This dataset comprises detailed agronomic measurements from a series of wheat field trials conducted in Roma, Queensland, designed to investigate the effects of sowing depth, coleoptile type, soil strength, and other factors on plant emergence, growth, and yield. The collection includes two primary Excel (.xlsx) files: a master data sheet containing raw and processed measurements from individual plots across multiple trials (MET, Pressure, Seed Size), and an analysis workbook summarizing statistical outputs and model selections. These main files are complemented by MET Deep Tiny Tag and MET Shallow Tiny Tag .csv files. The master sheet documents plot-level data for each trial, including sowing conditions (depth, date, soil strength at multiple depths), plant traits (coleoptile length and diameter), emergence counts at multiple intervals (7, 14, 21 days after sowing), and final emergence. It also includes biomass and grain yield metrics, harvest index, grain quality parameters (protein, moisture, test weight, screenings), and maturity dates. Each plot is identified by location, replicate, treatment, and variety, with coleoptile type (long or conventional) and seed size (standard or large) noted where relevant. The analysis workbook provides statistical summaries from ANOVA and regression models, highlighting significant effects and interactions among depth, variety, coleoptile type, and soil strength. It includes model selection outputs for emergence and coleoptile traits, with R² values and p-values for various combinations of predictors. Environmental conditions such as soil strength was measured at sowing and at multiple intervals post-sowing using gravimetric and pressure-based methods. Drone imagery, EM38 surveys, and weather station data were also collected to support spatial and temporal analysis. Data was processed using GenStat with fixed and random effects models, and transformations were applied where necessary to meet distributional assumptions. The dataset includes over 70 variables, with definitions embedded in column headers and trial documentation. Codes such as LCW (long coleoptile wheat) and conventional types are used to distinguish genetic traits. The dataset is structured to support multivariate analysis and is suitable for evaluating genotype by environment interactions, emergence dynamics, and yield formation under varying agronomic conditions.

This dataset comprises soil, plant, climatic, and management data from a 2023 field experiment conducted at Ungarra, Eyre Peninsula, South Australia. The trial aimed to evaluate the establishment and performance of long coleoptile wheat genotypes compared to short coleoptile varieties under varying sowing depths and fertiliser regimes. Three distinct experiments were conducted side-by-side: 1. Systems Trial (Water Balance): Investigated water balance at sowing using tarp treatments and sowing moisture assessments. 2. Core Genotype × Sowing Depth Trial: Compared eight wheat genotypes across three sowing depths (shallow, mid, deep). 3. Genotype × Depth × Nutrition Trial: Explored interactions between two genotypes, two sowing depths, and three fertiliser rates (45, 100, 150 kg/ha Monoammonium phosphate). Data was collected through field-based measurements including plant counts, seeding depth, NDVI (via Greenseeker), canopy cover (via Canopeo), biomass, spike counts, and grain yield using a plot header. Soil chemistry was analyzed by Eurofins APAL using standardized test codes, and rainfall data were sourced from a nearby soil moisture probe. All data was manually recorded and digitised for further analysis. The data is presented in an Excel workbook (.xlsx) contains trial details, metadata, raw experimental data and soil chemistry. The sheets are interrelated through shared identifiers such as trial number, sowing depth, genotype, and treatment number. Test variables across trials, include a range of agronomic, physiological, and soil metrics, such as grain yield, harvest ratio, biomass, coleoptile length, plant density, seeding depth, NDVI, estimated canopy cover and soil pH, EC, N, P). Codes and Symbols: - GS: Growth Stage (e.g., GS10–11) - NF: Nil Found (used in plant emergence data) - WB: Water Balance treatment codes (e.g., WB1, WB2)

This dataset comprises three Excel (.xlsx) of interrelated field trials conducted at Condobolin, NSW, during the 2024 winter cropping season, focusing on wheat genotype performance under varying agronomic treatments and environmental conditions. The trials include a Nutrition Trial, Seed Size Trial, and a Core Trial, each exploring distinct but complementary aspects of long coleoptile wheat development. Data is structured across multiple sheets detailing experimental design, treatment applications, phenological observations, soil and environmental metrics, and yield outcomes. Each file contains genotype-specific data across multiple ranges and rows, with treatments involving sowing depths (4 cm and 12 cm), fertilizer placement (with seed or above seed), and seed size (small or large). The Nutrition Trial includes fertilizer rate variations and detailed soil nutrient profiles, while the Seed Size Trial emphasizes seed size effects on emergence, biomass, and grain quality. The Core Trial integrates sowing time comparisons (TOS 1 and TOS 2), coleoptile measurements, and soil temperature logging. Methodological details include precise sowing dates, herbicide and insecticide applications, NDVI readings, frost tipping scores, and maturity assessments. Soil moisture was measured gravimetrically at multiple depths pre- and post-harvest, and nutrient analyses were conducted on samples from 0–60 cm. Environmental data from Condobolin AWS provides daily temperature and rainfall records, highlighting frost events and dry periods critical to crop development. The dataset includes over 30 variables such as genotype, sowing depth, seed size, plant counts, dry weight, grain yield, head counts, phenology scores, and grain quality metrics. Codes like “Mace18_4_W_L” or “Calibre_12_A_H” denote genotype, depth, placement, and fertilizer rate. Time-series soil temperature data is recorded at sub-minute intervals, offering high-resolution insights into thermal conditions affecting emergence. This dataset enables robust statistical analysis of genotype performance under frost-prone and moisture-limited conditions without requiring further input from the original researchers.

This dataset comprises comprehensive agronomic and phenotypic data from the 2024 long coleoptile wheat trials conducted at Breeza, New South Wales, Australia. The trials include four major experiments: N_MET_24 (multi-environment trial), N_Durum_24 (durum wheat trial), Seed_size (seed size and depth interaction), and Victrado (water regime and depth interaction). The trials were established on 36 ranges with 5 rows per bed, 2-meter bed centres, and 11-meter ranges (10.8 meters planted). Fertilisation included 238 kg/ha of urea and 70 kg/ha of Granulock Z Extra Treated starter. Herbicide applications included Axil Xtra, Starane, MCPA, and Metsulfuron. Sowing occurred in two time-of-sowing (TOS) windows: TOS1 on 28 May and TOS2 on 4 July 2024. The trials evaluated multiple genotypes including Mace, Mace18, Scepter, Magenta, Magenta13, Calibre, Westcourt, V190245-6, and Sunchaser, under varying treatments such as sowing depth (4 cm and 12 cm), seed size (small and large), FCR resistance (plus/minus), and water regimes (well-watered and dryland). The dataset includes over 450 unique plots across the trials. Variables recorded include emergence and plant counts (outside and inside row counts, plants per square meter), seedling traits (depth and length), Zadok growth stage scores, dry biomass at GS32, and final harvest metrics such as yield (T/ha), protein content, test weight, grain weight, and grain size. Temperature logger data and phenological observations are also included. Data is structured across multiple sheets, each corresponding to a specific trial or measurement type, with consistent identifiers for site, trial, TOS, genotype, depth, and treatment. The dataset enables analysis of genotype-by-environment interactions, agronomic performance under deep sowing, and the influence of seed size and water availability on wheat establishment, growth, and yield.

This dataset will contain phenotypic observations of a large number of wheat genotypes evaluated in 2016-2017 and 2017-2018 at the International Maize and Wheat Improvement Center in Ciudad Obregon, Mexico.

This dataset comprises detailed agronomic and phenotypic data from a series of wheat trials conducted in 2024 at the Narrabri, New South Wales, focusing on the performance of long coleoptile wheat genotypes under varying sowing depths, seed sizes, water regimes, and disease treatments. The collection includes multiple Excel (.xlsx) sheets, each representing different aspects of the trial: experimental diary, plot layout, multi-environment trials (MET), durum wheat trials, seed size trials, Victrado trials (irrigated and dryland), temperature logger data, GS32 dry matter biomass, and multiple plant count records across time points. The MET and Durum trials were conducted across two times of sowing (TOS1 and TOS2), with sowing depths of 4 cm and 12 cm, and included genotypes such as Mace, Scepter, Magenta, and Westcourt. Seed size trials compared small and large seeds, while Victrado trials assessed genotype responses under well-watered and dryland conditions with factorial combinations of depth and Fusarium crown rot (FCR) treatments. Data collection included emergence counts, seedling depth and length, biomass at GS32, head counts, plant height, lodging, and final harvest metrics such as grain yield, test weight, protein content, and grain size. Soil moisture was monitored using Tiny Tag and disposable probes, and neutron moisture meters (NMM) at depths from 0 to 150 cm. The dataset includes over 70 variables, with consistent identifiers for site, trial, genotype, depth, treatment, and replication. Codes such as “4cm_Mace” or “12cm_Sunchaser+” denote sowing depth, genotype, and treatment combinations. The data were collected using standard field trial protocols, with sowing conducted using tyned implements and press wheels at 25 cm row spacing. Fertiliser applications included 238 kg/ha urea and 70 kg/ha Granulock Z Extra. Herbicide applications were recorded per TOS. This dataset enables comprehensive analysis of genotype × environment × management interactions, particularly for traits associated with early vigour, drought adaptation, and disease resistance in wheat.

This dataset comprises detailed agronomic data from three coordinated field experiments conducted at Beelbangera, NSW. The trials investigate the effects of genotype, sowing depth, fertiliser placement and rate, and seed size on wheat establishment and yield performance. The Excel workbook contains 14 sheets, which include trial details, site maps, treatment layouts, packet plans, raw plot-level data, processed metrics, and harvest index calculations. The data is structured with consistent identifiers such as run number, genotype, sowing depth, fertiliser treatment, and seed size category. Raw data entries include grain yield per plot, sowing depth, genotype, fertiliser rate, and plot dimensions, enabling calculation of yield per hectare. Additional sheets provide derived metrics such as grain count, canopy cover, SAVI (Soil Adjusted Vegetation Index), and harvest index. Data was collected using standard field trial methodologies. Sowing was performed on 29 April 2024 using a Morris seeder at two depths: shallow (4 cm) and deep (12–14 cm). Fertiliser was applied either with the seed or above the seed, at safe (80 kg/ha MAP) and unsafe (160 kg/ha MAP) rates. Trials were replicated three times with consistent plot sizes (12 m × 1.75 m) and row spacing (25 cm × 7 rows). Environmental conditions were monitored, including rainfall (362.5 mm total, 246 mm in the growing season), and soil tests were conducted pre-sowing (pH 6.2, total N 57 kg/ha, Colwell P 38 ppm). Herbicide and fertiliser applications were logged with dates and rates. The dataset includes over 100 variables. Key fields include genotype (e.g., Calibre, Mace18, Magenta13), sowing depth, fertiliser rate and placement, seed size (e.g., small, medium, large), grain yield, biomass, spike count, and vegetation indices. Codes such as “SS” and “DS” denote sowing depth, while “Std”, “Lge”, “Sml”, “Med”, and “Vlge” refer to seed size categories. Fertiliser treatments are coded as “Cont”, “Withseed”, and “Aboveseed”. The dataset also includes image references for visual assessments and positional metadata for canopy measurements.

This dataset originates from the 2024 long coleoptile wheat trial conducted at Dookie College, Victoria, Australia. The trial investigates the interactions between wheat genotype, sowing depth, and presswheel pressure (as a proxy for soil strength) on early crop establishment and development. The core experimental design is a factorial combination of six wheat genotypes (Scepter, Calibre, Mace, Mace18, Magenta, Magenta13), two sowing depths (shallow: 30–40 mm; deep: 80–100 mm), and three presswheel pressures (light, standard, heavy), resulting in 36 treatment combinations replicated across multiple blocks. The dataset is structured across multiple Excel file (.xlsx) sheets, each representing different aspects of the trial, including experimental design, field maps, seed characteristics, soil measurements, and emergence data. Key files include treatment layouts, seed packing details, soil strength and moisture data at various depths and time points (pre-sowing, 0 days after sowing, and 12 days after sowing), temperature logger data, and detailed emergence counts over time. Soil strength was measured using a Geotester penetrometer, while gravimetric moisture and matric potential were assessed through laboratory analysis of soil cores taken at specified depths. Temperature sensors recorded hourly data at 0, 3–4, and 8–10 cm depths in selected plots. Seed characteristics such as thousand seed weight, seed size grading, and germination/vigour assessments were recorded for each genotype. The emergence data includes counts from two seeding rows per plot, tracked over multiple dates post-sowing, allowing for analysis of emergence dynamics. The dataset supports investigations into how genotype and agronomic practices influence wheat establishment under varying soil mechanical resistance and moisture conditions. All data is labelled with consistent identifiers for plot, treatment, genotype, depth, and pressure, facilitating integration across sheets. This comprehensive dataset enables robust analysis of genotype by environment by management interactions relevant to improving wheat establishment under challenging sowing conditions.

국립식량과학원에서 매년 개발되는 품종에 대해 지역별 적응성을 알아보기 위한 품종별 지역별 지적시험성적을 제공함

,Correlations between plant available soil and grain mineral concentrations are often assumed, yet few studies examine these associations. Here, soil and wheat grain samples were analyzed from a semi-arid dryland cropping study in the northern Great Plains conducted between 2006 and 2011. Continuous spring wheat (fertilized) (Triticum aestivum L; CSW) was compared with wheat following 5 yr of perennial forages of either alfalfa (Medicago sativa L.), intermediate wheatgrass (fertilized) (Thinopyrum intermedium (Host) Barkw. & D.R. Dewey sbsp. Intermedium; IWG), or an alfalfa/intermediate wheatgrass mixture (fertilized; MIX). Wheat performance (yield, 1,000 kernel weight [TKW], and crude protein [CP] concentration), and associations between 11 plant available soil mineral concentrations and 11 wheat grain mineral concentrations were assessed. Wheat following alfalfa had greater yield than all treatments, greater TKW than CSW, greater CP than IWG and CSW, but lower grain Zn concentration than IWG (p ≤ .05). Wheat grain following IWG had greater Fe and Mn concentration than MIX, greater Mg concentration than CSW, and lower S concentration than all treatments (p < .05). Multivariate correlation analysis showed positive correlations between plant available soil and grain B, Mg, Mn, and S concentrations (p ≤ .02), while plant available soil and grain Zn and Ca concentrations showed negative associations (p ≤ .05). Rotating perennial forage phases into wheat cropping systems increased wheat yield and CP but reduced certain plant available soil minerals. Although rotating perennials into annual cropping systems can benefit some soil quality parameters it may also diminish plant available soil minerals, influencing fertility recommendations.,