molecular methods. Here, we propose a new method of classification of the cultivars based on seed morphology and its application to a total of 224 varieties from the collection. Based on seed shape, fourteen groups have been defined according to the similarity of the seeds, with geometric figures used as models. The new models are Cariñena Blanca, Chardonnay, Parraleta, and Parduca, defining new groups to be added to the ten groups previously described. The study results in 14 groups comprising the Spanish cultivar’s seed shape and morphological variation. Seed morphology can help to identify varieties cultivated in the past through archaeological finds.

Selection of Stable Reference Genes for QRT-PCR in Tree Peony 'Doulv' and Functional Analysis of PsCUC3.

(1) Background: Tree peonies display extensive cultivar diversity due to widespread hybridization, resulting in a complex genetic architecture. This complexity complicates the selection of universal reference genes across different cultivars for qRT-PCR analyses. Paeonia suffruticosa 'Doulv', notable for its unique green blooms in China, exhibits chlorosis post-flowering and features petaloid stamens and pistils. (2) Methods: Based on published literature and RNA-seq data from 'Doulv', nine candidate reference genes-ACT (Actin), TUB (β-Tubulin), UBC (Ubiquitin Conjugating Enzyme), UBQ (Ubiquitin), UPL (Ubiquitin Protein Ligase), PP2A (Protein Phosphatase 2A), PP2C (Protein Phosphatase 2C), MBF1A (Multiprotein Bridging Factor 1A), and GAPDH (Glyceraldehyde-3-Phosphate Dehydrogenase)-were selected. Their expression stability was assessed across various tissues and developmental stages of 'Doulv' flowers using qRT-PCR, with evaluations conducted via GeNorm_v3.5, NormFinder_v20, and BestKeeper_v1.0. Gene cloning and expression analyses of PsCUC3, including its subcellular localization, were performed. (3) Results: GAPDH and ACT were identified as the most stable reference genes in petaloid stamens across various developmental stages of 'Doulv', whereas UBC and MBF1A were optimal across different tissues. Notably, specific conserved amino acids in PsCUC3 from 'Doulv' diverged from those in NAM/CUC3 proteins of other species, impacting its protein structure. PsCUC3 expression analysis revealed no correlation with chlorophyll content in petaloid stamens but an association with petaloid organ development. Furthermore, PsCUC3 was predominantly localized in the nucleus. (4) Conclusions: This study comprehensively evaluated suitable reference genes using GeNorm_v3.5, NormFinder_v20, and BestKeeper_v1.0 software, establishing a robust qRT-PCR detection system for 'Doulv' peony. These results provide a solid experimental foundation for further research on 'Doulv' peony. Building on this experimental foundation, the functional analysis of the PsCUC3 gene was conducted. The findings suggest a potential association between the PsCUC3 gene and floral morphology alterations in 'Doulv', identifying PsCUC3 as crucial for understanding the molecular mechanisms influencing floral structure in tree peonies.

A comprehensive analysis of the WRKY family in soybean and functional analysis of GmWRKY164-GmGSL7c in resistance to soybean mosaic virus

BackgroundSoybean mosaic disease caused by soybean mosaic virus (SMV) is one of the most devastating and widespread diseases in soybean producing areas worldwide. The WRKY transcription factors (TFs) are widely involved in plant development and stress responses. However, the roles of the GmWRKY TFs in resistance to SMV are largely unclear.ResultsHere, 185 GmWRKYs were characterized in soybean (Glycine max), among which 60 GmWRKY genes were differentially expressed during SMV infection according to the transcriptome data. The transcriptome data and RT-qPCR results showed that the expression of GmWRKY164 decreased after imidazole treatment and had higher expression levels in the incompatible combination between soybean cultivar variety Jidou 7 and SMV strain N3. Remarkably, the silencing of GmWRKY164 reduced callose deposition and enhanced virus spread during SMV infection. In addition, the transcript levels of the GmGSL7c were dramatically lower upon the silencing of GmWRKY164. Furthermore, EMSA and ChIP-qPCR revealed that GmWRKY164 can directly bind to the promoter of GmGSL7c, which contains the W-box element.ConclusionOur findings suggest that GmWRKY164 plays a positive role in resistance to SMV infection by regulating the expression of GmGSL7c, resulting in the deposition of callose and the inhibition of viral movement, which provides guidance for future studies in understanding virus-resistance mechanisms in soybean.

An Economic Analysis of Market Acceptance and Performance of Rice Varieties Grown in Northern Telangana Zone

This study aims to conduct an economic analysis of market acceptance and performance of rice varieties grown in the Northern Telangana Zone, where diverse rice cultivars face cultivation and marketing challenges. The objectives are to identify and document rice cultivars released by PJTSAU, study technological attributes preferred by stakeholders, and document constraints faced by stakeholders. A purposive sampling technique was used to select 90 farmers, 30 traders, and 30 consumers, totaling 150 participants. Data were collected using well-developed schedules and analyzed using tabular analysis, Rice Preference Index (RPI), Garrett ranking technique, and other suitable methods. The results showed that Telangana Sona (RNR 15048) is highly favored for its long grain size, high head rice recovery, and strong market demand, despite its susceptibility to stem borer and higher fertilizer requirements. Pranahitha (JGL 11727) is appreciated for its good rice quality but faces significant challenges, including high susceptibility to lodging, pests, and diseases, and lower germination rates. Kunaram Rice-1 (KNM 733) showed acceptable profitability but struggled with low market demand, poor grain quality, and higher water requirements. The study concludes that while Telangana Sona excels in market appeal and profitability, Pranahitha and Kunaram Rice-1 need targeted interventions to overcome their specific constraints. Enhancing pest resistance, improving grain quality, and reducing input requirements are essential for optimizing the potential of these varieties. Addressing these challenges through improved management practices and technology adoption can significantly benefit farmers and boost the marketability of these paddy varieties.

TAXONOMIC STRUCTURE AND FEATURES OF ALLERGENIC AEROPALYNODENDROFLORA IN THE GREENING OF THE CITY OF CHERNIHIV (CHERNIHIV REGION, LEFT-BANK POLISSIA, UKRAINE)

The first comprehensive assessment was conducted to study the allergenic aeropalynodendroflora in the greening of the Left-Bank Polissia region territories, using the example of the city of Chernihiv, Chernihiv region (taxonomic composition, biomorphological, ecological structure, frequency of occurrence, distribution).Based on the original research results, we found that the allergenic aeropalynodendroflora comprises 82 species, 18 cultivars, 26 genera, 16 families (Magnoliophyta – 59 species, 19 genera, 14 families, Pinophyta – 23 species, 7 genera, 2 families). The most numerous in terms of species are the families Pinaceae – 12 species (Pinus (8 species), Picea (4), Cupressaceae – 11 species (Juniperus (5); among angiosperms – Salicaceae – 20 species (Salix (15), Populus (5)), Aceraceae – 8 species (Acer (8). The most diverse cultivars are Thuja occidentalis (7), Juniperus sabina (3), Acer palmatum (3). Frequency analysis revealed that 36 species are widespread; while representatives of 43 species are rare (most are found in collection sites). We identified the locations of species according to their distribution by different types of urban plantings, with 10 species found in all types of plantings and 22 species found in public areas as part of the greening structure. It was determined that trees are the dominant life form in plantings (65 species: deciduous (47), evergreen (18)). In terms of height, there was a predominance of trees of the I size (27 species) and bushes of the I size (8) was noted. It has been established that most species have a high adaptive capacity to the natural and ecological conditions of urban ecotopes, with a significant proportion being oligotrophs (41 species) in terms of soil demand; mesophytes (43 species) in terms of soil moisture; and heliophytes (39 species) in terms of light requirement.

Large gradient of susceptibility to esca disease revealed by long-term monitoring of 46 grapevine cultivars in a common garden vineyard

Grapevine (Vitis vinifera L.) is prone to many fungal diseases, including esca, a severe vascular disease threatening the wine sector and for which there is no cost-effective cure. Susceptibility to esca varies between cultivars in different infection conditions. It may therefore be possible to use the genetic diversity of grapevine cultivars to mitigate disease impact. However, the genetic component of esca susceptibility has rarely been investigated in the vineyard, and the specific mechanisms and varietal traits underlying esca susceptibility remain unknown.In this study, we monitored the incidence and severity of esca foliar symptoms and plant dieback (apoplexy and mortality) at plant level for seven years, on 46 cultivars planted in an experimental common garden, to separate the genetic component of esca susceptibility from the effects of environment and cropping practices. We observed a broad gradient of varietal susceptibility, with a mean incidence of 0 to 26 % of vines expressing esca foliar symptoms depending on the variety. This gradient remained similar across years and, unlike the severity of foliar symptoms, the incidence of grapevine dieback was significantly correlated with that of foliar symptoms. We detected a significant but weak and very localised phylogenetic signal for the incidence of esca foliar symptoms in this panel of cultivars.We then explored the relationships between epidemiological metrics and ecophysiological and phenological traits phenotyped on the same plot. Esca disease incidence was negatively correlated with δ13C across cultivars, suggesting that varieties with higher water use efficiency are less prone to the expression of esca symptoms on leaves. Moreover, the least vigorous cultivars were among the least susceptible, although this relationship was not significant. By contrast, neither phenological stages nor nitrogen status were significantly predictive of cultivar susceptibility to the disease.Together, these results provide new insight into the potential of genetic resources for use in the sustainable management of grapevine trunk diseases and open up new perspectives for studying the pathological and physiological determinants of their incidence.

Classification of Grapevine Varieties Using UAV Hyperspectral Imaging

Classifying grapevine varieties is crucial in precision viticulture, as it allows for accurate estimation of vineyard row growth for different varieties and ensures authenticity in the wine industry. This task can be performed with time-consuming destructive methods, including data collection and analysis in the laboratory. In contrast, unmanned aerial vehicles (UAVs) offer a markedly more efficient and less restrictive method for gathering hyperspectral data, even though they may yield data with higher levels of noise. Therefore, the first task is the processing of these data to correct and downsample large amounts of data. In addition, the hyperspectral signatures of grape varieties are very similar. In this study, we propose the use of a convolutional neural network (CNN) to classify seventeen different varieties of red and white grape cultivars. Instead of classifying individual samples, our approach involves processing samples alongside their surrounding neighborhood for enhanced accuracy. The extraction of spatial and spectral features is addressed with (1) a spatial attention layer and (2) inception blocks. The pipeline goes from data preparation to dataset elaboration, finishing with the training phase. The fitted model is evaluated in terms of response time, accuracy and data separability and is compared with other state-of-the-art CNNs for classifying hyperspectral data. Our network was proven to be much more lightweight by using a limited number of input bands (40) and a reduced number of trainable weights (560 k parameters). Hence, it reduced training time (1 h on average) over the collected hyperspectral dataset. In contrast, other state-of-the-art research requires large networks with several million parameters that require hours to be trained. Despite this, the evaluated metrics showed much better results for our network (approximately 99% overall accuracy), in comparison with previous works barely achieving 81% OA over UAV imagery. This notable OA was similarly observed over satellite data. These results demonstrate the efficiency and robustness of our proposed method across different hyperspectral data sources.

Comprehensive studies reveal physiological and genetic diversity in traditional rice cultivars for UV-B sensitivity

Acclimation to crop niches for thousands of years has made indigenous rice cultivars better suited for stress-prone environments. Still, their response to UV-B resiliency is unknown. 38 rice landraces were grown in cemented pots in a randomised block design with three replicates under open field conditions in Sambalpur University in the wet season of 2022. Half of the plants in each of the cultivars were administered UV-B radiation at the panicle emergence stage in an adjustable UV-B chamber permitting sunlight, and the effects of the stress on various morpho-physiological features, such as spikelet sterility, flag leaf photosynthetic and flavonoid pigment contents, and lipid peroxidation activities, were estimated for calibration of stress resistance. The experiment identified Swarnaprabha and Lalkain as the most sensitive and resilient to stress respectively, and the differential response between them was further revealed in the expression of genes related to UV-B sensitivity. Subject to the stress, Swarnaprabha exhibited symptoms of injuries, like leaf burns, and a higher loss of various photosynthetic parameters, such as pigment contents, SPAD and Fv/Fm, ETR and qP values, while NPQ increased only in Lalkain. Exposure to UV-B increased the total phenolic and flavonoid contents in Lalkain while depressing them in Swarnaprabha. Such an effect amounted to a higher release of fluorescent energy in the latter. The levels of expression of gene families controlling flavonoid activation and UV-B signal transduction, such as OsWRKY, OsUGT, OsRLCK, OsBZIP, OsGLP, and CPD photolyase were similar in both the cultivars in the control condition. However, exposure to UV-B stress overexpressed them in resilient cultivars only. The magnitude of expression of the genes and the impact of the stress on photosynthetic parameters, phenolic compounds and pubescent hair structure at the panicle emergence stage could be valid indicators among indigenous rice for UV-B tolerance.

Phenotypic Diversity of Pomegranate Cultivars: Discriminating Power of Some Morphological and Fruit Chemical Characteristics

In modern agricultural production, where a small number of commercial cultivars dominate, the collection, evaluation, and preservation of germplasm are important tasks to reduce the erosion of genes and preserve biodiversity. The aim of this study is to characterize the morphological and fruit chemical properties of the pomegranate germplasm grown on the East Adriatic coast, including the commercial cultivars ‘Hicaznar’, ‘Granada’, and ‘Wonderful’, and to highlight the characteristics with the greatest discriminating power. The characterization of the tree, leaf, flower, arils, seed, and juice was carried out using the UPOV descriptor. The colors of the peel, arils, and juice were analyzed according to the CIEL*a*b* method, total soluble solids were measured using refractometers, and total acidity was determined by titration with 0.1 M NaOH. The research results showed significant diversity between the cultivars, which were grouped into several clusters using an unsupervised analysis technique. Factors such as plant vigor, plant growth habit, predominant number of leaves per node on young shoots, crown type, fruit shape, fruit shape in cross-section, peel weight, total aril weight, aril weight, number of arils per fruit, seed length and width, seed yield, total acidity, TSS/TA ratio, and color parameters of the peel, arils, and juice showed high variability, indicating their strong discriminating power in determining the phenotypic diversity of pomegranate.

Chromosome-Scale Genome Assembly and Characterization of Top-Quality Japanese Green Tea Cultivar 'Seimei'.

Japanese green tea, an essential beverage in Japanese culture, is characterized by the initial steaming of freshly harvested leaves during production. This process efficiently inactivates endogenous enzymes such as polyphenol oxidases, resulting in the production of sencha, gyokuro and matcha that preserves the vibrant green color of young leaves. Although genome sequences of several tea cultivars and germplasms have been published, no reference genome sequences are available for Japanese green tea cultivars. Here, we constructed a reference genome sequence of the cultivar 'Seimei', which is used to produce high-quality Japanese green tea. Using the PacBio HiFi and Hi-C technologies for chromosome-scale genome assembly, we obtained 15 chromosome sequences with a total genome size of 3.1 Gb and an N50 of 214.9 Mb. By analyzing the genomic diversity of 23 Japanese tea cultivars and lines, including the leading green tea cultivars 'Yabukita' and 'Saemidori', it was revealed that several candidate genes could be related to the characteristics of Japanese green tea. The reference genome of 'Seimei' and information on genomic diversity of Japanese green tea cultivars should provide crucial information for effective breeding of such cultivars in the future.

Breadmaking Quality Parameters of Different Varieties of Triticale Cultivars.

The aim of this research is to investigate the quality of different triticale cultivars (Ingen 35, Ingen 33, Ingen 93, Ingen 54, Ingen 40, Fanica and Costel) cultivated in the Republic of Moldova from the point of view of the flour, dough, and bread quality characteristics. This research may be of great importance for producers and consumers due to the high production capacity, wide adaptability, economic significance in human foods and nutritional value of triticale cultivars. The triticale flours were analyzed for moisture, ash, protein, wet gluten, fat, carbohydrates, acidity and color parameters (L*, a* and b* values). According to the chemical values, the triticale flours were suitable for breadmaking. The moisture content was less than 14% for all triticale varieties, indicating a long shelf life during its storage and the lowest protein content of 13.1%. The mixing, pasting and fermentation characteristics of triticale dough were analyzed using Mixolab, falling number, dynamic rheometer, alveograph and rheofermentometer devices. All triticale flours presented high levels of α-amylase, with falling number values being less than 70 s. The bread quality characteristics analyzed were the loaf volume, porosity, acidity, and sensory characteristics, and the textural parameters examined were the hardness, gumminess, chewiness, cohesiveness, and resilience. Our data showed large differences in breadmaking quality parameters. However, according to the sensory data, all the bread samples except those obtained from the Costel variety were of a very good quality, being within a total sensory range of 25.26-29.85 points. According to the relationships between flour, dough and bread characteristics obtained through principal component analysis, it may be concluded that the triticale varieties Costel, Ingen 33, Ingen 93 and Fanica, and Ingen 35 were more closely associated with each other. Significant differences were found between the triticale variety samples Ingen 40, Fanica, and Ingen 35 and between Ingen 54, Ingen 33, Costel, and Ingen 93.

A variety of potato cultivars from the VIR World Collection in northern conditions

Relevance. Potatoes are one of the most popular agricultural crops in Russia. The unique chemical composition characterizes potatoes as a valuable food product in the diet of the population. One of the important factors for increasing and stable potato yields is the selection of the optimal assortment for each region of the Russian Federation. Therefore, the varieties most adapted to local growing conditions should be used in production. The world potato collection allows solving various issues of modern breeding, such as: early maturity, resistance of tubers to various diseases, seed quality, adaptation to climatic stresses, history and systematics. The study and evaluation of new potato breeding varieties makes it possible to identify promising source material for the creation of future varieties suitable for cultivation in the northern regions of the country.The purpose of this study is to characterize the studied potato samples in extreme climate conditions.Material and methodology. In 2013-2023, 543 potato samples from the World Collection of VIR were studied at the experimental field of the Polar Experimental Station VIR branch according to the main biological and economically valuable characteristics. For a comprehensive assessment of the varieties according to the main economic and biological characteristics, phenological observations were carried out, the harvest was taken into account during early and final harvesting, including the structure of the crop. Visual assessment of diseases was carried out in the field and during storage. Starch was determined in the laboratory. All basic accounting is performed according to the VIR methodology.Results and discussion. Over the years, 15 potato varieties with the best characteristics of economically valuable traits have been identified. According to the results of the final harvest, 6 varieties had a stable harvest – Favorit, Meteor, Tekes, Severny, Gusar, Lingonberry. The yield of these varieties was 1034-1409 g/bush.

Genetic assessment of diverse rice germplasm for yield-related and stress tolerance traits

AbstractThe development of stress-resistant crops without compromising their yield and nutritional quality is one of the major challenges in plant biology. Plant breeders have made considerable effort in developing cultivars with high yield and tolerance to biotic and abiotic stresses. This research aimed to evaluate pre-breeding resources for favorable genes conferring good yield and resistance to biotic and abiotic stresses for rice varietal improvement. Two hundred forty diverse rice cultivars from top countries with which the United States imports and exports rice were selected from the Germplasm Resource Information Network (GRIN) collection, and these were characterized using molecular markers for various desirable traits. Among the cultivars, 16 were used as checks. The genes of various traits evaluated were grain number (Gn1a), panicle weight (WFP), cold stress tolerance (qSCT-11 and qCTS-12), anaerobic germination (AG1 and AG2), rice blast disease resistance (PiB, Pi-ta, Ptr, and Piz), wide compatibility (S5-n), and restoring ability (Rf4). Out of these 240 accessions, 192 have the Gn1a gene, 168 possess the qSCT-11 cold tolerance gene, 139 carry the Rf4 gene, 152 have the qCTS12 cold tolerance gene, 87 have blast resistance genes, and 44 possess the WC gene. None of the 240 accessions possess the WFP (Wealthy Farmer’s Panicle) gene. The selections with favorable genes can be used by breeders as potential donor parents for varietal improvement programs to produce new and promising cultivars with desired specific traits that may contribute towards alleviating global issues related to food security.

Estimating wheat spike-leaf composite indicator (SLI) dynamics by coupling spectral indices and machine learning

The contribution of spike photosynthesis to grain yield (GY) has been overlooked in the accurate spectral prediction of yield. Thus, it’s essential to construct and estimate a yield-related phenotypic trait considering spike photosynthesis. Based on field and spectral reflectance data from 19 wheat cultivars under two nitrogen fertilization conditions in two years, our objectives were to (i) construct a yield-related phenotypic trait (spike–leaf composite indicator, SLI) accounting for the contribution of the spike to photosynthesis, (ii) develop a novel spectral index (enhanced triangle vegetation index, ETVI3) sensitive to SLI, and (iii) establish and evaluate SLI estimation models by integrating spectral indices and machine learning algorithms. The results showed that SLI was sensitive to nitrogen fertilizer and wheat cultivar variation as well as a better predictor of yield than the leaf area index. ETVI3 maintained a strong correlation with SLI throughout the growth stage, whereas the correlations of other spectral indices with SLI were poor after spike emergence. Integrating spectral indices and machine learning algorithms improved the estimation accuracy of SLI, with the most accurate estimates of SLI showing coefficient of determination, root mean square error (RMSE), and relative RMSE values of 0.71, 0.047, and 26.93%, respectively. These results provide new insights into the role of fruiting organs for the accurate spectral prediction of GY. This high-throughput SLI estimation approach can be applied for wheat yield prediction at whole growth stages and may be assisted with agronomical practices and variety selection.

Combining spectrum, thermal, and texture features using machine learning algorithms for wheat nitrogen nutrient index estimation and model transferability analysis

The nitrogen nutrition index (NNI) has been extensively applied for the diagnosis of crop nitrogen status, providing insights into efficient nitrogen utilization and plant growth. In this study, we utilized a low-altitude unmanned aerial vehicle (UAV) platform, equipped with multispectral (MS), red–green–blue (RGB), and thermal infrared (TIR) cameras, to comprehensively capture wheat spectral information. The analysis of the relationship between NNI and relative yield revealed an initially linear relationship, which saturated for high NNI values. To enhance accuracy and minimize complexity, we employed a random forest (RF) – recursive feature elimination (RFE) method to select features as inputs for four machine learning (ML) models: back propagation neural network (BPNN), extreme learning machine (ELM), support vector regression (SVR), and Gaussian process regression (GPR). After feature selection, the prediction accuracies of single-sensor models were ranked as: MS > RGB > TIR. The R2 values for the four ML models were in the range of 0.54–0.75. Among multi-sensor combinations, the GPR with MS + RGB + TIR input features achieved the best results with R2 = 0.89 and RPD = 2.52. Further, the dataset was partitioned into six subsets based on location and cultivar variety to evaluate model transferability. The results showed that the transferability largely suffered during the bivariate conditions of different varieties at different locations; the transferability of the model was average improved by 11 % when GPR was combined with transfer component analysis (TCA). The accuracy and transferability of the NNI estimation models significantly improved, offering valuable guidance and methodological support for diagnosing the nitrogen nutrient status of wheat.

Microbiological survey and physicochemical analysis of Moroccan durum, soft and red wheat landraces

Morocco possesses a significant genetic diversity of wheat cultivars in the form of landraces conserved by local farmers in several regions. This study aimed to evaluate the microbiological quality of refined flour and bran derived from 75 samples of Moroccan durum, soft, and red wheat landraces and to estimate their microbiological stability for controlling and preventing undesirable microbial proliferation. Various microbial and physicochemical parameters were evaluated according to ISO and AOAC standards, and results were interpreted based on Codex Alimentarius Commission regulation. Compliance of the analyzed refined flour and bran samples with current regulatory limits and satisfactory microbiological quality were observed. The phenotypic characterization revealed the identification of 16 yeast species belonging to the genera Trichosporon, Candida, Cryptococcus, Rhodotorula, and Saccharomyces, which had not been previously explored. Furthermore, the biodiversity of lactic acid bacteria is notably characterized by the predominance of Pediococcus acidilactici and Lactobacillus plantarum species. The analysis of moisture content and water activity exhibited values falling below the maximum limits defined by international standards, demonstrating the effectiveness of the implemented processing and storage practices. The neutral pH recorded confirms the absence of excessive proliferation of the assessed microbial contaminants. The abundant availability of carbohydrates, lipids, proteins, and minerals creates a favorable non-competitive environment essential for maintaining their functional stability in the analyzed samples. These findings hold significant implications for the agricultural and food industries, providing insights into preserving indigenous wheat varieties and producing safe wheat-based products with high nutritional quality.

The role of small RNAs in resistant melon cultivar against Phelipanche aegyptiaca parasitization.

Bidirectional trans-kingdom RNA silencing, a pivotal factor in plant-pathogen interactions, remains less explored in plant host-parasite dynamics. Here, using small RNA sequencing in melon root systems, we investigated microRNA (miRNA) expression variation in resistant and susceptible cultivars pre-and post-infection by the parasitic plant, broomrape. This approach revealed 979 known miRNAs and 110 novel miRNAs across 110 families. When comparing susceptible (F0) and resistant (R0) melon lines with broomrape infection (F25 and R25), 39 significantly differentially expressed miRNAs were observed in F25 vs. F0, 35 in R25 vs. R0, and 5 in R25 vs. F25. Notably, two miRNAs consistently exhibited differential expression across all comparisons, targeting genes linked to plant disease resistance. This suggests their pivotal role in melon's defense against broomrape. The target genes of these miRNAs were confirmed via degradome sequencing and validated by qRT-PCR, ensuring reliable sequencing outcomes. GO and KEGG analyses shed light on the molecular functions and pathways of these differential miRNAs. Furthermore, our study unveiled four trans-kingdom miRNAs, forming a foundation for exploring melon's resistance to broomrape.

Effects of harvest height and time on hay yield and quality of some sweet sorghum and sorghum Sudangrass hybrid varieties.

This experiment was conducted in the Research and Application Field of Canakkale Onsekiz Mart University, Faculty of Agriculture, during the 2020 and 2021 summer period. The objective of this experiment was to determine the effects of different harvesting heights on forage yields and crude ash, fat, protein, and carbon and nitrogen content of leaves and stalks of sweet sorghum (SS) and sorghum sudangrass hybrid (SSH) cultivars. Nutri Honey and Nutrima varieties of SSH and the M81-E and Topper-76 varieties of SS were used in this study. The experiment was conducted using the randomized complete block design with four replications. The main plots each included two early and late varieties of SS and SSH cultivars, while the subplots were used to test different harvesting heights (30, 60, 90, 120, 150 cm) and physiological parameters of each crop. The results of this study showed that dry forage yields increased with plant growth, with the amount of forage produced at the end of the growth cycle increasing 172.2% compared to the early growth stages. Carbon (C) content of leaves decreased by 6.5%, nitrogen (N) by 46%, crude protein (CP) by 54%, crude fat (CF) by 34%, while crude ash (CA) content increased by 6% due to the increase in plant height harvest. At the same time, in parallel with the increase in plant height at harvest, the nitrogen content of the stems of the plants decreased by 87%, crude protein by 65%, crude ash by 33% and crude fat by 41%, while the carbon content increased by 4%. As plant height at harvest increased, hay yield increased but nutrient contents of the hay decreased. However, the Nutrima, Nutri Honey and M81-E sorghum cultivars, harvested three times at heights of 90 to 120 cm, are recommended for the highest yield.