Panicle Grain Research Articles

Principal Component Analysis in rice (Oryza sativa L.) varieties for three seasons in Annamalai Nagar, an east coast region of Tamil Nadu

Principal component analysis (PCA) was used to assess genetic variability and identify key yield-contributing traits among 50 rice genotypes evaluated over three seasons under saline conditions. The study aimed to select promising donor lines for developing salt-tolerant, high-yielding cultivars suitable for coastal regions. PCA identified three principal components (PCs) that explained 73.19%, 70.34%, and 64.81% of the total genetic variation in seasons 1, 2 and 3, respectively. Key plant attributes, such as grain yield per plant, panicle grain density, total tiller number, and productive tiller count, showed significant positive associations with PC1 across various growth stages, underscoring their crucial role in explaining the genetic diversity among the genotypes. Plant height, panicle length, and hundred-grain weight also emerged as major contributors to variation. The PCA biplots consistently demonstrated positive correlations between grain yield and traits like panicle length, hundred-grain weight, and tillering ability. In contrast, days to 50% flowering exhibited a negative association with yield. Genotypes G10, G49, G36, G41, G9, G4, G22, and G21 displayed favourable combinations of grain yield per plant, identifying them as potential donor lines for breeding programs aimed at improving rice yield and associated agronomic traits. This comprehensive PCA analysis highlights the effectiveness of the approach in capturing genotypic diversity and guiding the selection of promising germplasm for targeted trait improvement in rice.

Cytokinin oxidase2-deficient mutants improve panicle and grain architecture through cytokinin accumulation and enhance drought tolerance in indica rice.

The Osckx2 mutant accumulates cytokinin thereby enhancing panicle branching, grain yield, and drought tolerance, marked by improved survival rate, membrane integrity, and photosynthetic function. Cytokinins (CKs) are multifaceted hormones that regulate growth, development, and stress responses in plants. Cytokinins have been implicated in improved panicle architecture and grain yield; however, they are inactivated by the enzyme cytokinin oxidase (CKX). In this study, we developed a cytokinin oxidase 2 (Osckx2)-deficient mutant using CRISPR/Cas9 gene editing in indica rice and assessed its function under water-deficit and salinity conditions. Loss of OsCKX2 function increased grain number, secondary panicle branching, and overall grain yield through improved cytokinin content in the panicle tissue. Under drought conditions, the Osckx2 mutant conserved more water and demonstrated improved water-saving traits. Through reduced transpiration, Osckx2 mutants showed an improved survival response than the wild type to unset dehydration stress. Further, Osckx2 maintained chloroplast and membrane integrity and showed significantly improved photosynthetic function under drought conditions through enhanced antioxidant protection systems. The OsCKX2 function negatively affects panicle grain number and drought tolerance, with no discernible impact in response to salinity. The finding suggests the utility of the beneficial Osckx2 allele in breeding to develop climate-resilient, high-yielding cultivars for future food security.

Utilizing machine learning and bioinformatics analysis to identify drought-responsive genes affecting yield in foxtail millet

Drought stress is a major constraint on crop development, potentially causing huge yield losses and threatening global food security. Improving Crop's stress tolerance is usually associated with a yield penalty. One way to balance yield and stress tolerance is modification specific gene by emerging precision genome editing technology. However, our knowledge of yield-related drought-tolerant genes is still limited. Foxtail millet (Setaria italica) has a remarkable tolerance to drought and is considered to be a model C4 crop that is easy to engineer. Here, we have identified 46 drought-responsive candidate genes by performing a machine learning-based transcriptome study on two drought-tolerant and two drought-sensitive foxtail millet cultivars. A total of 12 important drought-responsive genes were screened out by principal component analysis and confirmed experimentally by qPCR. Significantly, by investigating the haplotype of these genes based on 1844 germplasm resources, we found two genes (Seita.5G251300 and Seita.8G036300) exhibiting drought-tolerant haplotypes that possess an apparent advantage in 1000 grain weight and main panicle grain weight without penalty in grain weight per plant. These results demonstrate the potential of Seita.5G251300 and Seita.8G036300 for breeding drought-tolerant high-yielding foxtail millet. It provides important insights for the breeding of drought-tolerant high-yielding crop cultivars through genetic manipulation technology.

A High-Throughput Method for Accurate Extraction of Intact Rice Panicle Traits.

Rice panicle traits serve as critical indicators of both yield potential and germplasm resource quality. However, traditional manual measurements of these traits, which typically involve threshing, are not only laborious and time-consuming but also prone to introducing measurement errors. This study introduces a high-throughput and nondestructive method, termed extraction of panicle traits (EOPT), along with the software Panicle Analyzer, which is designed to assess unshaped intact rice panicle traits, including the panicle grain number, grain length, grain width, and panicle length. To address the challenge of grain occlusion within an intact panicle, we define a panicle morphology index to quantify the occlusion levels among the rice grains within the panicle. By calibrating the grain number obtained directly from rice panicle images based on the panicle morphology index, we substantially improve the grain number detection accuracy. For measuring grain length and width, the EOPT selects rice grains using an intersection over union threshold of 0.8 and a confidence threshold of 0.7 during the grain detection process. The mean values of these grains were calculated to represent all the panicle grain lengths and widths. In addition, EOPT extracted the main path of the skeleton of the rice panicle using the Astar algorithm to determine panicle lengths. Validation on a dataset of 1,554 panicle images demonstrated the effectiveness of the proposed method, achieving 93.57% accuracy in panicle grain counting with a mean absolute percentage error of 6.62%. High accuracy rates were also recorded for grain length (96.83%) and panicle length (97.13%). Moreover, the utility of EOPT was confirmed across different years and scenes, both indoors and outdoors. A genome-wide association study was conducted, leveraging the phenotypic traits obtained via EOPT and genotypic data. This study identified single-nucleotide polymorphisms associated with grain length, width, number per panicle, and panicle length, further emphasizing the utility and potential of this method in advancing rice breeding.

Multivariate assumptions and effect of model parameters in path analysis in oat crop

Context Path analysis (PA) is a widely used multivariate statistical technique. When performing PA, the effects of the parameters of the mathematical model relating to the experimental design are disregarded, working only with the average effects of the treatments. Aims We aimed to analyse the implications of statistical assumptions, and of removing mathematical model parameters, on the PA results in oat. Methods A field study was conducted in southern Brazil in five crop years. The experimental design employed was a two-factor 22 × 5 randomised complete block design, characterised by 22 cultivars and five fungicide applications, with three repetitions. Six explanatory variables were measured, panicle length, panicle dry mass, panicle spikelet number, panicle grain number, panicle grain dry mass, and harvest index, and the primary variable yield. Initially, normality and multicollinearity diagnoses were carried out and correlation coefficients were calculated. The PA was performed in three ways: traditional, with measures to address multicollinearity (ridge), and traditional with eliminating variables. Key results and conclusions The occurrence of multicollinearity resulted in obtaining path coefficients without biological application. Removing the model’s parameters modifies the path coefficients, with average changes of 10.5% and 13.3% in the direction, and 24.7% and 23.0% in the magnitude, of the direct and indirect effects, respectively. Implications This new approach makes it possible to remove the influences of treatments and experimental design from observations and, consequently, from path coefficients and their interpretations. Therefore, the researcher will reduce possible bias in the coefficient estimates, highlighting the real relationship between the variables, and making the results and interpretations more reliable.

Evaluation of rice collection samples <i>Oryza sativa</i> L. in the Russian Far East

Relevance. Early-ripening varieties breeding is a constant task in the selection of rice in the Russian Far Eastern rice-growing zone, since the duration of the vegetation period is the main limiting factor in the region. Mediumand late-ripening forms, although more productive, often do not reach the full maturity phase. Early ripening varieties, as a rule, are less productive. Despite a certain negative relationship between productivity and precocity, it is necessary to select precisely these properties of rice plants.Methods. In the work, 157 samples of the updated rice collection Oryza sativa L. from 22 countries were studied. Varieties Primorsky 29 and Dolinny were used as control. Rice was sown in 2022 in a growing area in 1.54 m2 pots filled with soil. Each sample was placed in rows with row spacing of 15 cm, 10–12 plants in a row (randomized) in double repetition. Standard biometric measurements were taken. The sample size of each sample was 5–10 plants in replication. A total of 2194 plants were analyzed in the work.Results. Based on the first year results studying of the rice collection in the Primorsky Krai conditions, 39 accessions were identified that exceeded the standards in terms of main panicle grain mass and/or plant grain mass. Four of them exceed both standards in productivity (UkrNIS 9706, UkrNIS 3455, DON 7790, Nika Zulanzon). Nine early maturing accessions were identified with a vegetation period of 101–106 days, which is 2–8 days lower than the standards, which retained the productivity of panicles and plants at the control level (Zeravshanika, Onne Mochi, Mu 07-980, Mu-07-1055, Ussur, Uzros 24-24, No. 24, Kascade, Long Jing 15). Samples No. 24 are superior in main panicle grain mass, Mu 07-980 in grain mass of both control plants.

GrainPointNet: A deep-learning framework for non-invasive sorghum panicle grain count phenotyping

Grain count is an important trait in sorghum because it is highly correlated to the potential yield. By accurately phenotyping the number of grains per panicle, farmers and agronomists can better monitor crop development. Additionally, mapping the spatial variability of grain count can help identify areas of the field with higher or lower potential yields, allowing for targeted management strategies. This study introduces a method for predicting grain count for sorghum panicles by employing a deep learning-based regression framework for point clouds and Red Green Blue (RGB) images. The framework integrates global features derived from a point cloud model of the panicle and grain counts detected from a sequence of RGB images. The models were evaluated on a paired dataset of point cloud models and RGB images collected for 147 sorghum panicles, which included a variety of panicle structures and grain counts. The point cloud models were constructed via a proximal structure-from-motion-based photogrammetry workflow. The model uses PointNet as the backbone network for processing the point clouds and YoloV5 for detecting grains from RGB images. Following the grain detection step, a scaled dot product attention module is integrated into the network to process the grain counts obtained from the RGB image sequence. Finally, the global features for the point cloud model and the grain counts are combined to predict the total grain count for the panicle. Furthermore, the models are also evaluated on downscaled low-resolution point clouds to assess their potential to be adapted in the future for point cloud models for panicles acquired in the field. The models were able to predict grain counts for the high-resolution point cloud dataset with a mean absolute percent error of 6.5% and 6.8% for the low-resolution point cloud dataset. The results serve as a proof of concept to demonstrate the viability of using a multimodal approach based on point clouds and RGB images to estimate grain count per panicle. Additional enhancements to the model like the inclusion of a module to register the point cloud and the RGB images, and evaluating more point cloud backbone networks can help further strengthen the method.

Produksi Dan Mutu Benih Dasar Padi (Oryza Sativa L.) Varietas Membramo Pada Aplikasi Pupuk Humic Acid Super Phospate Dan Kaptan Super Phospate

Rice plants (Oryza sativa L) are food plants in the form of clumping grasses, as well as ancient plants originating from Asia and West Africa which are tropical and subtropical climates. This study aims to determine the effect of the interaction of Humic Acid Super Phosphate (HSP) and Kaptan Super Phosphate (KSP) on the basic seed production of rice (Oryza sativa. L) of the Membrano variety. This study used a factorial randomized block design (RBD) using 2 treatment factors. The first factor is HSP consisting of 3 levels, namely A0 : without HSP, A1 : 100 kg/ha and A2 : 200 kg/ha. The second factor is KSP consisting of 3 levels, namely P1: 200 kg/ha, P2: 300 kg/ha and P3: 400 kg/ha. The results obtained were then analyzed using ANOVA (Analysis of Variance) with a level of 5%. This study used the parameters of number of tillers, number of productive tillers, number of per panicle gabai, number of per panicle good grain, percentage of empty grain, and seed production per hectare. The results showed that the administration of HSP had a very significant effect on the parameters of the number of tillers, the number of productive tillers, the number of per panicle grain, the number of per panicle good grain, the percentage of empty grain and seed production per Ha. Meanwhile, the addition of KSP showed a very significant effect on the parameters of the number of per panicle grain, the number of non-sticky grain per panicle, the percentage of empty grain and had a significant effect on the parameter of seed production per Ha, but did not have a significant effect on the number of tillers. The interaction between HSP and KSP administration did not have a significant effect on all parameters, except for the number of productive tillers and production per hectare.

Uji Daya Hasil Tiga Varietas Padi Gogo (oryza sativa L) Terhadap Cekaman Kekeringan

Rice plant (Oryza sativa L.) is a very important food crop in the world, especially in Asia.The need for food in Indonesia continues to increase from year to year. Because of that until nowrice is still a staple food for most of the world's population, especially Asia. Rice is one of the most important food crops because it is a staple food for Indonesian people. Apart from being a staple food, rice cultivation can also provide jobs for rural farmers. This study used a non-factorial randomized block design (RBD), namely rice plant varieties including Situbagendit, Inpago 9, andInpago 12. Each treatment was repeated 3 times, so there were 27 experimental units. Did not have a significant difference to the plant height parameters. The best Gogo rice genotype
 can be determined on the inpago 9 variety which has significant advantages in several parameters including the number of productive tillers, production per hectare, 1000 grain weight and germination power, panicle grains, flowering age, and harvest age. Furthermore, the observation parameters which showed significant or very significant differences were carried out further testsusing the BNJ test with a level of 5%

Bagasse Yield and Quality Traits of Silage Made From Juice-Extracted Sweet Sorghum

This study was conducted to investigate possible use of juice-extracted sweet sorghum stalks (bagasse) as a quality roughage source through silage making. A total of 21 different sweet sorghum (Sorghum bicolor var. saccharatum (L.) Mohlenbr.) genotypes supplied from different sources were used as the primary material of the study. Field experiments were conducted in a randomized blocks design with 4 replications on the experimental fields of Eastern Mediterranean Agricultural Research Institute under 2nd crop conditions during the growing seasons of 2016 and 2017 years. Plants were harvested for bioethanol production at milk-dough stage of panicle grains. Plant leaves and panicles were stripped and remaining stalks were extracted through squeezing. Juice-extracted stalks (bagasse) were ensilaged for 60 days and quality traits were analyzed at the end of silage period. As the average of two years, bagasse yields varied between 42.6-113.9 t ha-1, silage DM yields varied between 11.6-40.0 t ha-1. In addition, crude protein (CP) content, acid detergent lignin (ADL), neutral detergent fiber (NDF) and acid detergent fiber (ADF) values varied between 29.79 - 50.84 g/kg DM, between 49.3 - 91.4 g/kg DM, between 525.1-694.8 g/kg DM and between 351.2-486.8 g/kg DM, respectively. It was concluded based on present findings that silages made from juice-extracted stalks of sweet sorghum grown under 2nd crop conditions of Cukurova region could be used as quality roughage source for livestock. Keywords: Bagasse yield; Genotype; Silage quality; Sweet sorghum

Effect of Different Levels of Bio Fertilizer on Growth and Yield of Sorghum Genotypes

A field experiment was conducted during the autumn season 2021 in one of the farms affiliated to the district of Kuthi (Jableh) located in the north of Babylon province, at longitude 44 east and latitude 44 north, in a sandy loam texture soil. The arrangement of the split plot was used according to the randomized complete block design (R.C.B.D) with three replicates, biofertilizer levels 0, 2, 4, 6 kg ha-1 were used, which occupied the main plots, while the genotypes occupied sub plots, namely (Aniqath, Buhouth70, Rabih, Alkayr, Syrie and American). The traits of plant height, leaf area, chlorophyll content of leaves, number of grains in panicle, weight of 1000 grains, grain yield and biological yield were studied. The results showed the treatment of adding 4 kg ha-1 of biofertilizer excelled in the average plant height cm2 214.14, leaf area and leaf cm2 7897 content of chlorophyll 55.72. Whereas the addition of 6 kg ha-1 excelled and gave the averageshowed superior in triats number of grains in panicle2816, the weight of 1000 grains 27.487, and the grain yield was 7.02 tons.ha-1 and the biological yield was 21,791 tons ha-1. The results also showed a significant difference between the genotypes, where the genotypes Buhouth 70 surpassed in the average plant height cm2 285.94 and weight of 1000 grains 36.212 g, and the biological yield was 31,038 tons ha-1, while the Rabih cultivar excelled in the average leaf area 8560 cm2, number of grains per panicle 3885, grain yield 7.353 tons ha-1, harvest index 36.891%. The nteraction between levels of bio-fertilizer and gentypes showed the highest of grain yield trait at the highest level of bio-fertilizer, which amounted to 8.030 tons ha-1 for Rabih genotype.

DETERMINING THE RIGHT DOSAGE OF INORGANIC FERTILIZERS TO INCREASE GROWTH AND RESULTS THREE LOCAL UPLAND RICE CULTIVARS

Fertilization is one of the important factor to increase production. The aim of this study was to determine the appropriate dosage of inorganic fertilizers to increase the growth and yield of three cultivars of upland rice. This research was conducted at the Center for Research and Development of Gogo Rice, Faculty of Agriculture, Tadulako University, Kalama, Tamarenja Village at an altitude of 180 to 250 above sea level with a latitude of 00o 26'51.5” South Latitude and 119o49'50.6” East Latitude, Sindue District, Donggala Regency, Central Sulawesi Province. The time of the research started from March to August 2020. This research was compiled and carried out using the factorial 2 factors Randomized Block Design (RBD) method. The first factor used three local upland rice cultivars, namely: Pae Bohe, Buncaili, and Uva Buya, while the second factor used six doses of inorganic fertilizers, namely: No fertilization, NPK fertilization 100 kg/ha, 200 kg/ha, 300 kg/ha, 400 kg/ha, and 500 kg/ha. There were 18 combinations, where each treatment was repeated three times so that there were 54 research units. Parameters observed included plant height, number of productive tillers, age of panicle appear, harvest age, number of panicle grains, percentage of empty grain, 1000 grain weight and production. The results showed that the Pae bohe cultivar with fertilization dose of 500 kg/ha produced the highest number of productive tillers (6.69 per clump), the lower percentage of grain pests (5.34%), and the highest production (3.82 tons/ha).

Host Determinants of Fungal Species Composition and Symptom Manifestation in the Sorghum Grain Mold Disease Complex

Sorghum grain mold (SGM) is an important multifungal disease complex affecting sorghum (Sorghum bicolor) production systems worldwide. SGM-affected sorghum grain can be contaminated with potent fumonisin mycotoxins produced by Fusarium verticillioides, a prevalent SGM-associated taxon. Historically, efforts to improve resistance to SGM have achieved only limited success. Classical approaches to evaluating SGM resistance are based solely on disease severity, which offers little insight regarding the distinct symptom manifestations within the disease complex. In this study, three novel phenotypes were developed to facilitate assessment of SGM symptom manifestation. A sorghum diversity panel composed of 390 accessions was inoculated with endogenous strains of F. verticillioides and evaluated for these phenotypes, as well as for the conventional panicle grain mold severity rating phenotype, in South Carolina, U.S.A., in 2017 and 2019. Distributions of phenotype values were examined, broad-sense heritability was estimated, and relationships to botanical race were explored. A typology of SGM symptom manifestations was developed to classify accessions using principal component analysis and k-means clustering, constituting a novel option for basing breeding decisions on SGM outcomes more nuanced than disease severity. Genome-wide association studies were performed using SGM trait data, resulting in the identification of 19 significant single nucleotide polymorphisms in linkage disequilibrium with a total of 86 gene models. Our findings provide a basis of exploratory evidence regarding the genetic architecture of SGM symptom manifestation and indicate that traits other than disease severity could be tractable targets for SGM resistance breeding.

Combining Ability of Some Agronomic Characters of Sweetwaxy Double Recessive Maize Inbred Lines

The present study was undertaken to explore more excellent sweet-waxy maize germplasm resources and provide a theoretical basis for the rational application of sweet-waxy maize inbred lines. Eight sweetwaxy maize inbred lines VB. RN1621, RN1423, RN1432, RN1636, RN1441, RN1443, RN1457 and RN1669 were selected as female parents (P1) and three sweet-waxy maize inbred lines e. g. LN505, LN506 and LN515 were taken as male parents (P2). Using incomplete diallel cross NCII design, 24 combinations were configured to analyze the combining ability of eight agronomic characters such as plant height, ear height, ear grain weight, ear length, number of grains per row, hundred-grain weight, peel residue rate and amylopectin content. It was obaerved that the order of general combining ability was RN1669, RN1636 and LN506. The combination with the highest effective value of special combining ability was RN1641 × LN506, RN1621 × LN506 followed by RN1657 × LN506 which ranked third. Plant height, panicle grain weight and bark residue rate should be selected in the early generation. The ear height, ear length, 100-grain weight and amylopectin content may be selected in the late generation, which can be used for sweet-waxy maize breeding. Bangladesh J. Bot. 51(4): 849-854, 2022 (December) Special

Growth Performances of BRRI dhan55 under Integrated Nutrient Management

Integrated nutrient management is vital for the development and growth of rice (Oryza sativa L.), but they are rarely used nowadays due to the widespread use of inorganic fertilizers. So, the current research was executed to determine the effect of organic amendments on different growth parameters of BRRI dhan55. A field investigation was managed at the Plant Pathology field lab, Sylhet Agricultural University, from November 2018 to April 2019. Different combinations of organic amendments (T1= Recommended Fertilizer Dose, RFD which includes TSP 100g 10 m-2, MoP 100g 10 m-2, Gypsum 50g 10 m-2, Zinc 15g 10 m-2, T2= RFD with vermicompost 2kg 10 m-2, T3= RFD with vermicompost 4 kg 10 m-2, T4= RFD with cowdung 2 kg 10 m-2, T5= RFD with cowdung 4 kg 10 m-2, and T6= RFD with Biochar 4 kg 10 m-2) were used in a RCBD (Randomized Complete Block Design) with three replications. The existing results showed that RFD with biochar treatments showed better performance in terms of the initial weight of grain (50.70 g), clean grain weight (48.55 g), and number of non-effective grains per panicle (27.67) and tiller per hill (12.07). T2 (RFD with vermicompost 2 kg 10 m-2) treatments demonstrated better results in parameters such as weight of grain from a single panicle (4.04 g), single panicle grain weight (3.90 g), panicle length (24.77 cm), and grain per panicle (153.00). Biomass (34.56 g) and above-ground length parameters (90.00 cm) performed better with the T4 treatment (RFD with 2 kg 10 m-2 of cowdung). T6 treatments were showed the highest grain yield (10.71 t ha-1) followed by T3 treatments. Therefore, the present results recommended that organic amendments could be a better supplement than inorganic amendments for the growth performance of BRRI dhan55.

Effects of Rotational Tillage on Soil Physicochemical Properties and Crop Yield in a Rice–Wheat Double Cropping Area

This paper aims to explore issues related to destruction of soil nutrients and structure in a rice-wheat double-cropping area caused by over-tillage prior to rice cultivation. A three-year cycle of rotation tillage pattern (RT), consisting of “no-tillage–no-tillage–plough”, with a straw-returning and direct rice-seeding technology, was designed and tested, and was compared with continuous no-tillage pattern (CN) and conventional ploughing & rotary tillage (PR). The soil rotation experiment in the rice-wheat double-cropping region is located on the southeastern coast of Shandong Province, with a warm, temperate, humid monsoon climate and paddy soil type. Comparison experiments were conducted on the three farming patterns over a period of 3 years, continuously measuring soil physical and chemical properties and crop yields. The results showed that under the same straw-returning conditions, RT significantly increased soil macroaggregates content and enhanced their stability within 0~30 cm (p < 0.05). RT significantly reduced the bulk density of 0~30 cm soil to below 1.5 g/cm3, which was beneficial to crop root growth (p < 0.05). Meanwhile, RT significantly increased the contents of soil organic carbon, total nitrogen, and available phosphorus, and the nutrients are evenly distributed in 0~30 cm layer (p < 0.05). Another result was that the RT significantly increased the rice panicle length, grains number per panicle, and thousand-grain weigh. The crop yield was not significantly different from that of PR, but significantly higher than that of CN (p < 0.05). At the same time, cultivation measures prior to rice cultivation had some after-effects on wheat; the RT significantly increased the average tillers, effective panicle number, effective panicle grain number, and thousand-seed weight of wheat; and the wheat yields were 10.5% and 13.3% higher than that of CN and PR, respectively. This study provides a theoretical reference for improving tillage patterns in rice-wheat double-cropping areas.

Response of some rice cultivars (Oryza sativa L.) to spraying with a natural honey solution and effect on growth and yield characteristics

The field experiment for the current study was carried out at the rice research station in Najaf governorate, affiliated with the Iraqi Ministry of Agriculture. To know the response of three cultivars of rice to spraying with the natural honey solution at different. The factorial experiment was carried out using a randomized complete block design with three replications. The results showed the significant effect of the various study factors with their interactions on the characteristics of the present study, as the honey solution spray treatment at 6 g. l-1 was superior to cultivar Ambar 33 in plant height and number of panicle branches (same as cultivar Mashkhab 1 with the same concentration). The number of grains in panicle, panicle length, 1000 grain weight and fertility percentage (same as cultivar Jasmine with the same concentration) achieved 67.7%, 88.3%, 104.5%, 52.7%, 21.3% and 148% increase for the traits, respectively compared to control treatment. As for the result, the spray treatment of cultivar Jasmine with a concentration of 6 g.l-1 with the natural honey solution was superior in giving the highest grain yield with an increase of 45.6%. Keywords: rice cultivars, spraying, honey, growth, yield.

Combined Analysis of BSA-Seq Based Mapping, RNA-Seq, and Metabolomic Unraveled Candidate Genes Associated with Panicle Grain Number in Rice (Oryza sativa L.).

Rice grain yield is a complex and highly variable quantitative trait consisting of several key components, including the grain weight, the effective panicles per unit area, and the grain number per panicle (GNPP). The GNPP is a significant contributor to grain yield controlled by multiple genes (QTL) and is crucial for improvement. Attempts have been made to find genes for this trait, which has always been a challenging and arduous task through conventional methods. We combined a BSA analysis, RNA profiling, and a metabolome analysis in the present study to identify new candidate genes involved in the GNPP. The F2 population from crossing R4233 (high GNPP) and Ce679 (low GNPP) revealed a frequency distribution fitting two segregated genes. Three pools, including low, middle, and high GNPP, were constructed and a BSA analysis revealed six candidate regions spanning 5.38 Mb, containing 739 annotated genes. Further, a conjunctive analysis of BSA-Seq and RNA-Seq showed 31 differentially expressed genes (DEGs) in the candidate intervals. Subsequently, a metabolome analysis showed 1024 metabolites, with 71 significantly enriched, including 44 up and 27 downregulated in Ce679 vs. R4233. A KEGG enrichment analysis of these 31 DEGs and 71 differentially enriched metabolites (DEMs) showed two genes, Os12g0102100 and Os01g0580500, significantly enriched in the metabolic pathways’ biosynthesis of secondary metabolites, cysteine and methionine metabolism, and fatty acid biosynthesis. Os12g0102100, which encodes for the alcohol dehydrogenase superfamily and a zinc-containing protein, is a novel gene whose contribution to the GNPP is not yet elucidated. This gene coding for mitochondrial trans-2-enoyl-CoA reductase is involved in the biosynthesis of myristic acid, also known as tetradecanoic acid. The Os01g0580500 coding for the enzyme 1-aminoclopropane-1-carboxylate oxidase (OsACO7) is responsible for the final step of the ethylene biosynthesis pathway through the conversion of 1-aminocyclopropane-1-carboxylic acid (ACC) into ethylene. Unlike Os12g0102100, this gene was significantly upregulated in R4233, downregulated in Ce679, and significantly enriched in two of the three metabolite pathways. This result pointed out that these two genes are responsible for the difference in the GNPP in the two cultivars, which has never been identified. Further validation studies may disclose the physiological mechanisms through which they regulate the GNPP in rice.

Pearl Millet (Pennisetum glaucum) Seedlings Transplanting as Climate Adaptation Option for Smallholder Farmers in Niger

Pearl millet is the most widely grown cereal crop in the arid and semi-arid regions of Africa, and in Niger in particular. To determine an optimized management strategy for smallholder farmers in southern Niger to cope with crop production failure and improve cropping performance in the context of climate change and variability, multi-site trials were conducted to evaluate the impacts of transplanting on pearl millet growth and productivity. Eight treatments viz. T1-0NPK (100% transplanting without NPK), T1-NPK (100% transplanting + NPK), T2-0NPK (100% transplanting of empty hills without NPK), T2-NPK (100% transplanting of empty hills + NPK), T3-0NPK (50% transplanting of empty hills without NPK), T3-NPK (50% transplanting of empty hills + NPK), T4-0NPK (farmer practice without NPK), and T4-NPK (farmer practice + NPK) were included in the experiment. Compared to farmer practice, transplanting significantly reduced time to tillering, flowering, and maturity stages by 15%, 27%, and 11%, respectively. The results also revealed that T1-NPK significantly increased panicle weight, total biomass, grain yield, and plant height by 40%, 38%, 27%, and 23%, respectively. Farmers’ evaluations of the experiments supported these findings, indicating three substantial advantages of transplanting, including higher yield (37.50% of responses), larger, more vigorous and more panicles (34.17% of responses), and good tillering (28.33% of responses). An economic profitability analysis of the system revealed that biomass gain (XOF 359,387/ha) and grain gain (XOF 324,388/ha) increased by 34% and 22%, respectively, with T1-NPK. Therefore, it can be inferred that transplanting is a promising strategy for adapting millet cultivation to climate change and variability in southern Niger.

Automatic estimation of rice grain number based on a convolutional neural network.

The grain number on the rice panicle, which directly determines the rice yield, is a very important agronomic trait in rice breeding and yield-related research. However, manual counting of grain number per rice panicle is time-consuming, error-prone, and laborious. In this study, a novel prototype, dubbed the "GN-System," was developed for the automatic calculation of grain number per rice panicle based on a deep convolutional neural network. First, a whole panicle grain detection (WPGD) model was established using the Cascade R-CNN method embedded with the feature pyramid network for grain recognition and location. Then, a GN-System integrated with the WPGD model was developed to automatically calculate grain number per rice panicle. The performance of the GN-System was evaluated through estimated stability and accuracy. One hundred twenty-four panicle samples were tested to evaluate the estimated stability of the GN-System. The results showed that the coefficient of determination (R2) was 0.810, the mean absolute percentage error was 8.44%, and the root mean square error was 16.73. Also, another 12 panicle samples were tested to further evaluate the estimated accuracy of the GN-System. The results revealed that the mean accuracy of the GN-System reached 90.6%. The GN-System, which can quickly and accurately predict the grain number per rice panicle, can provide an effective, convenient, and low-cost tool for yield evaluation, crop breeding, and genetic research. It also has great potential in assisting phenotypic research.