Papers by Robert J. Lascano
Texas Journal of Agriculture and Natural Resources, May 4, 2016
The development and application of cropping system simulation models for cotton production has a ... more The development and application of cropping system simulation models for cotton production has a long and rich history, beginning in the southeastern U. S. in the 1960s and now expanded to major cotton production regions globally. This paper briefly reviews the history of cotton simulation models, examines applications of the models since the turn of the century, and identifies opportunities for improving models and their use in cotton research and decision support. Cotton models reviewed include those specific to cotton (GOSSYM, Cotton2K, COTCO2, OZCOT, and CROPGRO-Cotton) and generic crop models that have been applied to cotton production (EPIC, WOFOST, SUCROS, GRAMI, CropSyst, and AquaCrop). Model application areas included crop water use and irrigation water management, nitrogen dynamics and fertilizer management, genetics and crop improvement, climatology, global climate change, precision agriculture, model integration with sensor data, economics, and classroom instruction. Generally, the literature demonstrated increased emphasis on cotton model development in the previous century C otton (Gossypium hirsutum L. and Gossypium barbadense L.) is an important commodity crop globally, providing sources of fiber, feed, food, and potentially fuel for diverse industries. Cotton fiber is used in products ranging from textiles to paper, coffee filters, and fishing nets. Cottonseed meal and hulls are used mainly for ruminant livestock feed. Cottonseed oil is Programming Language Time Step Key References Decision Support Tools GOSSYM SIMCOTI SIMCOTII Fortran Daily Baker et al. (1983) Reddy et al. (2002b) COMAX Cotton2K GOSSYM CALGOS C++, formerly Fortran Hourly Marani (2004) None COTCO2 KUTUN ALFALFA Fortran Hourly Wall et al. (1994) None OZCOT SIRATAC C#, formerly Fortran Daily Hearn and Da Roza (1985) Hearn (1994) APSIM CottBASE HydroLOGIC VARIwise Whopper Cropper CSM-CROPGRO-Cotton CROPGRO-Soybean Fortran Daily Hoogenboom et al. (1992) Jones et al. (2003) DSSAT GOSSYM Cotton2K COTCO2 OZCOT CROPGRO-Cotton Phenology Develops vegetative and fruiting branches and nodes based on thermal time Calculates the number of branches, squares, bolls, open bolls, fruiting sites, and aborted fruits Develops vegetative and fruiting branches and nodes based on thermal time Calculates the number of branches, squares, bolls, open bolls, fruiting sites, and aborted fruits Develops meristem tissue, leaf primordia, petioles, growing and mature leaves, stem segments between nodes, squares, bolls, and open bolls based on thermal time Develops the number of fruiting sites based on thermal time Calculates the number of squares, bolls, open bolls, and aborted fruits based on crop carrying capacity Development proceeds through growth stages based on photothermal time: emergence, first leaf, first flower, first seed, first cracked boll, and 90% open boll. Calculates boll number and aborted fruits Plant maps Yes Yes Yes No No Potential carbon assimilation Canopy-level radiation interception Canopy-level radiation interception Organ-level biochemistry (Farquhar et al., 1980) Canopy-level radiation interception Leaf-level biochemistry (Farquhar et al., 1980) Respiration Uses an empirical function of respiration based on biomass and air temperature Calculates growth and maintenance respiration and photorespiration Calculates organlevel growth and maintenance respiration and photorespiration Uses empirical functions of respiration based on fruiting site count and air temperature Calculates growth and maintenance respiration Partitioning Allocates carbon to individual growing organs Allocates carbon to individual growing organs Allocates carbon to individual growing organs Allocates carbon to cohort pools for developing bolls Allocates carbon to single pools for leaves, stems, roots, and bolls Canopy size Calculates plant height Calculates plant height Calculates stem segment lengths None Calculates hedgerowbased canopy height and width Yield components Calculates fiber mass as a fraction of boll mass and boll size Calculates burr mass and seed cotton mass Calculates boll mass Calculates fiber mass as a fraction of boll mass and boll size Calculates boll mass, seed cotton mass, seed number, and unit seed weight Stress Calculates stress due to water, nitrogen, and air temperature Calculates stress due to water, nitrogen, and air temperature Calculates stress due to water and air temperature Calculates stress due to water, nitrogen, and air temperature Calculates stress due to water, nitrogen, and air temperature Table 3. Atmospheric and soil processes simulated by existing cotton simulation models. GOSSYM Cotton2K COTCO2 OZCOT CROPGRO-Cotton [CO2] effect on photosynthesis Yes Yes Yes No Yes [CO2] effect on transpiration No No Yes No Yes ET Ritchie (1972) Modified Penman equation from CA Irrigation Management Information System Leaf-level energy balance coupled with stomatal conductance Richie (1972) Priestley and Taylor (1972) and FAO-56 (Allen et al., 1998)
Journal of Economic Entomology, Aug 1, 2003
Helicoverpa zea (Boddie) is an important pest of cotton, Gossypium hirsutum L., for which many ec... more Helicoverpa zea (Boddie) is an important pest of cotton, Gossypium hirsutum L., for which many economic injury and population models have been developed to predict the impact of injury by this species on cotton yield. A number of these models were developed using results from simulated damage experiments, despite the fact that no studies have demonstrated that simulated damage is comparable to real H. zea damage. Our main objective in this study was to compare the effect on yield of H. zea larvae feeding on cotton fruiting structures at different irrigation levels, larval densities, and cotton physiological ages with damage produced artiÞcially by removing fruiting structures by hand using simulated estimates of H. zea injury. To accomplish this, we used two irrigation levels, each divided into real and simulated damage plots. In real damage plots, H. zea larvae were placed on plants and allowed to feed; whereas in simulated damage plots, fruiting structures were removed by hand using a simulation model of H. zea damage to determine numbers and amounts of fruiting structures to remove. Each of these plots was further divided into one undamaged control plot and nine treatment plots. Each treatment plot was randomly assigned one of three damage times (early, middle, or late season) and one of three H. zea densities. In 1998, we found that only artiÞcial H. zea damage (performed by hand removal of fruiting structures) at the highest density and during the late season decreased yield; whereas real damage caused by H. zea larvae placed on plants, and artiÞcial damage occurring at earlier time periods and lower H. zea densities did not affect yield. In 1999, both real and artiÞcial damage decreased yield at the higher H. zea densities compared with the lowest density, but, as in 1998, this was only true when damage occurred late in the season. The most important Þnding of this study was that high H. zea densities had no effect on cotton yield unless they occurred late in the season. In particular, this was true for artiÞcial H. zea damage. The second most important Þnding of this study was that, with the exception of late in the season, our model for simulating H. zea damage to cotton through removal of fruiting structures resulted in similar yields as real H. zea larvae damage to cotton.
Agricultural and Forest Meteorology, Jun 1, 2022
Agronomy Journal, Mar 1, 2012
Agronomy Journal, May 1, 2014
All rights reserved. No part of this periodical may be reproduced or transmitted in any form or b... more 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.
Plant Biosystems, Oct 26, 2012
ABSTRACT Canopy temperature (Tc) provides an easy-to-acquire indication of crop water deficit tha... more ABSTRACT Canopy temperature (Tc) provides an easy-to-acquire indication of crop water deficit that has been used in irrigation scheduling systems, but interpretation of this measurement has proven difficult. We compared the timing of irrigation application of the Stress Time (ST) method of irrigation scheduling with the Stress Degree Hours (SDH) method on deficit irrigated cotton (Gossypium hirsutum L.) where each irrigation event delivered 5 mm of water through subsurface drip tape. A well-watered (WW) control and a dry land (DL) treatment were also part of the experimental design. We used data collected from the WW and DL treatments to develop upper and lower baselines for the Crop Water Stress Index (CWSI) appropriate for cotton grown at our location. The ST method detected drought stress earlier in the growing season when both the SDH and CWSI indicated very little drought stress. The SDH method resulted in the application of irrigations relatively later in the growing season when the CWSI also detected higher levels of drought stress. These results suggest that the adding certain micrometeorological variables to simple Tc methods of deficit irrigation scheduling may improve the ability to detect and quantify the degree of crop drought stress.
Vadose Zone Journal, Nov 1, 2003
to measure these changes. The TDR method, for example, is based on the determination of the chang... more to measure these changes. The TDR method, for example, is based on the determination of the changes in Development of management strategies for efficient water utilizathe velocity of an electromagnetic pulse sent through a tion of crop production requires measurements of changes in soil water content on a dynamic basis. Many of the methods currently probe (wave-guide) inserted into the soil. Differences used for measuring these changes are destructive, slow, or relatively in time required for the pulse to traverse the length of expensive for large-scale investigations. A commercially available, the wave-guide and return depend on the soil dielectric low-cost, nondestructive soil moisture sensor for measuring changes constant and consequently on the soil VWC. in soil volumetric water content (VWC) on the basis of changes in Another technique that depends on the changes in the dielectric constant of the soil water was evaluated under laboratory the soil dielectric constant to measure water content conditions for two soil series (Amarillo fine sandy loam [fine-loamy, is the capacitance method. Here a capacitor (probe) is mixed, superactive, thermic Aridic Paleustalfs] and Pullman clay loam subjected to a specific voltage and the charge time is [fine, mixed, thermic Torretic Paleustolls]) and a potting material measured. The charge time is a function of the capaciacross a wide range of water contents. Probes were placed in containtance of the probe, which is directly related to the dielecers filled with deionized water and soil. Containers with Amarillo fine sandy loam were placed in a programmable temperature chamber tric constant of the medium (soil). and subjected to a series of changes in both temperature and VWC. Both TDR and capacitance methods depend on Containers with Pullman soil and potting material were only subjected changes in the soil dielectric constant to measure soil to changes in VWC at a constant temperature. Probe output at a VWC. Therefore, ease of use, and other factors affecting constant temperature between air dry and a VWC of 0.25 m 3 m Ϫ3 was the output of the instruments (e.g., temperature, salinlinear for the Pullman soil and potting material and nonlinear for the ity) become considerations in the choice of methods Amarillo soil. When the Amarillo soil temperature varied between (Wraith and Or, 1999; Or and Wraith, 1999; Baumhardt 15.9 and 39.1؇C Ϫ1 at a constant VWC, probe output changed the et al., 2000). equivalent of 0.10 m 3 m Ϫ3. The temperature sensitivity was 0.5 mV A low-cost capacitance probe is currently being man-؇C Ϫ1 for air-dry and about 5 mV ؇C Ϫ1 for wet Amarillo soil. We ufactured and is commercially available for use in a conclude that probe output is soil specific and, given the nonlinear response to increasing water content on some soils and sensitivity to wide range of soil types. The objective of this study was temperature, will require soil-specific calibration equations. to evaluate the effect of changes in water contents for two soil series and a potting material on the output and sensitivity of these probes under controlled laboratory conditions. In our study we did not compare the capaci
Agricultural Water Management
Frontiers in Sustainable Food Systems, 2021
In the Texas High Plains (THP), diminishing irrigation well-capacities, and increasing costs of e... more In the Texas High Plains (THP), diminishing irrigation well-capacities, and increasing costs of energy and equipment associated with groundwater extraction and application are contributing factors to a transition from irrigated to dryland agriculture. The primary goal of this modeling exercise was to investigate whether and to what extent hypothetical changes in factors putatively associated with soil health would affect dryland cotton (Gossypium hirsutum L.) yields. The factors selected were drainage, surface runoff, soil water holding capacity, soil organic carbon (SOC) and albedo. As a first analysis to evaluate these factors, we used the CROPGRO-Cotton module within the Decision Support System for Agrotechnology Transfer (DSSAT) cropping system model. Specifically, we evaluated the effects of reduced surface runoff, increased soil water holding capacity, and SOC, doubling of the soil albedo through stubble mulching, and of soil drainage by enhancing infiltration with no-tillage/...
Declines in Ogallala aquifer levels used for irrigation has prompted research to identify methods... more Declines in Ogallala aquifer levels used for irrigation has prompted research to identify methods for optimizing water use efficiency (WUE) of cotton (Gossypium hirsutum L). In this experiment, conducted at Lubbock, TX, USA in 2014, our objective was to test two canopy temperature based stress indices, each at two different irrigation trigger set points: the Stress Time (ST) method with irrigation triggers set at 5.5 (ST_5.5) and 8.5 h (ST_8.5) and the Crop Water Stress Index (CWSI) method with irrigation triggers set at 0.3 (CWSI_0.3) and 0.6 (CWSI_0.6). When these irrigation triggers were exceeded on a given day, the crop was deficit irrigated with 5 mm of water via subsurface drip tape. Also included in the experimental design were a well-watered (WW) control irrigated at 110% of potential evapotranspiration and a dry land (DL) treatment that relied on rainfall only. Seasonal crop water use ranged from 353 to 625 mm across these six treatments. As expected, cotton lint yield increased with increasing crop water use but lint yield WUE displayed asignificant (p ≤ 0.05) peak near 3.6 to 3.7 kg ha −1 mm −1 for the ST_5.5 and CWSI_0.3 treatments, respectively. Our results suggest that WUE may be optimized in cotton with less water than that needed for maximum lint yield.
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Papers by Robert J. Lascano