From Neglecting to Including Cultivar-Specific Per Se Temperature Responses: Extending the Concept of Thermal Time in Field Crops (2024)

Table of Contents
Abstract References FAQs

Lukas Roth( From Neglecting to Including Cultivar-Specific Per Se Temperature Responses: Extending the Concept of Thermal Time in Field Crops (1) ),Martina Binder,Norbert Kirchgessner,Flavian Tschurr,Steven Yates,Andreas Hund,Lukas Kronenberg,,Achim Walter

Abstract

Predicting plant development, a longstanding goal in plant physiology, involves 2 interwoven components: continuous growth and the progression of growth stages (phenology). Current models for winter wheat and soybean assume species-level growth responses to temperature. We challenge this assumption, suggesting that cultivar-specific temperature responses substantially affect phenology. To investigate, we collected field-based growth and phenology data in winter wheat and soybean over multiple years. We used diverse models, from linear to neural networks, to assess growth responses to temperature at various trait and covariate levels. Cultivar-specific nonlinear models best explained phenology-related cultivar–environment interactions. With cultivar-specific models, additional relations to other stressors than temperature were found. The availability of the presented field phenotyping tools allows incorporating cultivar-specific temperature response functions in future plant physiology studies, which will deepen our understanding of key factors that influence plant development. Consequently, this work has implications for crop breeding and cultivation under adverse climatic conditions.

References

1

Ramirez-Villegas J, Watson J, Challinor AJ. Identifying traits for genotypic adaptation using crop models. J Exp Bot. 2015;66(12):3451–3462.

2

Pauli D, Chapman SC, Bart R, Topp CN, Lawrence-Dill CJ, Poland J, Gore MA. The quest for understanding phenotypic variation via integrated approaches in the field environment. Plant Physiol. 2016;172:662–634.

3

Tardieu F, Granato ISC, Van Oosterom EJ, Parent B, Hammer GL. Are crop and detailed physiological models equally ‘mechanistic’ for predicting the genetic variability of whole-plant behaviour? The nexus between mechanisms and adaptive strategies. In Silico Plants. 2020;2(1):diaa011.

4

White JW, Hoogenboom G, Kimball BA, Wall GW. Methodologies for simulating impacts of climate change on crop production. Field Crop Res. 2011;124(3):357–368.

5

Hammer G, Messina C, Wu A, Cooper M. Biological reality and parsimony in crop models—Why we need both in crop improvement! In Silico Plants. 2019;1(1):diz010.

6

Nagelmüller S, Kirchgessner N, Yates S, Hiltpold M, Walter A. Leaf length tracker: A novel approach to analyse leaf elongation close to the thermal limit of growth in the field. J Exp Bot. 2016;67(6):1897–1906.

7

Tschurr F, Kirchgessner N, Hund A, Kronenberg L, Anderegg J, Walter A, Roth L. Frost damage index: The antipode of growing degree days. Plant Phenomics. 2023;5:0104.

8

Steinberg RA, Garner WW. Response of certain plants to length of day and temperature under controlled conditions. J Agric Res. 1936;52(12):943–960.

9

Slafer GA. Differences in phasic development rate amongst wheat cultivars independent of responses to photoperiod and vernalization. A viewpoint of the intrinsic earliness hypothesis. J Agric Sci. 1996;126(4):403–419.

10

Bogard M, Ravel C, Paux E, Bordes J, Balfourier F, Chapman SC, Le Gouis J, Allard V. Predictions of heading date in bread wheat (Triticum Aestivum L.) using QTL-based parameters of an ecophysiological model. J Exp Bot. 2014;65(20):5849–5865.

11

Ochagavía H, Prieto P, Zikhali M, Griffiths S, Slafer GA. Earliness per se by temperature interaction on wheat development. Sci Rep. 2019;9(1):2584.

12

Bonhomme R. Bases and limits to using ‘degree.day’ units. Eur J Agron. 2000;13(1):1–10.

13

Parent B, Tardieu F. Temperature responses of developmental processes have not been affected by breeding in different ecological areas for 17 crop species. New Phytol. 2012;194:760–774.

14

Wang E, Martre P, Zhao Z, Ewert F, Maiorano A, Rötter RP, Kimball BA, Ottman MJ, Wall GW, White JW, et al. The uncertainty of crop yield projections is reduced by improved temperature response functions. Nat Plants. 2017;3:17102.

15

Kronenberg L, Yates S, Boer MP, Kirchgessner N, Walter A, Hund A. Temperature response of wheat affects final height and the timing of stem elongation under field conditions. J Exp Bot. 2021;72(2):700–717.

16

Roth L, Kronenberg L, Walter A, Aasen H, Hartung J, van Eeuwijk F, Piepho H-P, Hund A. High-throughput field phenotyping reveals that selection in breeding has affected the phenology and temperature response of wheat in the stem elongation phase. bioRxiv. 2022. https://www.biorxiv.org/content/10.1101/2022.09.05.506627.

17

Grieder C, Hund A, Walter A. Image based phenotyping during winter: A powerful tool to assess wheat genetic variation in growth response to temperature. Funct Plant Biol. 2015;42(2):387–396.

18

Roth L, Piepho H-P, Hund A. Phenomics data processing: Extracting dose-response curve parameters from high-resolution temperature courses and repeated field-based wheat height measurements. In Silico Plants. 2022;4:1, diac007.

19

Friedli M, Kirchgessner N, Grieder C, Liebisch F, Mannale M, Walter A. Terrestrial 3D laser scanning to track the increase in canopy height of both monocot and dicot crop species under field conditions. Plant Methods. 2016;12:9.

20

Roth L, Fossati D, Krähenbühl P, Walter A, Hund A. Image-based phenomic prediction can provide valuable decision support in wheat breeding. Theor Appl Genet. 2023;136(7):162.

21

Wallach D, Hwang C, Correll MJ, Jones JW, Boote K, Hoogenboom G, Gezan S, Bhakta M, Vallejos CE. A dynamic model with QTL covariables for predicting flowering time of common bean (Phaseolus vulgaris) Geno types. Eur J Agron. 2018;101:200–209.

22

Viswanathan M, Scheidegger A, Streck T, Gayler S, Weber TKD. Bayesian multi-level calibration of a process-based maize phenology model. Ecol Modell. 2022;474:110154.

23

White JW, Markus H, Hunt LA, Payne TS, Hoogenboom G. Simulation-based analysis of effects of Vrn and Ppd loci on flowering in wheat. Crop Sci. 2008;48(2):678–687.

24

Messina CD, Technow F, Tang T, Totir R, Gho C, Cooper M. Leveraging biological insight and environmental variation to improve phenotypic prediction: Integrating crop growth models (CGM) with whole genome prediction (WGP). Eur J Agron. 2018;100:151–162.

25

Mielewczik M, Friedli M, Kirchgessner N, Walter A. Diel leaf growth of soybean: A novel method to analyze two-dimensional leaf expansion in high temporal resolution based on a marker tracking approach (Martrack leaf). Plant Methods. 2013;9:30.

26

Kirchgessner N, Liebisch F, Yu K, Pfeifer J, Friedli M, Hund A, Walter A. The ETH field phenotyping platform FIP: A cable-suspended multi- sensor system. Funct Plant Biol. 2016;44(1):154–168.

27

Millet EJ, Kruijer W, Coupel-Ledru A, Prado SA, Cabrera-Bosquet L, Lacube S, Charcosset A, Welcker C, van Eeuwijk F, Tardieu F. Genomic prediction of maize yield across European environmental conditions. Nat Genet. 2019;51(6):952–956.

28

Sadras VO, Reynolds MP, de la Vega AJ, Petrie PR, Robinson R. Phenotypic plasticity of yield and phenology in wheat, sunflower and grapevine. Field Crop Res. 2009;110:242–250.

29

Salazar-Gutierrez MR, Johnson J, Chaves-Cordoba B, Hoogenboom G. Relationship of base temperature to development of winter wheat. Int J Plant Prod. 2013;7(4):741–762.

30

Slafer GA, Kantolic AG, ML, Tranquilli G, Miralles DJ, Savin R. Genetic and environmental effects on crop development determining adaptation and yield. In: Sadras VO, Calderini DF, editors Crop physiology. applications for genetic improvement and agronomy. London (UK): Elsevier.

31

McMaster GS, Wilhelm WW. Growing degree-days: One equation, two interpretations. Agric For Meteorol. 1997;87(4):291–300.

32

Pérez-Valencia DM, Rodríguez-Álvarez MX, Boer MP, Kronenberg L, Hund A, Bosquet LC, Millet EJ, van Eeuwijk FA. A two-stage approach for the Spatio-temporal analysis of high-throughput phenotyping data. Sci Rep. 2022;12:3177.

33

Roth L, Rodríguez-Álvarez MX, van Eeuwijk F, Piepho H-P, Hund A. Phenomics data processing: A plot-level model for repeated measurements to extract the timing of key stages and quantities at defined time points. Field Crop Res. 2021;274:108314.

34

Kronenberg L, Yu K, Walter A, Hund A. Monitoring the dynamics of wheat stem elongation: Genotypes differ at critical stages. Euphytica. 2017;213:157.

35

Roth L, Camenzind M, Aasen H, Kronenberg L, Barendregt C, Camp K-H, Walter A, Kirchgessner N, Hund A. Repeated multiview imaging for estimating seedling tiller counts of wheat genotypes using drones. Plant Phenomics. 2020;2020:3729715.

36

Roth L, Barendregt C, Bétrix C-A, Hund A, Walter A. High-throughput field phenotyping of soybean: Spotting an ideotype. Remote Sens Environ. 2022;269:112797.

37

Zenkl R, Timofte R, Kirchgessner N, Roth L, Hund A, Van Gool L, Walter A, Aasen H. Outdoor plant segmentation with deep learning for high-throughput field phenotyping on a diverse wheat dataset. Front Plant Sci. 2022;12:774068.

38

Lowe DG. Object Recognition from local scale-invariant features. In: Proceedings of the Seventh IEEE International Conference on Computer Vision. IEEE; 1999; p. 1150–1157.

39

Rublee E, Rabaud V, Konolige K, Bradski G. ORB: An efficient alternative to SIFT or SURF. In: Proceedings of the 2011 IEEE International Conference on Computer Vision. IEEE 2011; p. 2564–2571.

40

Fischler MA, Bolles RC. Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography. Graph Image Process. 1981;24(6):381–395.

41

Pauli V, Gommers R, Oliphant TE, Haberland M, Reddy T, Cournapeau D, Burovski E, Peterson P, Weckesser W, Bright J, et al. SciPy 1.0: Fundamental algorithms for scientific computing in python. Nat Methods. 2020;17:261–272.

42

Roth L, Streit B. Predicting cover crop biomass by lightweight UAS-based RGB and NIR photography: An applied photogrammetric approach. Precis Agric. 2018;19:93–114.

43

Pya N. scam: Shape Constrained Additive Models. R package version 1.2-5 2019.

44

Meier U. Growth Stages of Mono-and Dicotyledonous Plants: BBCH-Monograph. Germany: Open Agrar Repositorium; 2018.

45

Anderegg J, Yu K, Aasen H, Walter A, Liebisch F, Hund A. Spectral vegetation indices to track senescence dynamics in diverse wheat germplasm. Front Plant Sci. 2020;10:1749.

46

Baker CK, Gallagher JN. The development of winter wheat in the field 1. Relation between apical development and plant morphology within and between seasons. J Agric Sci. 1983;101(2):327–335.

47

Whigham DK, Minor HC. Agronomic characteristics and environmental stress. In: Soybean Physiology, Agronomy, and Utilization. New York, San Francisco, London: Academic Press; 1978.

48

Pinheiro JC, Bates DM. Mixed-effects models in S and S-PLUS. New York (NY): Springer-Verlag New York; 2000.

49

R Core Team. R: A language and environment for statistical computing. Vienna (Austria): R Foundation for Statistical Computing; 2019.

50

Durbán M, Harezlak J, Wand MP, Carroll RJ. Simple fitting of subject-specific curves for longitudinal data. Stat Med. 2005;24(8):1153–1167.

51

Butler D. asreml: Fits the Linear Mixed Model. R package version 4.1.0.93 (2018).

52

Piepho HP, Büchse A, Emrich K. A Hitchhiker’s guide to mixed models for randomized experiments. J Agron Crop Sci. 2003;189(5):310–322.

53

Tschurr F, Feigenwinter I, Fischer AM, Kotlarski S. Climate scenarios and agricultural indices: A case study for Switzerland. Atmosphere. 2020;11(5):535.

54

Porter JR, Gawith M. Temperatures and the growth and development of wheat a review. Eur J Agron. 1999;10:23–36.

55

Gallagher JN, Biscoe PV, Wallace JS. Field studies of cereal leaf growth: Ⅳ. Winter wheat leaf extension in relation to temperature and leaf water status. J Exp Bot. 1979;30(117):657–668.

56

Anderegg J, Aasen H, Perich G, Roth L, Walter A, Hund A. Temporal trends in canopy temperature and greenness are potential indicators of late-season drought avoidance and functional stay-green in wheat. Field Crop Res. 2021;274:108311.

57

McKee TB, Doesken NJ, Kleist J. The relationship of drought frequency and duration to time scales. In: Proceedings of the Eighth Conference on Applied Climatology; 1993, p. 179–184.

58

Vicente-Serrano SM, Beguería S, López-Moreno JI. A multiscalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index. J Clim. 2010;23(7):1696–1718.

59

Thronthwaite CW. An approach toward a rational classification of climate. Soil Sci. 1948;38(1):55–94.

60

Beguería S, Vicente-Serrano SM, Reig F, Latorre B. Standardized precipitation evapotranspiration index (SPEI) revisited: Parameter fitting, evapotranspiration models, tools, datasets and drought monitoring. Int J Climatol. 2014;34(10):3001–3023.

61

Friedman J, Hastie T, Tibshirani R, Narasimhan B. Package ‘glmnet’ type package title lasso and elastic-net regularized generalized linear models. 2022.

62

Kuhn M. Building predictive models in R using the caret package. J Stat Softw. 2008;28(5):1–26.

63

Shaykewich CF. An appraisal of cereal crop phenology modelling. Can J Plant Sci. 1995;75(2):329–341.

64

Wang E, Engel T. Simulation of phenological development of wheat crops. Agric Syst. 1998;58(1):1–24.

65

Parent B, Millet EJ, Tardieu F. The use of thermal time in plant studies has a sound theoretical basis provided that confounding effects are avoided. J Exp Bot. 2019;70(9):2359–2370.

66

Jamieson PD, Brooking IR, Porter JR, Wilson DR. Prediction of leaf appearance in wheat: A question of temperature. Field Crop Res. 1995;41(1):35–44.

67

Kronenberg L, Yates S, Ghiasi S, Roth L, Friedli M, Ruckle ME, Werner RA, Tschurr F, Binggeli M, Buchmann N, et al. Rethinking temperature effects on leaf growth, gene expression and metabolism: Diel variation matters. Plant Cell Environ. 2021;44(1):2262–2276.

68

Malosetti M, Visser RGF, Celis-Gamboa C, van Eeuwijk FA. QTL methodology for response curves on the basis of non-linear mixed models, with an illustration to senescence in potato. Theor Appl Genet. 2006;113(2):288–300.

69

Benaouda S, Dadshani S, Koua P, Léon J, Ballvora A. Identification of QTLs for wheat heading time across multiple-environments. Theor Appl Genet. 2022;135(8):2833–2848.

From Neglecting to Including Cultivar-Specific Per Se Temperature Responses: Extending the Concept of Thermal Time in Field Crops (2024)

FAQs

What is the ability of a plant to withstand the minimum temperature of an area? ›

A plant's hardiness determines its ability to withstand the average minimum temperature of a region without damage or death. Although winter hardiness is genetically determined, it is influenced by the duration of cool temperatures. Cool temperatures acclimate plants and prepare them for winter dormancy.

What causes temperatures to vary from region to region and time to time? ›

The temperature characteristics of a region are influenced by natural factors such as latitude, elevation and the presence of ocean currents.

How do plants respond to low temperatures? ›

Plants respond by increasing the proportion of saturated fatty acids in the membranes to improve heat resistance and prevent membrane fluidization. During cold stress, the low temperature causes the lipid bilayer to become more rigid, decreasing permeability.

How does temperature affect the ability of a plant to support life? ›

Temperature influences most plant processes, including photosynthesis, transpiration, respiration, germination and flowering. As temperature increases (up to a point), photosynthesis, transpiration and respiration increase.

What is the ability of a plant to withstand cold temperatures? ›

Hardiness of plants describes their ability to survive adverse growing conditions. It is usually limited to discussions of climatic adversity. Thus a plant's ability to tolerate cold, heat, drought, flooding, or wind are typically considered measurements of hardiness.

What is the ability of a plant to withstand low temperatures? ›

Freezing tolerance describes the ability of plants to withstand subzero temperatures through the formation of ice crystals in the xylem and intercellular space, or apoplast, of their cells.

What is the ability to withstand temperature? ›

Heat tolerance is the ability of a person to physiologically adjust to a heat stress exposure. About 4% of the population can be described as heat intolerant; that is they do not thermoregulate well enough to work under most conditions of heat stress (Wyndham et al., 1972).

What is the minimum temperature for plants? ›

Most houseplants are tropicals and prefer temperatures between 65-75°F during the day and about 10 degrees cooler at night. For many plants, temperatures below 50°F can cause problems.

Top Articles
Get The Latest Scoop: Mikayla Campinos' Age Revealed
Business Forms and Information | BECU
How To Fix Epson Printer Error Code 0x9e
Yogabella Babysitter
Hertz Car Rental Partnership | Uber
5 Bijwerkingen van zwemmen in een zwembad met te veel chloor - Bereik uw gezondheidsdoelen met praktische hulpmiddelen voor eten en fitness, deskundige bronnen en een betrokken gemeenschap.
Select The Best Reagents For The Reaction Below.
A.e.a.o.n.m.s
Jessica Renee Johnson Update 2023
Unit 1 Lesson 5 Practice Problems Answer Key
Sams Early Hours
Dutchess Cleaners Boardman Ohio
Cinebarre Drink Menu
Aberration Surface Entrances
Craiglist Kpr
Who called you from +19192464227 (9192464227): 5 reviews
Tygodnik Polityka - Polityka.pl
Lcwc 911 Live Incident List Live Status
50 Shades Of Grey Movie 123Movies
Ge-Tracker Bond
Amazing deals for Abercrombie & Fitch Co. on Goodshop!
Georgetown 10 Day Weather
Selfservice Bright Lending
The Largest Banks - ​​How to Transfer Money With Only Card Number and CVV (2024)
Where to eat: the 50 best restaurants in Freiburg im Breisgau
Xfinity Outage Map Fredericksburg Va
Talk To Me Showtimes Near Marcus Valley Grand Cinema
Integer Division Matlab
How To Find Free Stuff On Craigslist San Diego | Tips, Popular Items, Safety Precautions | RoamBliss
Craigslist Ludington Michigan
Kitchen Exhaust Cleaning Companies Clearwater
Turns As A Jetliner Crossword Clue
Yu-Gi-Oh Card Database
Current Students - Pace University Online
Busch Gardens Wait Times
91 Octane Gas Prices Near Me
Ugly Daughter From Grown Ups
Have you seen this child? Caroline Victoria Teague
Nextdoor Myvidster
What Happened To Father Anthony Mary Ewtn
Kstate Qualtrics
Retire Early Wsbtv.com Free Book
Mandy Rose - WWE News, Rumors, & Updates
craigslist | michigan
Www Usps Com Passport Scheduler
Craigslist en Santa Cruz, California: Tu Guía Definitiva para Comprar, Vender e Intercambiar - First Republic Craigslist
Sour OG is a chill recreational strain -- just have healthy snacks nearby (cannabis review)
Stosh's Kolaches Photos
antelope valley for sale "lancaster ca" - craigslist
Solving Quadratics All Methods Worksheet Answers
Puss In Boots: The Last Wish Showtimes Near Valdosta Cinemas
OSF OnCall Urgent Care treats minor illnesses and injuries
Latest Posts
Article information

Author: Mr. See Jast

Last Updated:

Views: 6535

Rating: 4.4 / 5 (55 voted)

Reviews: 94% of readers found this page helpful

Author information

Name: Mr. See Jast

Birthday: 1999-07-30

Address: 8409 Megan Mountain, New Mathew, MT 44997-8193

Phone: +5023589614038

Job: Chief Executive

Hobby: Leather crafting, Flag Football, Candle making, Flying, Poi, Gunsmithing, Swimming

Introduction: My name is Mr. See Jast, I am a open, jolly, gorgeous, courageous, inexpensive, friendly, homely person who loves writing and wants to share my knowledge and understanding with you.