Traits In Maize Research Articles

Chromatin interaction maps reveal genetic regulation for quantitative traits in maize

Chromatin loops connect regulatory elements to their target genes. They serve as bridges between transcriptional regulation and phenotypic variation in mammals. However, spatial organization of regulatory elements and its impact on gene expression in plants remain unclear. Here, we characterize epigenetic features of active promoter proximal regions and candidate distal regulatory elements to construct high-resolution chromatin interaction maps for maize via long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). The maps indicate that chromatin loops are formed between regulatory elements, and that gene pairs between promoter proximal regions tend to be co-expressed. The maps also demonstrated the topological basis of quantitative trait loci which influence gene expression and phenotype. Many promoter proximal regions are involved in chromatin loops with distal regulatory elements, which regulate important agronomic traits. Collectively, these maps provide a high-resolution view of 3D maize genome architecture, and its role in gene expression and phenotypic variation.

In vivo human-like robotic phenotyping of leaf traits in maize and sorghum in greenhouse

In plant phenotyping, leaf-level physiological and chemical trait measurements are needed to investigate and monitor the condition of plants. The manual measurement of these properties is time consuming, error prone, and laborious. The use of robots is a new approach to accomplish such endeavors, enabling automated monitoring with minimal human intervention. In this paper, a plant phenotyping robotic system was developed to realize automated measurement of plant leaf properties. The robotic system comprised of a four Degree of Freedom (DOF) robotic manipulator and a Time-of-Flight (TOF) camera. A robotic gripper was developed to integrate an optical fiber cable (coupled to a portable spectrometer) for leaf spectral reflectance measurement, and a thermistor for leaf temperature measurement. A MATLAB program along with a Graphical User Interface (GUI) was developed to control the robotic system and its components, and for acquiring and recording data obtained from the sensors. The system was tested in a greenhouse using maize and sorghum plants. The results showed that leaf temperature measurements by the phenotyping robot were significantly correlated with those measured manually by a human researcher (R2 = 0.58 for maize and 0.63 for sorghum). The leaf spectral measurements by the phenotyping robot predicted leaf chlorophyll, water content and potassium with moderate success (R2 ranged from 0.52 to 0.61), whereas the prediction for leaf nitrogen and phosphorus were poor. The total execution time to grasp and take measurements from one leaf was 35.5 ± 4.4 s for maize and 38.5 ± 5.7 s for sorghum. Furthermore, the test showed that the grasping success rate was 78% for maize and 48% for sorghum. The phenotyping robot can be useful to complement the traditional image-based high-throughput plant phenotyping in greenhouses by collecting in vivo leaf-level physiological and biochemical trait measurements.

Long-range interactions between proximal and distal regulatory regions in maize

Long-range chromatin interactions are important for transcriptional regulation of genes, many of which are related to complex agronomics traits. However, the pattern of three-dimensional chromatin interactions remains unclear in plants. Here we report the generation of chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) data and the construction of extensive H3K4me3- and H3K27ac-centered chromatin interaction maps in maize. Results show that the interacting patterns between proximal and distal regulatory regions of genes are highly complex and dynamic. Genes with chromatin interactions have higher expression levels than those without interactions. Genes with proximal-proximal interactions prefer to be transcriptionally coordinated. Tissue-specific proximal–distal interactions are associated with tissue-specific expression of genes. Interactions between proximal and distal regulatory regions further interweave into organized network communities that are enriched in specific biological functions. The high-resolution chromatin interaction maps will help to understand the transcription regulation of genes associated with complex agronomic traits of maize.

Fine mapping and candidate gene analysis of qhkw5-3, a major QTL for kernel weight in maize.

KEY MESSAGE: qhkw5-3, a major QTL for kernel weight in maize, was mapped to an interval of 125.3kb between the InDel markers InYM20 and InYM36, and the candidate genes were analysed. Yield, of which kernel weight is a major component, is the primary trait of interest in maize breeding programmes. In our previous study, a major QTL (named qhkw5-3), which controls hundred-kernel weight, was identified and mapped to the interval between simple sequence repeat (SSR) markers SYM033 and SYM108 on chromosome 5, using an F2:3 population derived from a cross between the maize inbred line Zheng58 and the single-segment substitution line Z22. In order to fine map qhkw5-3, a larger BC1F1 segregating population of 14,759 seeds, derived from a (Z22 × Zheng58) × Z22 cross, was screened using the SSR markers SYM036 and SYM119. Forty genotypes with donor chromosomal fragments of different lengths were obtained. Progeny testing results indicated that qhkw5-3 was mapped to an interval of 442.6kb between the SSR markers SYM077 and SYM084. Overlap mapping results, based on seven homozygous recombinant lines, showed that qhkw5-3 was narrowed down to an interval of 125.3kb between the InDel markers InYM20 and InYM36. Within this interval, six candidate genes were analysed using qRT-PCR. The results of this study lay the foundations for cloning and functional analysis of qhkw5-3 and will contribute to advancing our knowledge of the genetic basis of yield traits in maize.

Maize responsiveness to Azospirillum brasilense: Insights into genetic control, heterosis and genomic prediction.

Several studies have shown differences in the abilities of maize genotypes to facilitate or impede Azospirillum brasilense colonization and to receive benefits from this association. Hence, our aim was to study the genetic control, heterosis effect and the prediction accuracy of the shoot and root traits of maize in response to A. brasilense. For that, we evaluated 118 hybrids under two contrasting scenarios: i) N stress (control) and ii) N stress plus A. brasilense inoculation. The diallel analyses were performed using mixed model equations, and the genomic prediction models accounted for the general and specific combining ability (GCA and SCA, respectively) and the presence or not of G×E effects. In addition, the genomic models were fitted considering parametric (G-BLUP) and semi-parametric (RKHS) kernels. The genotypes showed significant inoculation effect for five root traits, and the GCA and SCA were significant for both. The GCA in the inoculated treatment presented a greater magnitude than the control, whereas the opposite was observed for SCA. Heterosis was weakly influenced by the inoculation, and the heterozygosity and N status in the plant can have a role in the benefits that can be obtained from this Plant Growth-Promoting Bacteria (PGPB). Prediction accuracies for N stress plus A. brasilense ranged from 0.42 to 0.78, depending on the scenario and trait, and were higher, in most cases, than the non-inoculated treatment. Finally, our findings provide an understanding of the quantitative variation of maize responsiveness to A. brasilense and important insights to be applied in maize breeding aiming the development of superior hybrids for this association.

Response of white maize hybrids to plant densities and nitrogen fertilizer rates

Two field experiments were conducted on the Farm of Agric. Res. and Exp. Center of Fac. of Agric. Moshtohor, Benha University, Toukh Directorate, Qalyubia Governorate, Egypt, during the two successive summer growing seasons of 2016 and 2017 to study the effect of three plant population densities i.e. 20000, 24000 and 28000 plants/feddan (fed) and three nitrogen fertilizer rates, i.e. 90, 120 and 150 kg N/fed on the growth traits, yield components, yield and some kernels chemical properties of three white single cross hybrids of maize (S.C. 7071, S.C. 30K8 and S.C. 2031). The obvious results of this investigation can be summarized as follows: Increasing plant population density from 20000 to 28000 plants/fed significantly increased mean values of No. of days from planting to 50 % tasseling and silking, leaf area index, plant height (cm), ear height (cm) No. of barren plants/fed, No. of ears/fed, stover yield/fed (kg) and biological yield/fed (kg) in both seasons. On the other hand, mean values of No. of green leaves/plant, leaf area/plant (cm2), No. of plants carried two ears/fed, No. of kernels/ear, ear weight (g), shelling (%), 100-kernel weight (g), ear yield/fed (kg), grain yield/fed (kg), harvest index, nitrogen uptake/fed (kg) and protein yield/fed (kg) were significantly decreased in the two seasons. Allmost traits of maize under study were significantly increased by increasing nitrogen fertilizer rates from 90 and 120 to 150 kg N/fed except, No. of days to 50 % tasseling and silking as well as No. of barren plants/fed were significantly decreased with increasing nitrogen rates in the both seasons, nitrogen fertilizer rate of 150 gave the best mean values for all maize traits under study. White single cross hybrids of maize were significantly differed in all maize traits under study in the both seasons. Maize hybrid of S.C. 30K8 was significantly surpassed S.C. 7071 and S.C. 2031 in mean values of No. of plants carried two ears/fed, No. of ears/fed, No. of kernels/ear, grain yield/fed and harvest index as well as gave the lowest mean values of No. of barren plants/fed and the shortest period from planting to 50 % tasseling or silking in the both seasons. Moreover, S.C. 2031 surpassed the other two maize hybrids in mean values of leaf area/plant, leaf area index, ear weight, 100-kernel weight, ear yield/fed, biological yield/fed, nitrogen uptake/fed and protein yield/fed in the two seasons. Meanwhile, S.C. 7071 recorded the highest mean values of No. of green leaves/plant, plant height, ear height, shelling % and stover yield/fed in the two seasons. The first order interactions between (20000 plants/fed X 150 kg N/fed), (24000 plants/fed X S.C. 30K8), (20000 plants/fed X S.C. 2031) and (150 kg N/fed X S.C. 30K8) as well as the second order interactions between (24000 plants/fed X 150 kg N/fed X S.C. 30K8) and (20000 plants/fed X 150 kg N/fed X S.C. 2031) were significantly recorded the greatest grain yield/fed as compared with the others interactions in the both seasons.

Genetic dissection of stalk lodging-related traits using an IBM Syn10 DH population in maize across three environments (Zea mays L.).

Stalk lodging severely limits the grain yield of maize (Zea mays L.). Mechanical stalk strength can be reflected by the traits of stalk diameter (SD), stalk bending strength (SBS), and lodging rind penetrometer resistance (RPR). To determine the genetic basis of maize stalk lodging, quantitative trait loci (QTLs) were mapped for these three traits using the IBM Syn10 DH population in three environments. The results indicated that there were strong genetic correlations among the three traits, and the analyses of phenotypic variations for SD, SBS, and RPR across the three environments showed high broad-sense heritability (0.6843, 0.5175, and 0.7379, respectively). In total, 44 significant QTLs were identified control the above traits across the 3 environments. A total of 14, 14, and 16 QTLs were identified for SD, SBS, and RPR across single-environment mapping, respectively. Notably, ten QTLs were stably expressed across multiple-environments, including two QTLs for SD, three for SBS, and five for RPR. Three major QTLs each accounting for over 10% of the phenotypic variation were qSD6-2 (10.03%), qSD8-2 (13.73%), and qSBS1-2 (11.89%). Comprehensive analysis of all QTLs in this study revealed that 5 QTL clusters including 12 QTLs were located on chromosomes 1, 3, 7, and 8, respectively. Among these 44 QTLs, 9 harbored 13 stalk lodging-associated SNPs that were detected by our recently published work, with 1 SNP successfully validated in the IBM Syn10 DH population. These chromosomal regions will be useful for marker-assisted selection and fine mapping of stalk lodging-related traits in maize.

MaizeNet: a co-functional network for network-assisted systems genetics in Zea mays.

Maize (Zea mays) has multiple uses in human food, animal fodder, starch and sweetener production and as a biofuel, and is accordingly the most extensively cultivated cereal worldwide. To enhance maize production, genetic factors underlying important agricultural traits, including stress tolerance and flowering, have been explored through forward and reverse genetics approaches. Co-functional gene networks are systems biology resources useful in identifying trait-associated genes in plants by prioritizing candidate genes. Here, we present MaizeNet (http://www.inetbio.org/maizenet/), a genome-scale co-functional network of Z.mays genes, and a companion web server for network-assisted systems genetics. We describe the validation of MaizeNet network quality and its ability to functionally predict molecular pathways and complex traits in maize. Furthermore, we demonstrate that MaizeNet-based prioritization of candidate genes can facilitate the identification of cell wall biosynthesis genes and detect network communities associated with flowering-time candidate genes derived from genome-wide association studies. The demonstrated gene prioritization and subnetwork analysis can be conducted by simply submitting maize gene models based on the commonly used B73 RefGen_v3 and the latest B73 RefGen_v4 reference genomes on the MaizeNet web server. MaizeNet-based network-assisted systems genetics will substantially accelerate the discovery of trait-associated genes for crop improvement.

Chelators induced uptake of cadmium and modulation of water relation, antioxidants, and photosynthetic traits of maize.

The present study was aimed to reveal the effect of cadmium (Cd)-polluted soil on the activation of antioxidant enzymes, photosynthesis, pigments, water relation, and other biochemical traits and comparative effect of synthetic and organic chelators. A pot experiment was conducted using two maize varieties grown in Cd-contaminated (15 and 30mgkg-1) soil and chelators (1mM EDTA, and 1mM citric acid). Cd decreased biomass and photosynthetic traits while increased malondialdehyde (MDA) contents, total proteins, and antioxidant enzyme activities. Addition of EDTA enhanced Cd uptake, antioxidative enzyme, and total proteins; however, it reduced the water, osmotic, and turgor potential as compared to Cd alone. Addition of citric acid has lessened the antioxidant enzyme activities and MDA contents and enhanced the plant biomass as compared to Cd alone. Increases in antioxidants and MDA content were found to be positively related to the Cd contents in shoot and root. The application of citric acid significantly alleviated the Cd-induced toxic effects, showing remarkable improvement in biomass. These results indicated that EDTA was more effective for mobilizing Cd from soil to the root and shoot than citric acid; however, the physiological traits and plant biomass were more strongly inhibited by EDTA than by the Cd. Our study implies that citric acid ameliorated the negative effect of Cd on physiological traits and biomass, and hence could be used effectively for Cd phytoextraction.

Mapping of quantitative trait loci for seedling salt tolerance in maize

Improved salt tolerance is a major goal for maize breeders, but the control of salt tolerance-related traits in maize is poorly understood. A set of 209 doubled haploid (DH) lines derived from the maize hybrid Xianyu335 was genotyped using 1335 single-nucleotide polymorphism (SNP) markers. Biomass-related traits under salt stress were used as salt tolerance indicators, and a quantitative trait loci (QTL) analysis was conducted in hydroponic culture under salt-stress and normal conditions. Fourteen traits showed significant phenotypic differences between parents, and 16 traits showed transgressive segregation in the DH population. We detected 65 QTL: 41 associated with salt tolerance and 24 related to normal growth. Salt tolerance-related QTL clustered on chromosomes 1, 3, 7, and 9, among which 13 major effect QTL on chromosome 1 individually explained more than 21% of the phenotypic variation. Of these large-effect QTL, QTL controlling seven traits upon salt treatment and two salt tolerance indexes were co-located; they extensively overlapped with the remaining four co-localized QTL related to four other salt tolerance indexes. The QTL identified here shed new light on the molecular mechanism of salt tolerance in maize and may provide robust functional markers for marker-assisted selection of salt tolerant maize varieties.

Population structure and association mapping studies for yield-related traits in Maize (Zea mays L.)

Association mapping is an efficient approach for dissecting the genetic architecture of yield-related traits using single nucleotide polymorphism (SNP) markers in maize. The present study was carried out with a set of 93 diverse maize accessions with the objectives of analysing the population structure and conducting association mapping between SNP markers and yield-related traits viz. number of kernel rows per ear (NKR), number of kernel columns per ear (NKC), 100 grain weight (HGW) and grain yield (GY). Illumina golden gate assay containing 1536 SNPs distributed in all the chromosomes were used for genotyping 93 maize accessions. The population structure studies depicted the presence of five subpopulations, named ZM1, ZM2, ZM3, ZM4 and ZM5, contained 21, 16, 19, 12 and 25 accessions, respectively. Association mapping analysis carried out using mixed linear model (MLM), which is identified 36 marker-trait associations (MTAs) in the two years. Of these, 26 MTAs were detected either nearby or flanking the regions where the genomic regions have been reported. While, remaining10 MTAs were detected in the novel genomic region. The number of markers associated with each trait ranged from 6 (NKC) to 13 (HGW). We also found that one trait was associated with many markers (e.g., HGW with 13 markers), and single marker was also associated with multiple traits (eg. PZB00114_1 associated with HGW and GY). Our results provide good information for genetic architecture of yield-related traits and associated SNP markers could be valuable in implementing marker assisted selection (MAS) in maize breeding programs.

Development of enzymes for robust aryloxyphenoxypropionate and synthetic auxin herbicide tolerance traits in maize and soybean crops.

Effective management of weedy species in agricultural fields is essential for maintaining favorable growing conditions and crop yields. The introduction of genetically modified crops containing herbicide tolerance traits has been a successful additional tool available to farmers to better control weeds. However, weed resistance challenges present a need for additional herbicide tolerance trait options. To help meet this challenge, a new trait that provides tolerance to an aryloxyphenoxypropionate (FOP) herbicide and members of the synthetic auxin herbicide family, such as 2,4-dichlorophenoxyacetic acid (2,4-D), was developed. Development of this herbicide tolerance trait employed an enzyme engineered with robust and specific enzymatic activity for these two herbicide families. This engineering effort utilized a microbial-sourced dioxygenase scaffold to generate variants with improved enzymatic parameters. Additional optimization to enhance in-plant stability of the enzyme enabled an efficacious trait that can withstand the higher temperature conditions often found in field environments. Optimized herbicide tolerance enzyme variants with enhanced enzymatic and temperature stability parameters enabled robust herbicide tolerance for two herbicide families in transgenic maize and soybeans. This herbicide tolerance trait for FOP and synthetic auxin herbicides such as 2,4-D could be useful in weed management systems, providing additional tools for farmers to control weeds. © 2019 Society of Chemical Industry.

Vertical distributions of chlorophyll and nitrogen and their associations with photosynthesis under drought and rewatering regimes in a maize field

In this study, we characterize the vertical leaf distribution of chlorophyll (Chl) and nitrogen (N) content and their associations with leaf photosynthetic responses in Zea mays L. under field watering regimes. We simulated five precipitation patterns, including a drought-rewatering sequence using an electric-powered, rainproof shelter. The results indicate the vertical leaf Chl and N distribution versus the cumulative leaf-area index (LAIc) fit well into a significant quadratic function. The simulated precipitation patterns significantly influenced the parabolic curve trajectory patterns and their parameters. Chlorophyll and N contents had the same trend, with a close and positive relationship. Drought stress followed by rewatering increased the slopes of the linear equations but narrowed the parabolic opening of the quadratic functions. This finding implies that the relationship between Chl and N content can be used to estimate responses to drought and rewatering. The findings also suggested that the relationship patterns between Chl and N levels could be an assessment tool for N-fertilizer managements under different drought conditions to maintain high yields in maize production. Principal component analysis indicated the correlations between functional traits in maize leaves and the responses to drought and rehydration. These findings help to improve drought management and cultivar selection, which will be important in coping with the severe intensity and high frequency of episodic drought events expected from climate change.

Green manure and phosphorus fertilization affect weed community composition and crop/weed competition in organic maize

AbstractGreen manure and compost-enriched in phosphorus can promote the sustainability of cropping systems by increasing soil fertility over the long term. They can also be used to manage crop/weed interactions, a key element in guaranteeing an appropriate level of satisfactory crop yields. We studied how green manuring with hairy vetch (Vicia villosaRoth.) and the application of different types of phosphorous-enriched compost affect weed/maize (Zea maysL.) interactions in an organic stockless Mediterranean agroecosystem for two consecutive dry years. Green manure stimulated the expression of maize traits related to a higher competitive ability against weeds, such as early growth, height and leaf area index, while the effect of compost was less clear. Regarding crop/weed competition, both green manuring and a phosphorus-enriched compost application gave a significant advantage to maize. Neither green manure nor compost increased total weed density and biomass compared to the control. Green manuring significantly affected the weed community composition. The relative density of ruderal and competitive-ruderal species (according to Grime's classification) was higher in plots where the green manure was applied. The use of green manure, together with novel composting techniques, significantly affected crop/weed competitive interactions, favoring maize, but also creating favorable conditions for unwanted weed species such as competitive-ruderals. Increasing nitrogen availability in the early growth stages of maize through green manuring can increase crop competitive ability. However, this may not suffice to preserve the system from future weed problems, should potentially detrimental species be selected. Dedicated strategies for the control of emerging weed species may thus be needed.

Effects of soil water on maize root morphological and physiological responses to phosphorus supply

AbstractWater shortage directly constrains plant growth and survival, and indirectly influences plant responses to soil mineral nutrients, especially low‐mobility nutrients such as phosphorus (P). We examined the effects of soil water content on the responses of agronomic and root morphological and physiological traits of maize (Zea mays L. cv. NE15) to P supply. Seven P supply levels (0, 12.5, 25, 50, 75, 100, and 300 mg P kg−1 soil) and two water regimes (well watered, WW; water stress, WS) were employed. Shoot dry weight, root dry weight, and root length were enhanced with the increase of P supply rates, while the root : shoot ratio, specific root length, and transcription levels of four inorganic phosphate (Pi) transporter genes (Pht1;1–4) declined with the increase of P supply rates. Under WS conditions, root dry weight and root length decreased by 4–38% and 6–32%, respectively, compared to the WW treatment, whereas the root : shoot ratio and specific root length increased by 7–33% and 8–28%, respectively. Pi transporter gene transcription was up‐regulated and that of the arbuscular‐mycorrhizal‐induced transporter (Pht1;6) gene was both up‐ and down‐regulated in response to the WS treatment. Comprehensive analysis revealed that interaction between maize root morphological and physiological traits was stimulated as a strategy for efficient P acquisition under WS conditions. This study is the first to use both morphological and physiological traits to describe the impacts of soil water conditions on maize responses to P fertilization. Our results provide valuable information for optimization of P management under different soil water conditions.

Factors Affecting the Accuracy of Genomic Selection for Agricultural Economic Traits in Maize, Cattle, and Pig Populations.

Genomic Selection (GS) has been proved to be a powerful tool for estimating genetic values in plant and livestock breeding. Newly developed sequencing technologies have dramatically reduced the cost of genotyping and significantly increased the scale of genotype data that used for GS. Meanwhile, state-of-the-art statistical methods were developed to make the best use of high marker density genotype data. In this study, 14 traits from four data sets of three species (maize, cattle, and pig) and five influential factors that affect the prediction accuracy were evaluated, including marker density (from 1 to ~600 k), statistical method (GBLUP-A, GBLUP-AD, and BayesR), minor allele frequency (MAF), heritability, and genetic architecture. Results indicate that in the GBLUP method, higher marker density leads to a higher prediction accuracy. In contrast, BayesR method needs more Monte Carlo Markov Chain (MCMC) iterations to reach the convergence and get reliable prediction values. BayesR outperforms GBLUP in predicting high or medium heritability trait that affected by one or several genes with large effects, while GBLUP performs similarly or slightly better than BayesR in predicting low heritability trait that controlled by a large amount of genes with minor effects. Prediction accuracy of trait with complex genetic architecture can be improved by increasing the marker density. Interestingly, for simple traits that controlled by one or several genes with large effects, higher marker density can cause a lower prediction accuracy if the QTN is included, but leads to a higher prediction accuracy if the QTN is excluded. The quantity of genetic markers with low MAF would not significantly affect the prediction accuracy of GBLUP, but results in a bad prediction accuracy performance of BayesR method. Compared with GBLUP-A, GBLUP-AD didn't show any advantages in capturing the non-additive variance for the traits with high heritability. The factors that affected prediction accuracy are discussed in this study and indicate that a combination of either GBLUP or BayesR method with moderate marker density and favorable polymorphism single nucleotide polymorphisms (SNPs) (~25 k SNPs) would always produce a good and stable prediction accuracy with acceptable breeding and computational costs.

Calculation Method for Phenotypic Traits Based on the 3D Reconstruction of Maize Canopies.

A reasonable plant type is an essential factor for improving canopy structure, ensuring a reasonable expansion of the leaf area index and obtaining a high-quality spatial distribution of light. It is of great significance in promoting effective selection of the ecological breeding index and production practices for maize. In this study, a method for calculating the phenotypic traits of the maize canopy in three-dimensional (3D) space was proposed, focusing on the problems existing in traditional measurement methods in maize morphological structure research, such as their complex procedures and relatively large error margins. Specifically, the whole maize plant was first scanned with a FastSCAN hand-held scanner to obtain 3D point cloud data for maize. Subsequently, the raw point clouds were simplified by the grid method, and the effect of noise on the quality of the point clouds in maize canopies was further denoised by bilateral filtering. In the last step, the 3D structure of the maize canopy was reconstructed. In accordance with the 3D reconstruction of the maize canopy, the phenotypic traits of the maize canopy, such as plant height, stem diameter and canopy breadth, were calculated by means of a fitting sphere and a fitting cylinder. Thereafter, multiple regression analysis was carried out, focusing on the calculated data and the actual measured data to verify the accuracy of the calculation method proposed in this study. The corresponding results showed that the calculated values of plant height, stem diameter and plant width based on 3D scanning were highly correlated with the actual measured data, and the determinant coefficients R2 were 0.9807, 0.8907 and 0.9562, respectively. In summary, the method proposed in this study can accurately measure the phenotypic traits of maize. Significantly, these research findings provide technical support for further research on the phenotypic traits of other crops and on variety breeding.

TREATMENT-TRAIT (TT) BIPLOT AS AN EFFECTIVE TOOL FOR SUPPORTING DECISION MAKING IN MAIZE FERTILIZER PROGRAM

This work aimed to study the effect of FYM rates (0, 10 & 20 m3 fed-1) and application in time of N fertilizer on maize grain yield and its attributes using single cross hybrid 130 at two field experiments. The technique of treatment - trait (TT) biplot graph was used to study the interrelationships among maize traits. The Results showed that application of 10 or 20 m3 FYM and adding the recommended N fertilizer on these doses with first, second or third irrigations gave highest values for the grain yield and most agronomic traits. It is obvious that the highest correlation coefficients were obtained between grain yield and each of number of ears plot-1 (NE),ear length (EL), ear diameter (ED) and 100 kernel weight (KW),under Gemmeiza location, while the traits of days to 50%tassiling and silking, plant height (PH), ear height (EH), number of ears plot-1 (NE) and 100 kernel weight (KW) were the most associated traits with grain yield under Sids location. Using the TT biplot graph, results revealed that the best performance treatments for most studied across the two locations were the application (T11) before as well as application (T10). The results showed that TT biplot graph was an effective statistical tool to study the effects of treatments on yield and its attributes and also to discover the interrelationships among these traits. Accordingly, the maize breeder should give interest in the interrelationships among grain yield and its attributes when planning the breeding program.

Integration of potassium fertilizer with mechanically prepared potassium-enriched compost from city market waste for improvement in maize production

Abstract In modern agriculture, potassium (K) is being considered as an indispensable nutrient for sustainable crop production. However its use is negligible or minimal in current agricultural practices of Pakistan. In view of the significance of K, a field experiment was conducted to evaluate the effects of K-enriched recycled organic wastes (potassium enriched compost- KEC) for improving yield of hybrid maize (Hycorn-11-plus). The KEC was prepared from the market wastes (fruits and vegetables) using mechanical composter at Institute of Soil and Environmental Sciences, University of Agriculture, Faisalabad, Punjab, and applied @ 300 kg ha-1. The inorganic K treatments were involved 0, 60, 45, 30, 15 K2O ha-1 in the form of potassium sulphate (K2SO4). The randomized complete block design was used. The enrichment of compost with K reduced carbon to nutrient (N, P, K) ratios and improved the nutrients content of the compost. The results of field study revealed that integration of KEC and inorganic K fertilizer (K2SO4) showed that growth and yield traits of maize (including K concentration of maize stover and grain) improved under the combined application of 60 and or 45 kg K ha-1 in conjunction with 300 kg KEC improved most of the as against 60 kg ha-1 K alone. The overall findings of present study suggested that the use of KEC @ 300 kg with 75% inorganic K fertilizer (45 kg K ha-1) improved growth, yield and K concentrations of hybrid maize. Keyword: Compost; Maize production; Market waste; Potassium http://dx.doi.org/10.19045/bspab.2019.80026

Effect of Organic, Inorganic and Nano Fertilizers on Agronomic Traits of Maize

Integrated nutrient management is a judicious application of fertilizer from different sources for sustainable agriculture. Two-year field experiment was conducted at the Agric. Res. and Exp. Center, Fac. of Agric., Moshtohor, Banha Univ., Kalubia Governorate, during the two growing seasons 2016 and 2017, to study the influence of three biogas sludge manure rates (0, 3.5, 7 ton/fed), four mineral NP fertilizer i.e. (N0P0, N40P7.5, N80P15,N120P22.5 kg/fed) and three levels of nano micronutrients foliar application (0, 100 and 200 g/fed) on growth, yield and its component of maize (Zea mays L.). The experiment was laid out in split-split-plot design with three replications. Results of combined analysis of the two seasons showed that increasing biogas rate to 3.5 ton/fed significantly increased grain weight/ear as well as grain and biological yield/fed compared with control. Yield components (ear length, grain weight/ear and 100-grain weight) as well as grain and biological yield (ton/fed) were significantly increased by increasing NP fertilizer levels up to N80P15 kg/fed. Significant effect of nano micronutrients application on No. of ears/plant and 100-grain weight at rate 100 g/fed and plant height, grain weight/ear as well as grain and biological yield/fed at rate 200 g/fed were detected. Interaction effect between biogas x NP x nano had significant effect on ear length, grain weight/ear as well as grain and biological yield. Treatment 3.5 ton biogas x N80P15 kg x 200 g nano/fed was the best treatment had 56.02% more grain yield, in comparison to control with increased soil fertility and saving 33.3% of mineral fertilizer compared with high fertilizer level.