Modeling 556 Agronomy Journal  Volume 101, Issue 3  2009 Published in Agron. J. 101:556–563 (2009). doi:10.2134/agronj2008.0137x Copyright © 2009 by the American Society of Agronomy, 677 South Segoe Road, Madison, WI 53711. All rights reserved. No part of this periodical may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. O ne of the most important human endeavors is to increase crop yields over time. Careful investigation of the determinants of past wheat yields provides crucial infor- mation about how to maximize future yields. Agronomists developed the PTQ to summarize the impact of weather on crop yields (Nix, 1976). Te PTQ for wheat is defned by Nix (1976) as the quotient of Solar to Temp minus 4.5°C for a given time period around anthesis. Tis base temperature is based on Fischer (1985), who states that 4.5°C is the base tempera- ture for wheat growth. Tus, the PTQ summarizes a large volume of weather data into a single measure. While PTQ has been used widely in the agronomy literature, few articles have analyzed the efects of varying the time interval which defnes PTQ. For wheat, GM −2 is the yield component most correlated with yield variation (Midmore et al., 1984; Slafer and Andrade, 1993; Demotes-Mainard and Jeufroy, 2001). Potential wheat yield can be disaggregated into two main components: GM −2 and individual weight kernel −1 . Te GM −2 is largely determined by the events that occur in the few weeks preceding anthesis, whereas individual weight kernel −1 is attributable to events afer anthesis (Ortiz-Monasterio et al., 1994). With enough water and nutrients, the two components of yield are largely determined by the amount of solar radia- tion received and the mean temperature. Nix (1976) asserted that Solar and Temp infuence plant growth and development diferently, their combined efects on yield can be described conveniently as PTQ. Using wheat test plot data from northwest Mexico, Fischer (1985) observed that GM −2 is associated with PTQ prevailing over the 30 d preceding 50% anthesis, described as 10.51 on the Feekes (1941) growth stage scale, and 65 on the Zadoks et al. (1974) growth stage scale. Fischer (1985) stated that earlier growing conditions were not as infuential on GM −2 because, under irrigation and optimum fertility, sufcient yield poten- tial (in terms of tillers, spiklets, and forets) and photosynthetic capacity were almost always reached before this point. Tis has been confrmed in other research in England by Torne and Wood (1987); and in Argentina by Savin and Slafer (1991) and Margin et al. (1993). Teoretically, the higher the value of PTQ observed, the higher the potential yield. High solar radiation around anthesis results in increased photosynthesis, which is advanta- geous for yield. Conversely, a high temperature around the same period has negative impacts on yield, as it shortens the duration of the spike growth period. Dawson and Wardlaw (1989) found that high temperatures (above 30°C) during the ABSTRACT Previous research has demonstrated the importance and statistical signifcance of the photothermal quotient (PTQ) to predict and explain wheat ( Triticum aestivum L.) yields. Te objective of this study is to respecify PTQ to enhance the explanatory power of statistical models used to explain grains per square meter (GM -2 ), and increase understanding of weather’s impact on yields. Te primary objective is to identify and quantify potential gains from including separate components of solar radiation (Solar) and temperature (Temp) in place of PTQ (Solar/Temp) to improve wheat yield model explanatory ability. Te study also determines the optimal time interval that defnes PTQ by varying the number of days before and afer 50% anthesis. Using wheat test plot data from Centro Internacional de Mejoramiento de Maíz y Trigo (CIMMYT) in Mexico’s Yaqui Valley, a multivariate regression- based stochastic model of wheat yields was used to estimate the impact of altering PTQ defnition and specifcation. Results sup- port previous research: the maximum F-test value of 66.02 and adjusted R 2 value of 0.446 were obtained for 31 d before to 1 d afer 50% anthesis. Interpretation and analysis were also enhanced by disaggregating PTQ into separate variables Solar and Temp. A 1 MJ m -2 d -1 increase in Solar increased GM -2 by 1.25%, whereas a 1°C increase in Temp decreased GM -2 by 2.8%. Tis difer- ence in yield responsiveness to weather components results in greater statistical signifcance, explanatory power, and interpreta- tion of GM -2 models. Future research that builds on these results will better explain, predict, and forecast crop yields. L.L. Nalley, Dep. of Agricultural Economics and Agribusiness, Univ. of Arkansas, Agricultural Building Room 217, Fayetteville, AR 72701; A.P. Barkley, Dep. of Agricultural Economics, Kansas State Univ., 217 Waters Hall, Manhattan, KS 66506; K. Sayre, CIMMYT, P.O. Box 6-641, Mexico D.F. 06600, Mexico. Received 15 Oct. 2008. *Corresponding author (llnalley@uark.edu). Abbreviations: BedsMinus, raised planting beds without fungicide application; BedsPlus, raised planting beds with fungicide application; Bread, bread wheat; CIMMYT, Centro Internacional de Mejoramiento de Maíz y Trigo; Durum, durum wheat; GM −2 , grains per square meter; Melgas, traditional planting technique in Mexico’s Yaqui Valley; Nets, raised planting beds with fungicide application and nets; PTQ, photothermal quotient; PTQ-D, disaggregated photothermal quotient; RLYR, the year a cultivar was released to the public; Solar, solar radiation exposure; Temp, average daily temperature; Triticale, Triticale wheat. Photothermal Quotient Specifications to Improve Wheat Cultivar Yield Component Models Lawton Lanier Nalley,* Andrew P. Barkley, and Ken Sayre Published May, 2009