Try:droughtFusariumnitrogen fertilizerArabidopsisseed germination
Claim · model-written summary
Country and crop forecasting errors were comparable to group-level errors.
Not reportedTaxon
Verbatim
e0“the errors obtained are comparable to the ones obtained for the group.”
Title
Global Cropland Yield Monitoring with Gaussian Processes
Maria Piles; Anna Mateo-Sanchis; Jordi Munoz-Mari; et al. 2021 IEEE International Geoscience and Remote Sensing Symposium IGARSS 2021. doi:10.1109/igarss47720.2021.9554315
Claim · model-written summary
Additional errors were found, including errors affecting reported data and manuscript typographical errors.
Not reportedTaxon
Verbatim
e0“we found several others, some of which affect reported data and some of which are simple typographical errors introduced while preparing a manuscript”
Title
Hamish Symington; Joris Rockx Journal of Pollination Ecology 2025. doi:10.26786/1920-7603(2025)841
Claim · model-written summary
Detection errors included more commission errors in upper stems.
Pinus sylvestrist0Not reportedValue
Verbatim
e0“Error patterns revealed more commission errors in upper stem regions”
t0“Scots pine (Pinus sylvestris L.) trees”
Title
Stem crook detection in terrestrial laser scanning data using semi-empirical simulations
Raul de Paula Pires; Nils Lindgren; Henrik J Persson; et al. Forestry An International Journal of Forest Research 2026. doi:10.1093/forestry/cpag026
Claim · model-written summary
Segmentation misclassification and mosaicking errors contributed mainly to detection errors.
Verbatim
e0“Misclassifications of panicles during the semantic segmentation step and mosaicking errors in the field orthomosaic contributed mainly to panicle detection errors”
t0“Sorghum”
Title
A Deep Learning Semantic Segmentation-Based Approach for Field-Level Sorghum Panicle Counting
Lonesome Malambo; Sorin Popescu; Nian-Wei Ku; et al. Remote Sensing 2019. doi:10.3390/rs11242939
Claim · model-written summary
The dependency of errors on the response variable of interest can increase the probability of errors.
Not reportedTaxon
Verbatim
e0“The dependency of errors on the response variable of interest can influence the effect size and increase the probability of errors”
Title
Accuracy of image analysis tools for functional root traits: A comment on Delory et al. (2017)
Laura Rose; Guillaume Lobet Methods in Ecology and Evolution 2019. doi:10.1111/2041-210x.13156
Claim · model-written summary
Temperature data errors influenced both crop models significantly more than precipitation errors.
Verbatim
e0“errors in temperature data have a significantly stronger influence on both models than errors in precipitation”
t0“a process-based crop model and a statistical crop model”
Title
James Watson; Andrew J. Challinor; Thomas E. Fricker; et al. Climatic Change 2014. doi:10.1007/s10584-014-1264-3
Claim · model-written summary
Cross-validation prediction errors were similar to fitting errors.
Verbatim
e0“The root mean squared errors of prediction (RMSEPs) were similar to fitting errors”
Title
Estimating Genetic Coefficients for the CSM‐CERES‐Maize Model in North Carolina Environments
Zhengyu Yang; Gail G. Wilkerson; Gregory S. Buol; et al. Agronomy Journal 2009. doi:10.2134/agronj2008.0234x
Claim · model-written summary
Cross-validation errors were similar to errors from independent data.
Verbatim
e0“These errors were similar to those computed using independent data.”
Title
Evaluating Methods for Simulating Soybean Cultivar Responses Using Cross Validation
Ayse Irmak; James W. Jones; Theodoros Mavromatis; et al. Agronomy Journal 2000. doi:10.2134/agronj2000.9261140x
Claim · model-written summary
Thermal conductance estimation errors were similar in order to porometer measurement errors.
Verbatim
e0“The errors in thermal estimates of conductance were of the same order as the measurement errors using a porometer”
e1“measured gs data from a vineyard in Southern Portugal”
Title
Estimating stomatal conductance with thermal imagery
I. LEINONEN; O. M. GRANT; C. P. P. TAGLIAVIA; et al. Plant Cell & Environment 2006. doi:10.1111/j.1365-3040.2006.01528.x
Claim · model-written summary
Errors associated with NIRS estimations were often one-half as large as the experimental and sampling errors.
Verbatim
e0“Errors associated with NIRS estimations were often one‐half as large as the experimental and sampling errors”
Title
Estimation of Botanical Composition in Alfalfa/Ryegrass Mixtures by Near Infrared Spectroscopy
J. A. Shaffer; G. A. Jung; J. S. Shenk; et al. Agronomy Journal 1990. doi:10.2134/agronj1990.00021962008200040004x
Claim · model-written summary
Transplanting errors introduced among-hill variation.
Oryza sativat0Verbatim
e0“Transplanting errors introduced variation among hills”
t0“Rice”
Title
Spatial and Temporal Variability of Transplanted Rice at the Field Scale
Achim Dobermann; Mirasol F. Pampolino; Heinz‐Ulrich Neue Agronomy Journal 1995. doi:10.2134/agronj1995.00021962008700040018x
Claim · model-written summary
System parameters were identified to reduce application errors.
Not reportedComparatorValue
Verbatim
e0“A complement of system parameters was identified to reduce application errors.”
Title
A FEASIBILITY STUDY OF DIRECT INJECTION FOR VARIABLE-RATE HERBICIDE APPLICATION
W. Qiu; G. A. Watkins; C. J. Sobolik; et al. Transactions of the ASAE 1998. doi:10.13031/2013.17174
Claim · model-written summary
Prediction errors matched the magnitude of calculated probable errors.
Nicotiana tabacume1Verbatim
e0“Prediction errors were of the same magnitude as the calculated probable errors.”
e1“living tobacco plant”
Title
Temperature Predictions for Plant and Controlled-Resistance Artificial Leaves
John E. Morrison; Jr.; Billy J. Barfield Transactions of the ASAE 1981. doi:10.13031/2013.34421
Claim · model-written summary
Errors attributable to the model are of similar magnitude to conventional pasture yield measurement errors
Verbatim
e0“Errors attributable to the model are of a similar magnitude to those of conventional pasture yield measurements”
Title
Loss in monthly pasture production resulting from dryland conditions in the Waikato
K.J. McAneney; M.J. Judd; W.C. Weeda New Zealand Journal of Agricultural Research 1982. doi:10.1080/00288233.1982.10420904
Claim · model-written summary
The dewpoint method had theoretical errors.
Not reportedTaxon
Verbatim
e0“Theoretical errors in the dewpoint method of operation for these sensors were demonstrated.”
Title
Theoretical and Experimental Errors for In Situ Measurements of Plant Water Potential
Kenneth A. Shackel PLANT PHYSIOLOGY 1984. doi:10.1104/pp.75.3.766
Claim · model-written summary
The technique reduced seed displacement errors.
Not reportedTaxonComparatorValue
Verbatim
e0“It also reduced errors of seed displacement.”
Title
A Simple Technique for Seed Transfer in X-ray Analysis of Seed
B. S. P. Wang Canadian Journal of Forest Research 1974. doi:10.1139/x74-058
Claim · model-written summary
Leaf-length measurement errors caused larger plastochron-index errors at 10 mm than at 20 mm.
Verbatim
e0“the errors of measuring length cause larger errors of P.I. in the case of 10 mm than in 20 mm.”
t0“On the Expression of Plant Age of Soybean by Means of Plastochron Index”
Title
On the Expression of Plant Age of Soybean by Means of Plastochron Index
Kiichi HANADA; Suk Yong SON Japanese Journal of Crop Science 1974. doi:10.1626/jcs.43.8
Claim · model-written summary
Percentage errors for herbage components at or below 5% of the sample were unacceptably large.
Verbatim
e0“Percentage errors associated with herbage components constituting up to 5% of the sample, were unacceptably large.”
t0“pasture plots for herbage dissection”
Title
C.C. Boswell; C.B. Dyson; I.M. Ritchie; et al. Proceedings of the New Zealand Grassland Association 1976. doi:10.33584/jnzg.1976.38.1450
Claim · model-written summary
Observed error variance standard errors exceeded expected standard errors in both designs.
Verbatim
e0“Observed standard errors of the experimental error variances were larger than “expected standard errors” for both Designs.”
t0“Maize”
Title
Epistatic and Other Genetic Variances in Two Varieties of Maize1
S. A. Eberhart; R. H. Moll; H. F. Robinson; et al. Crop Science 1966. doi:10.2135/cropsci1966.0011183x000600030019x
Claim · model-written summary
Errors resulting from uneven grazing are compared with errors due to transference of fertility.
Trifolium repense1Verbatim
e0“a comparison is made with errors due to transference of fertility”
e1“white clover”
Title
REMOVAL OF THE EFFECTS OF UNEVEN GRAZING IN PASTURE EXPERIMENTS
Andrew L. Gardner; Gilberto A. Centeno Grass and Forage Science 1966. doi:10.1111/j.1365-2494.1966.tb00484.x
Claim · model-written summary
Leaf-material errors appeared similar to calibration errors.
Not reportedTaxon
Verbatim
e0“With leaf material the errors appear to be about the same, although release of cell sap at the cut edges of the disks may cause an overestimation by as much as 0.5 atm”
Title
A Vapour-pressure Instrument for the Measurement of Leaf and Soil Water Potential
A. E. S. MACKLON; P. E. WEATHERLEY Journal of Experimental Botany 1965. doi:10.1093/jxb/16.2.261
Claim · model-written summary
Standard errors of lesion counts depend on count magnitude.
Not reportedTaxonDirection
Verbatim
e0“the standard errors of x’s depend on their magnitude”
Title
A. KLECZKOWSKI Journal of General Microbiology 1955. doi:10.1099/00221287-13-1-91
Claim · model-written summary
Error mean squares and standard errors per pot increased with mean yields.
Verbatim
e0“Error mean squares and standard errors per pot increased with mean yields.”
e1“corn, small grains, and grasses”
Title
Variability in Results from Greenhouse Pot Experiments Comparing Phosphorus Rates and Sources1
G. L. Terman Agronomy Journal 1959. doi:10.2134/agronj1959.00021962005100020002x
Claim · model-written summary
Pin thickness caused large errors in percentage cover estimates for microphyllous heathland vegetation.
Verbatim
e0“Errors caused by the thickness of point quadrat pins are found to be large for the estimation of percentage cover in the microphyllous heathland vegetation”
Title
The use of point quadrats for the analysis of heathland
RE Winkworth Australian Journal of Botany 1955. doi:10.1071/bt9550068
Claim · model-written summary
Uneven wireworm distribution caused high sampling errors, accounting for most experimental error.
Not reportedTaxon
Verbatim
e0“The uneven distribution of the wireworms in the soil resulted in high sampling errors accounting for most of the experimental error.”
Title
FIELD EXPERIMENTS ON THE CONTROL OF WIREWORMS
W. R. S. LADELL; W. G. COCHRAN Annals of Applied Biology 1938. doi:10.1111/j.1744-7348.1938.tb02338.x
Claim · model-written summary
Sampling errors were even less important in estimating actual dry matter or nitrogen yields.
Verbatim
e0“The effect of sampling errors was of even less importance in the estimation of the actual yields of dry matter or of nitrogen.”
t0“pasture”
Title
M. S. Bartlett; A. W. Greenhill The Journal of Agricultural Science 1936. doi:10.1017/s0021859600021948
Claim · model-written summary
For strongly pathogenic strains, healthy seedling differences from control were 20 to 50 times probable errors.
Triticum aestivumt0Not reportedDirection
Verbatim
e0“The differences between the mean percentages of healthy seedlings of some strains and that of the control are 20 to 50 times of their probable errors”
t0“Wheat Seedlings”
Title
Y. NISIKADO; H. MATSUMOTO; K. YAMAUTI Japanese Journal of Phytopathology 1934. doi:10.3186/jjphytopath.4.1
Claim · model-written summary
The authors identify changes and errors in prior fern lists and make several additions.
Not reportedDirection
Verbatim
e0“we shall call attention chiefly to changes and errors, also making several additions to the above mentioned lists”
e1“species of Arkansas ferns, and can include more valuable notes on distribution”
Title
Notes on Arkansas Pteridophyta
John T. Buchholz American Fern Journal 1924. doi:10.2307/1544715
Claim · model-written summary
Indiscriminate sampling of citrus leaves may cause large errors.
Verbatim
e1“The great variation in sap concentration of citrus leaves brought about by direct sunlight”
e2“large errors may result through indiscriminate sampling”
Title
Effect of Sunlight on Sap Concentration of Citrus Leaves
F. F. Halma; A. R. C. Haas Botanical Gazette 1928. doi:10.1086/333876
Claim · model-written summary
Larger late-life-cycle fluctuations in maize unit leaf rate were attributed mainly to sampling errors.
Verbatim
e0“experiments on the growth of maize”
e1“The larger fluctuations which occur in the values for Unit Leaf Rate calculated for the later phases of the life‐cycle have been attributed mainly to sampling errors”
Title
A QUANTITATIVE ANALYSIS OF PLANT GROWTH: PART II.
G. E. BRIGGS; FRANKLIN KIDD; CYRIL WEST Annals of Applied Biology 1920. doi:10.1111/j.1744-7348.1920.tb05308.x
Lexical search (BM25). All words must match; if nothing does, any word. Organism names also match every spelling of the same organism. No semantic search yet.
Sorghum
Glycine max
Zea mays
Citrus