Kernel Weight Research Articles

Inheritance patterns of pomological traits in walnut hybridization breeding: influence of parental varieties on nut traits

BackgroundWalnut (Juglans regia L.) breeding programs aim to develop new genotypes that exhibit superior agronomic traits, including high yield, improved nut quality, and favorable phenological traits. One of the primary methods used in these programs is hybridization, which involves controlled crosses between selected parent varieties. In reciprocal cross, understanding the genetic contributions of both maternal and paternal parents is crucial, as these contributions significantly influence the phenotypic traits of the resulting progeny. This knowledge allows breeders to predict and select genotypes that best meet the desired breeding objectives, ultimately enhancing agricultural productivity and sustainability.ResultsThis study analyzed the pomological traits of F1 plants derived from four different hybrid combinations: Pedro × Maraş 18, Pedro × Sütyemez 1, Maraş 18 × Pedro, and Sütyemez 1 × Pedro. The assessment focused on key nut traits, including nut length, nut diameter, nut weight, kernel weight, and kernel percentage. Statistical analyses revealed significant variations in these traits among the hybrid combinations, with these differences determined at the p < 0.05 significance level. Kernel weight exhibited the highest coefficient of variation (CV = 33.63%), indicating substantial variability in this trait among the hybrids. Nut diameter had the lowest variability (CV = 12.82%), suggesting greater consistency across the hybrid combinations. Other traits, such as nut weight, nut length, and kernel percentage, showed intermediate levels of variability, with CVs of 27.33%, 13.45%, and 18.59%, respectively. The study found that maternal parents played a more partially dominant role in determining nut traits in most hybrid combinations. However, when Sütyemez 1 and Maraş 18 were used as maternal parents, their influence on the inheritance of some nut traits was relatively greater than the other parent variety (Pedro).ConclusionThe findings emphasize the crucial role of parent selection in walnut hybridization breeding programs, with parental effects being relatively prominent in influencing pomological traits, underscoring the need for careful selection of maternal parents to achieve the desired outcomes. Among the varieties studied, Pedro, Maraş 18, and Sütyemez 1 were identified as promising parent genotypes for improving key nut traits. The variability observed in traits such as kernel and nut weights suggests potential for further selection and genetic improvement. This variation highlights the genetic diversity present in the studied hybrids, which can be effectively utilized in breeding efforts. These results not only contribute to the improvement of walnut varieties but also have broader implications for global walnut production, providing valuable guidance for breeding programs aiming to improve nut quality in walnut hybridization programs.

Efficacy of ascorbic acid coated quantum dots in alleviating lead-induced oxidative damage and enhancing growth parameters in rice (Oryza sativa L.) for sustainable cultivation.

Lead (Pb) toxicity impairs the growth, yield, and biochemical traits of rice, making it essential to mitigate Pb stress in soil and restore its growth and production. This study investigated the potential of ascorbic acid-coated quantum dots (AsA-QDs) in alleviating Pb stress in two rice cultivars, Japonica (JP-5) and Indica (Super Basmati), grown in pots under Pb stress (50 mg/kg as lead chloride) with AsA-QD suspensions (50 ppm and 100 ppm) as treatments. The synthesized AsA-QDs were characterized by zeta potential (-14.4 mV), particle size (472.3 nm, PDI 0.745), UV-Vis absorption peak (240 nm), FT-IR analysis revealing functional groups (carboxylic acid and alkene), and TEM showing spherical morphology (average size 9.43 nm). Pb stress reduced key traits in JP-5, including tillers per plant (11.11 %), grain yield (18.22 %), kernel weight (18.22 %), protein (40.19 %), phenolic content (59.66 %), and antioxidant capacity (17.75 %), while 50 ppm AsA-QDs improved these by 33.33 %, 5.73 %, 2.03 %, and 13.19 %, respectively. Similarly, Pb stress reduced plant height, T/P, biomass yield (BY), GY, TKW, total sugars, reducing sugars, non-reducing sugars, starch, proteins, and TPC in Super Basmati by 19.76 %, 21.43 %, 11.01 %, 11.01 %, 7.52 %, 38.09 %, 7.24 %, 13.96 %, 11.97 %, and 40.39 %, respectively, while PbQD1 improved these traits by 14.29 %, 15.49 %, 9.25 %, 109.52 %, 8.31 %, 31.72 %, 25.91 %, and 7.075 %, respectively. The findings demonstrate that AsA-QDs effectively mitigate Pb toxicity by reducing oxidative stress, enhancing growth parameters, and restoring yield components, establishing them as a promising nanomaterial for sustainable crop resilience under Pb stress.

Mapping Variability of Mycotoxins in Individual Oat Kernels from Batch Samples: Implications for Sampling and Food Safety.

Oats are susceptible to contamination by Fusarium mycotoxins, including deoxynivalenol (DON), zearalenone (ZEN), and T-2/HT-2 toxins, posing food safety risks. This study analyses the variation in levels of 14 mycotoxins in 200 individual oat kernels from two DON-contaminated batch samples (mean = 3498 µg/kg) using LC-MS/MS. The samples also contained deoxynivalenol-3-glucoside (DON-3G), 3-acetyldeoxynivalenol (3-ADON), 15-acetyldeoxynivalenol (15-ADON), and ZEN. Contamination levels varied notably among individual kernels, with DON detected in 70% of them, followed by DON-3G (24.5%) and 3-ADON (20.5%). Importantly, 8% of kernels exceeded the EU legal limit for DON (1750 µg/kg), and some occasionally surpassed limits for ZEN and T-2/HT-2. Correlation analyses revealed strong associations between DON and its derivatives but weaker correlations with other toxins. Mycotoxin ratios varied widely, indicating that although they often co-occur, their concentrations differ between kernels. Contamination did not significantly impact kernel weight, though a slight trend toward lower weights in contaminated kernels was noted. Additionally, sampling statistics showed that as the percentage of selected kernels increased, the probability of batch sample rejection for DON contamination rose significantly. The study highlights the heterogeneity of mycotoxin contamination in oat batches, emphasising the importance of accurate detection and regulatory compliance to ensure safer oat-based products.

Harnessing Genetic Resistance in Maize and Integrated Rust Management Strategies to Combat Southern Corn Rust.

Southern corn rust (SCR) caused by Puccinia polysora Underw. has recently emerged as a focal point of study because of its extensive distribution, significant damage, and high prevalence in maize growing areas such as the United States, Canada, and China. P. polysora is an obligate biotrophic fungal pathogen that cannot be cultured in vitro or genetically modified, thus complicating the study of the molecular bases of its pathogenicity. High temperatures and humid environmental conditions favor SCR development. In severe cases, SCR may inhibit photosynthesis and cause early desiccation of maize, a decrease in kernel weight, and yield loss. Consequently, an expedited and accurate detection approach for SCR is essential for plant protection and disease management. Significant progress has been made in elucidating the pathogenic mechanisms of P. polysora, identifying resistance genes and developing SCR-resistant cultivars. A detailed understanding of the molecular interactions between maize and P. polysora will facilitate the development of novel and effective approaches for controlling SCR. This review gives a concise overview of the biological characteristics and symptoms of SCR, its life cycle, the molecular basis of interactions between maize and P. polysora, the genetic resistance of maize to SCR, the network of maize resistance to P. polysora infection, SCR management, and future perspectives.

Discrete Wavelet Transform Sampling for Image Super Resolution

ABSTRACT In battlefield environments, drones depend on high-resolution imagery for critical tasks such as target identification and situational awareness. However, acquiring clear images of distant targets presents a significant challenge. To address this, we propose a supervised learning approach for image super-resolution. Our network architecture builds upon the U-Net framework, incorporating enhancements to the encoder and decoder through techniques such as Discrete Wavelet Transform, Channel Attention Residual Modules, Selective Kernel Feature Fusion, Weight Normalization, and Dropout. We evaluate our model on a super-resolution dataset and compare its performance against other networks, highlighting the importance of minimizing trainable parameters for real-time deployment on resource-constrained drone platforms. The effWicacy of our proposed network is further validated through image recognition tasks and real-world scenario testing. By enhancing image clarity at extended ranges, our approach enables drones to detect adversaries earlier, facilitating proactive countermeasures and improving mission success rates

Genetic parameter analysis and evaluation of maize hybrids under local climatic condition of Mymensingh, Bangladesh.

Maize is a cornerstone of global agriculture, essential for food security, livestock feed, and industrial uses. With the increasing demand for maize due to population growth and changing dietary patterns, there is a pressing need to enhance maize production. Hybridization is a strategic approach for developing high-yielding and stress-tolerant maize varieties and evaluating these hybrids in specific environmental conditions is vital for optimizing yield and adaptability. With this objective, a field experiment was conducted to evaluate the growth and yield performance of ten hybrid maize varieties under the local climatic conditions of Mymensingh. A randomized complete block design with three replicates was used to collect data on thirteen different parameters. Significant variation was observed among the hybrids for all phenological, growth, and yield contributing traits. The phenotypic coefficient of variation exceeds the genotypic coefficient of variation, indicating substantial environmental interactions. Heritability estimates ranged from 59% to 98%. Positive correlations were noted between cob length, cob diameter, grains per row, and 100-seed weight with kernel weight per plant. Path coefficient analysis revealed that plant height, cob diameter, number of leaves at harvest, cob length, and grains per row positively influenced grain yield. Among the hybrids, Kaveri54 exhibited superior performance with a kernel weight of 202.7g. Therefore, Kaveri54 is recommended as a promising hybrid for maize cultivation in the Mymensingh region, which will support future breeding efforts aimed at improving yield and resilience.

Identification of the arl1 locus controlling leaf rolling and its application in maize breeding

Increasing planting density is one of the most important strategies for generating higher maize yields. Moderate leaf rolling decreases mutual shading of leaves and increases the photosynthesis of the population and hence increases the tolerance for high-density planting. Few genes that control leaf rolling in maize have been identified, however, and their applicability for breeding programs remains unclear. Here we identified a maize abaxially rolled leaf1 (arl1) mutant with extreme abaxially rolled leaves and found that the size of the bulliform cells within the adaxial leaf blade surface increased in the arl1 mutant. Bulk segregation analysis mapping in an F2 population derived from a single cross between arl1 and inbred line Gui18421 with normal leaves identified the arl1 locus on chromosome 2. Sequential fine-mapping delimited the arl1 locus to a 233.56-kb genomic interval containing three candidate genes. Sequence alignment between arl1 and Gui18421 identified an 8-bp insertion in the coding region of Zm00001eb082500, which led to a frame shift causing premature transcription termination in arl1 mutant. Meanwhile, both deep sequencing and Sanger sequencing showed that Zm00001eb082520 was present in Gui18421 but was absent in arl1. A pair of near isogenic lines (NILs) carrying the Gui18421 allele (NILGui18421) and the arl1 allele (NILarl1) were developed, and the leaves of NILarl1 plants had greater light transmission and photosynthetic rate in the middle and lower canopy than did those of NILGui18421 plants under high-density planting. Furthermore, NILarl1 had a higher seed setting rate, more kernels per ear, and an increased kernel weight per ear than NILGui18421, and the grain yield of NILarl1 was not affected as the planting density increased, suggesting that the arl1 locus can be used for genetic improvement of high-density planting tolerance. Taken together, the identification of arl1 and evaluation of yield-related traits for NILGui18421 and NILarl1 provide an excellent target for future maize improvement.

Evaluation of grain yield, and quality characteristics of some bread wheat cultivars in different agro-ecological regions of Türkiye.

Climate change and recurrent droughts challenge wheat production and yield, necessitating careful selection and plant breeding research. "Value for Cultivation and Use" experiments are crucial for assessing genetic gains and providing information about potential pathways to alleviate production losses under specific environmental conditions. The goal of the study was to compare the grain yield and quality characteristics of 46 registered bread wheat cultivars in 5 out of 7 agro-ecological regions of Türkiye between 2016-2017 and 2017-2018. The registered wheat cultivars were also characterized in terms of high molecular weight glutenin subunits (HMW-GS) and the relationships between quality traits and band patterns. Genotype×environment interaction was found statistically significant (p<0.05) for grain yield and the stability of the cultivars as explained on biplot graphs. The Mediterranean and the Central Anatolian region had the highest and the lowest average grain yield of 8137kgha-1 and 4260kgha-1 respectively under the rainfed conditions. The average thousand kernel weight of the cultivars was 35.3-39.9g, with test weight of 77.2-79.2kghL-1, protein content of 13.4-14.7%, Zeleny sedimentation of 39.2-53.3mL, and alveograph energy value varied between 191.2-276.4×10-4J. The most common subunits in cultivars were 2∗ at Glu-A1, 7+8 and 7+9at Glu-B1, and 5+10at Glu-D1. It is concluded that high-quality new varieties are developed by high-molecular-weight glutenin subunits oriented crosses and selections in Turkish wheat breeding programs.

Correlation and Path Coefficient Studies of Yield and Its Contributing Traits in Groundnut (Arachis hypogea L.)

Groundnut is currently a major industrial oilseed crop with good commercial significance. It is highly variable in phenotypic characters and thus it is important to investigate the variations and associations of these morphological features. Ten confectionary type advanced breeding lines along with two checks (Kadiri chitravathi and Kadir-7) were raised in a randomized block design with three replications and they were evaluated for 15 characters. Significant variations were observed among the genotypes for all the characters studied. The highest genotypic coefficient of variation was observed for hundred pod weight and hundred pod kernel weight indicating the presence of wide range of variation for this character. The dry pod yield per plant had significant positive association with hundred pod kernel weight, kernel yield per plot and positive association with plant height, no. of pods per plant and hundred pod weight. Path coefficient analysis revealed that, hundred pod weight reported the highest positive direct effect on pod yield per plot followed by hundred pod kernel weight, kernel yield per plot, days to maturity, days to 50 % flowering, plant height, final plant count and initial plant count indicating that the selection for these characters was likely to bring about an overall improvement in pod yield per plot directly.

Evaluation of variability and principal component analysis in segregating populations of groundnut (Arachis hypogaea L.)

Groundnut is a favourable and profitable crop for resource-poor farmers in Africa and Asia, both for edible oil production and direct consumption. There is significant potential to breed high-yielding, better-quality groundnut cultivars by generating new variations through artificial techniques. In this study, the F2 generations of the crosses CO 7 × Chico and ICGV 07222 × Chico was analysed to assess the variability created through artificial hybridization in groundnut. The various yield and yield-related traits were analysed to estimate genetic parameters, skewness, kurtosis and subjected to principal component analysis (PCA). The variability study of the F2 population from both crosses revealed significant variations for the traits under study. The traits “days to accumulation of 25 flowers” and “shelling %” showed low GCV (genotypic coefficient of variation) and PCV (phenotypic coefficient of variation) in both populations. Most traits exhibited moderate to high heritability and genetic advance, whereas “days to accumulation of 25 flowers” and “maturity duration” had moderate heritability and low genetic advance. Only shelling % had low estimates of heritability and genetic advances. Tests for skewness and kurtosis revealed that both F2 population did not follow a normal distribution. The traits “days to maturity”, “shelling %”, “kernel yield,” and “hundred kernel weight” displayed significant positive skewness. The traits “days to accumulation of 25 flowers”, “number of matured pods”, “height of main axis”, “shelling %”, “hundred pods” and “hundred kernel weight” and “pod yield” showed platy- kurtosis, while “Kernel yield” displayed lepto-kurtosis in both populations. The first principal component explained 37 % and 32 % of the total variance in the 2 F2 populations respectively, with a focus on yield-related traits. The PCA biplot effectively clustered the genotypes based on the 10 different traits studied and clearly, grouped the population based on maturity duration. Thus, hybridization created significant variation in groundnut for all yield-related traits and yield, except for “days to maturity”. The traits require further enhancement using additional sources and could be improved through intense selection.

Resistant wheat cultivars and fungicide applied at stem elongation or mid-anthesis are effective stripe rust control strategies in Saskatchewan

Stripe rust, caused by Puccinia striiformis f. sp. tritici, has been observed frequently on wheat since 2010 in Saskatchewan. The deployment of resistant cultivars and the use of fungicides are common control measures for this disease. The effectiveness of fungicide application at various timings on wheat cultivars varying in resistance to the disease at two seeding dates was determined in central Saskatchewan from 2012 to 2016. Under high disease pressure, a single fungicide application at mid-anthesis growth stage of wheat seeded mid-May decreased disease severity of the susceptible cultivar ‘AC Barrie’ from 87% (unsprayed control) to 26% and protected yield by 59%. The response was somewhat less dramatic for the moderately resistant cultivar ‘CDC Imagine’; stripe rust severity was reduced from 54% to 14%, and yield protected by 32%. Similar effects of fungicide application were observed for thousand kernel weight, test weight and protein content. Furthermore, at a later seeding date (early June), fungicide application at stem elongation reduced stripe rust severity on the susceptible cultivar ‘AC Barrie’ from 87% to 51% and protected yield by 53%. Fungicide applied at the mid-anthesis stage had the same positive effect, reducing symptoms from 87% to 54% and increasing yield by 46%. Fungicide application had no detectable effect on stripe rust severity of the resistant cultivar ‘Lillian’ at any growth stage of either seeding date experiment. The study demonstrated that, under the conditions that prevail in Saskatchewan, a single fungicide application at stem elongation or mid-anthesis, depending on seeding date, can reduce disease severity, protect yield and improve grain quality in wheat cultivars susceptible and moderately resistant to stripe rust.

INFLUENCE OF TILLAGE SYSTEMS ON SELECTED SOIL CHARACTERISTICS AND YIELD OF SPRING CEREALS

Climate change necessitates a revised approach to crop cultivation technologies, prioritizing enhanced agricultural practices for soil conservation, water retention, and high-quality yields. To evaluate the influence of different soil tillage systems on yield and yield quality in spring cereals, a field experiment was conducted at the Agricultural Research and Development Station (ARDS) Turda. The experiment followed a split-plot design with two replications, within a 3-year rotation (soybean–spring cereals–maize). Three spring cereal species (wheat, two oat varieties, and barley) were tested under four tillage systems (plowing, chiseling, disking, and direct sowing) on Phaeozem soil with a clay-clay texture. The hectoliter weight (TW), thousand kernel weight (TKW), and grain protein content are influenced to some degree by the tillage system. The highest soil compaction levels were observed in the NT system, while the lowest were recorded in the CS system. High temperatures and drought led to notable soil moisture decreases in June and July, especially in the minimum tillage with disking (MTD) and NT systems. Tillage with plow and chisel resulted in lower bulk density values. Yields in the unconventional systems (minimum tillage with chisel (MTC) and MTD) were comparable to those in the conventional system (CS), indicating their viability as alternatives to traditional plowing. A yield reduction was noted in the no-tillage system.

Trait Correlations and Path Analysis for Kernel Yield Improvement in Groundnut (&amp;lt;i&amp;gt;Arachis hypogaea&amp;lt;/i&amp;gt; L.) Genotypes

Groundnut (&amp;lt;i&amp;gt;Arachis hypogaea L&amp;lt;/i&amp;gt;.), or peanut, is a self-pollinating legume valued for its oil-rich kernels and nitrogen-fixing roots. Given the limited availability of enriched germplasm in Ethiopia, indirect selection through association studies is pivotal for identifying traits linked to high kernel yield. This study evaluated fifteen groundnut genotypes using a Randomized Complete Block Design with three replications to analyze correlations and path coefficients for yield improvement. Significant differences among genotypes were observed for key traits, including days to flowering and maturity, number of mature pods per plant, 100-kernel weight, and kernel yield, indicating the presence of variability among the genotypes in terms of these traits. Correlation analysis revealed a significant negative phenotypic correlation between kernel yield and days to maturity, but positive correlations with number of mature pods per plant and number of kernels per pod. The result revealed that late maturing genotypes produce high number of pods in turn exhibit higher kernel yield than early maturing ones. Genotypic correlations reinforced these findings, highlighting number of mature pods per plant as a critical determinant of yield. Path coefficient analysis indicated that the number of mature pods per plant had the highest direct positive effect on kernel yield, suggesting that enhancing this trait could significantly boost productivity. These results underscore the importance of selecting for high number of mature pods per plant in groundnut breeding programs to enhance kernel yield.

Changes in Quality Components of Durum Wheat Genotypes under Temperature Stress and Sufficient Rainfall Conditions during the Growth Period

A combination of genetic makeup and environmental factors determine the quality characteristics of durum wheat. Specifically, environmental stressors, such as extreme temperature fluctuations, can have a substantial impact on the productivity and quality of wheat crops. The effect of terminal temperature stress on yield and quality in durum wheat genotypes grown during 2019 and 2020 seasons was studied. These characteristics include thousand kernel weight, protein content, hectoliter weight, wet gluten content, Zeleny sedimentation value, and grain colour. The first year of the study was warmer than the second, resulting in decreased kernel weight, hectoliter weight, and gluten values, as well as increased protein content and Zeleny sedimentation values. This indicates that temperature stress leads to a higher protein content. The study also showed considerable variation in quality traits among genotypes, with certain genotypes demonstrating greater stability in specific quality traits. Genotype by environment interaction significantly affected grain weight, protein content, gluten content and Zeleny sedimentation. These data indicate that temperature stress plays an important role in determining the quality characteristics of durum wheat. Future studies should focus on mitigating the adverse effects of terminal temperature stress and improving the generation of genotypes with optimal quality traits.

Relationships between the number of nuts per cluster and fruit characteristics in the Foşa hazelnut cultivar

This research aimed to determine the effect of the number of nuts per cluster on the fruit characteristics of the Foşa hazelnut cultivar grown in the Arsin district of Trabzon province, Türkiye. Hazelnuts are divided into groups of 1 to 7 according to the number of nuts in cluster. Nut weight, nut length, nut width, nut depth, kernel weight, kernel length, kernel width, kernel depth, shell thickness, kernel ratio, husk length, husk width, and husk opening of the hazelnuts in each group were examined. Principal component analyses (PCA) was used to determine the relationship between the number of nuts in cluster and fruit characteristics. Nut weight, shell thickness, husk length, and husk width values were the highest values in single nut clusters. If the number of nuts in the cluster exceeds four, nut and kernel weights decrease. There was a negative relationship between the nut weight and nut length when the number of nuts in the cluster was above four. A strong relationship were observed in clusters 1, 2, 3, and 4, but a weaker relationship, was seen especially in clusters 5 and 7. A negative relationship was determined between the nut weight and nut length. This study clarified that increasing nut numbers shifts quality characteristics, particularly in a negative trend.

Mean Normalization Improved Genome-Wide Association Detection Power of Wheat (Triticum aestivum) Grain and Flour Quality Traits with Year-to-Year Variation

Grain and flour quality traits affect marketing potential and milling and baking properties. Trait means varied in fourteen wheat grain and flour quality traits for a population of 188 diverse soft winter wheat varieties harvested from 2020 to 2023 at the same location. Significant weather differences occurred yearly. This created a challenge for the detection of chromosome locations affecting these traits through genome-wide association studies (GWAS). Mean normalization using standard deviation to transform raw data to Z scores has been used successfully in other statistical analyses of biological systems with mean differences. Mean normalization was applied to a GWAS, improving detection power for thirteen grain and flour quality traits with high broad-sense heritability. It did not improve the lone trait with low heritability. Improvement was measured as the reduction in the p-value of mean normalized data compared with raw data for the same significant marker using the same GWAS model in the same trait. Improvement varied by trait and marker, but the average p-value of 135 common significant marker/GWAS model combinations was reduced 27 times with mean normalization over raw averaged data. Mean normalization reduced p-values ~1800 times when compared with a GWAS using best linear unbiased predictors. However, the best linear unbiased predictors led to only 15 common marker/GWAS model combinations with mean normalization, limiting the ability for direct marker comparison. Test weight, kernel protein, kernel weight, sodium carbonate solvent retention capacity, and sucrose solvent retention capacity showed the greatest increased detection power.

Registration of New Bread Wheat Variety (Gutu) for Mid to Highland Altitude Wheat Producing Areas of Ethiopia

Wheat, a staple crop in Ethiopia, is constrained by biotic and abiotic stresses. Despite efforts to develop high-yielding, disease-resistant varieties, most have short agronomic life spans due to mainly yellow rust and stem rust diseases. Therefore, continuous breeding and selection are needed to identify new varieties with high yield potential, resistance to major wheat diseases, and adaptability to different climatic conditions. Thirty advanced bread wheat lines together with standard and local checks were evaluated using row-to-column design in three replications at six and nine locations during the 2021 and 2022 main seasons, respectively. Data such as days to maturity, plant height, yield, TKW, and test weight were taken. The yield data were exposed to statistical analysis. The new variety, EBW192345 (Kenya sunbird/2*Kachu/3/SWSR22T.B/2* Blouk#1//Wbll1*2/Kuruku) outyielded the standard check (Boru) and local check (Dandaá) by 25.43% and 51.9%, respectively. The new variety not only outyielded the checks, but it exhibited better resistance to yellow and stem rust diseases and had better performances in 1000 Kernel weight and test weight compared to the other treatments including the checks. Based on two years of multi-location data and performances on research plots and farmers’ fields, EBW192345 was released by the national variety release committee for commercial production in mid to highlands in Ethiopia during 2023.

Maize Kernel Broken Rate Prediction Using Machine Vision and Machine Learning Algorithms.

Rapid online detection of broken rate can effectively guide maize harvest with minimal damage to prevent kernel fungal damage. The broken rate prediction model based on machine vision and machine learning algorithms is proposed in this manuscript. A new dataset of high moisture content maize kernel phenotypic features was constructed by extracting seven features (geometric and shape features). Then, the regression model of the kernel (broken and unbroken) weight prediction and the classification model of kernel defect detection were established using the mainstream machine learning algorithm. In this way, the defect rapid identification and accurate weight prediction of broken kernels achieve the purpose of broken rate quantitative detection. The results prove that LGBM (light gradient boosting machine) and RF (random forest) algorithms were suitable for constructing weight prediction models of broken and unbroken kernels, respectively. The r values of the models built by the two algorithms were 0.985 and 0.910, respectively. SVM (support vector machine) algorithms perform well in constructing maize kernel classification models, with more than 95% classification accuracy. A strong linear relationship was observed between the predicted and actual broken rates. Therefore, this method could help to be an accurate, objective, efficient broken rate online detection method for maize harvest.

Genetic relationships among some old walnuts (Juglans regia L.) genotypes in Iran and selection of superior genotypes

Abstract Walnut (Juglans regia L.) is one of the oldest and most economically important edible nut species due to its high nutritional value. Iran is known as one of the most important centres of the origin and diversity of walnuts worldwide. This research was carried out to determine the genetic relationships of some old walnut genotypes in Iran in order to select superior genotypes and better conserve them. The results of morphological evaluation of the fruits showed that the highest coefficients of variation were related to nut weight, kernel weight, percentage kernel, thickness and weight of the shell, and thickness and weight of the packing tissue in both years. The average morphological traits among the studied genotypes were different, such that the highest nut weights in the first and second years were 15.59 and 14.79 g and the corresponding lowest values were 7.37 and 7.79 g, respectively. The highest and lowest kernel weights were observed in the first years to be 8.09 and 3.80 g and in the second years were 6.94 and 2.65 g, respectively. The highest kernel percentages in the first and second years were 64.97 and 59.79% and the lowest percentages were 39.52 and 27.80% in the first and second years, respectively. Molecular evaluation results showed that the 16 start codon of target (SCoT) primers amplified a total of 166 bands with an average of 10.44 bands per primer. The number of polymorphic bands was changed from 2 to 19 in primers SCoT-19 and SCoT-15. The average polymorphism information content value was 0.30 and the highest amount of this index (0.36) was observed in SCoT-14 and SCoT-19 primers. The results of principal component analysis and analysis of molecular variance indicated the presence of relatively high diversity within the investigated genotypes. The amount of genetic diversity within the investigated regions was 84% and that between areas was 16%. Based on the obtained results, it was concluded that SCoT markers could provide helpful information on the genetic relationships among walnut genotypes, which can be used in future walnut breeding and conservation programmes.

Screening of Bread Wheat (&amp;lt;i&amp;gt;Triticum aestivum &amp;lt;/i&amp;gt;L.) Genotypes for Septoria Tritici Blotch in Central Highland of Ethiopia

Septoria tritici blotch is a major disease that limits wheat yields globally. This study aimed to identify Septoria-resistant bread wheat genotypes for use in future breeding and variety development programs. A total of 49 genotypes were evaluated in the first year and 60 in the second year, selected from an international nursery and evaluated during the 2016–2018 cropping seasons. The experiments were conducted in both research and farmers&amp;apos; fields during the 2018/19 and 2019/20 cropping seasons. The trial used an alpha lattice design with three replications. Data on yield and related traits were analyzed using SAS version 9.3 software. The results indicated significant (P &amp;lt; 0.01) variation among the genotypes for all phenotypic traits measured at Holetta over the two years. Similarly, significant differences (P &amp;lt; 0.01) were observed at Weliso for all traits except for Septoria disease severity, thousand kernel weight, and grain yield. Across the two locations, the highest grain yield recorded was 5.4 t/ha, while the lowest was 1.8t/ha. Therefore, the study findings indicated that some genotypes showed the best performance and a good opportunity to incorporate a variety of development of wheat breeding programs.