Row spacing effects on the canopy light extinction coefficient of upland cotton

Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to [email protected], referencing the URI of the item.Includes bibliographical references (leaves 102-107).Issued also on microfiche from Lange Micrographics.Field experiments were conducted in 1998 and 1999 at the Stiles Farm, Thrall, Texas and the Blackland Research Center, Temple, Texas, respectively, to characterize the influence of row spacing, plant density and time of day on the extinction coefficient (k) in cotton (Gossypium hirsutum). Treatments consisted of four row spacings (0.19-m, 0.38-m, 0.76-m, and 1.00-m) and four plant densities [148, 222, 296, 445 (1998) and 371 (1999) thousand plants ha-1] with each treatment replicated three times. Experimental design was a split-plot randomized complete block design. Main plots were row spacings, and subplots were plant densities. Light interception measurements were taken on square meter areas approximately two weeks apart beginning at pinhead square at 0900h, 1030h and 1230h. Above-canopy-incoming, above-canopy-reflected and below-canopy-transmitted photosynthetically active radiation were measured on each date and time. Leaf area index, plant height and main stem node number (1999) were also recorded for each area measured. Plant density had no influence on leaf area indices, plant height, main stem node number, or k during both years. Time of day showed to significantly influence the extinction coefficient. Light extinction coefficient values were lowest at solar noon, suggesting that daily light interception based solely on solar noon values may underestimate the total daily light interception of a canopy. Results from 1998 indicated that the ultra-narrow row spacings (0.19-m) had greater leaf area indices throughout the season. In 1999 the ultra-narrow row spacings (0.19-m) accumulated LAI faster than the wide rows (>0.76-m), but as the season progressed the wide rows surpassed the narrow rows due to interplant competition in the narrow rows. Row spacing had no effect on the number of main stem nodes per plant. Row spacing had a significant influence on k during both years. In 1998 the extinction coefficient increased slightly as the row spacing increased, contradictory to previously published material. However, in 1999, similar to other estimations of k for cotton, the extinction coefficient increased as row spacing decreased

Row spacing effects on the canopy light extinction coefficient of upland cotton

Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to [email protected], referencing the URI of the item.Includes bibliographical references (leaves 102-107).Issued also on microfiche from Lange Micrographics.Field experiments were conducted in 1998 and 1999 at the Stiles Farm, Thrall, Texas and the Blackland Research Center, Temple, Texas, respectively, to characterize the influence of row spacing, plant density and time of day on the extinction coefficient (k) in cotton (Gossypium hirsutum). Treatments consisted of four row spacings (0.19-m, 0.38-m, 0.76-m, and 1.00-m) and four plant densities [148, 222, 296, 445 (1998) and 371 (1999) thousand plants ha-1] with each treatment replicated three times. Experimental design was a split-plot randomized complete block design. Main plots were row spacings, and subplots were plant densities. Light interception measurements were taken on square meter areas approximately two weeks apart beginning at pinhead square at 0900h, 1030h and 1230h. Above-canopy-incoming, above-canopy-reflected and below-canopy-transmitted photosynthetically active radiation were measured on each date and time. Leaf area index, plant height and main stem node number (1999) were also recorded for each area measured. Plant density had no influence on leaf area indices, plant height, main stem node number, or k during both years. Time of day showed to significantly influence the extinction coefficient. Light extinction coefficient values were lowest at solar noon, suggesting that daily light interception based solely on solar noon values may underestimate the total daily light interception of a canopy. Results from 1998 indicated that the ultra-narrow row spacings (0.19-m) had greater leaf area indices throughout the season. In 1999 the ultra-narrow row spacings (0.19-m) accumulated LAI faster than the wide rows (>0.76-m), but as the season progressed the wide rows surpassed the narrow rows due to interplant competition in the narrow rows. Row spacing had no effect on the number of main stem nodes per plant. Row spacing had a significant influence on k during both years. In 1998 the extinction coefficient increased slightly as the row spacing increased, contradictory to previously published material. However, in 1999, similar to other estimations of k for cotton, the extinction coefficient increased as row spacing decreased

Using EPIC model to manage irrigated cotton and maize

Simulation models are becoming of interest as a decision support system for management and assessment of crop water use and of crop production. The Environmental Policy Integrated Climate (EPIC) model was used to evaluate its application as a decision support tool for irrigation management of cotton and maize under South Texas conditions. Simulation of the model was performed to determine crop yield, crop water use, and the relationships between the yield and crop water use parameters such as crop evapotranspiration (ETc) and water use efficiency (WUE). We measured actual ETc using a weighing lysimeter and crop yields by field sampling, and then calibrated the model. The measured variables were compared with simulated variables using EPIC. Simulated ETc agreed with the lysimeter, in general, but some simulated ETc were biased compared with measured ETc. EPIC also simulated the variability in crop yields at different irrigation regimes. Furthermore, EPIC was used to simulate yield responses at various irrigation regimes with farm fields' data. Maize required ~700mm of water input and ~650mm of ETc to achieve a maximum yield of 8.5Mgha-1 while cotton required between 700 and 900mm of water input and between 650 and 750mm of ETc to achieve a maximum yield of 2.0-2.5Mgha-1. The simulation results demonstrate that the EPIC model can be used as a decision support tool for the crops under full and deficit irrigation conditions in South Texas. EPIC appears to be effective in making long-term and pre-season decisions for irrigation management of crops, while reference ET and phenologically based crop coefficients can be used for in-season irrigation management.Crop model EPIC Crop evapotranspiration Irrigation management

Drought-Induced Nitrogen and Phosphorus Carryover Nutrients in Corn/Soybean Rotations in the Upper Mississippi River Basin

Droughts reduce crop yields, which translates to reduced nutrient uptake or removal from the soil. Under such conditions, residual plant nutrients such as nitrogen (N) and phosphorus (P) can be carried over for subsequent crops. We applied the Agricultural Policy Environmental eXtender (APEX) model to simulate continuous corn (Zea mays L.)/soybean (Glycine max [L.] Merr.) rotations on 3703 farm fields within the Upper Mississippi River Basin (UMRB) over a 47-year timescale: 1960 to 2006. We used the Standardized Precipitation Index (PSI) to identify the drought years between 1960 to 2006, following which we evaluated potential drought-induced carryover N and P nutrients in corn/soybean rotations relative to near normal and very to extremely wet years. Overall, drought reduced N uptake, total N losses, N mineralization and N fixation, the main driver of the soybean carryover N. Given the high cost of fertilizers and concerns over nutrient loss impacts on offsite water quality, farmers are compelled to account for every plant nutrient that is already in the soil. Information from this study could be applied to develop optimal N and P recommendations after droughts, while identification of region-wide potential reductions in N and P applications has implications for conservation efforts aimed at minimizing environmental loading and associated water quality concerns

Drought-Induced Nitrogen and Phosphorus Carryover Nutrients in Corn/Soybean Rotations in the Upper Mississippi River Basin

Droughts reduce crop yields, which translates to reduced nutrient uptake or removal from the soil. Under such conditions, residual plant nutrients such as nitrogen (N) and phosphorus (P) can be carried over for subsequent crops. We applied the Agricultural Policy Environmental eXtender (APEX) model to simulate continuous corn (Zea mays L.)/soybean (Glycine max [L.] Merr.) rotations on 3703 farm fields within the Upper Mississippi River Basin (UMRB) over a 47-year timescale: 1960 to 2006. We used the Standardized Precipitation Index (PSI) to identify the drought years between 1960 to 2006, following which we evaluated potential drought-induced carryover N and P nutrients in corn/soybean rotations relative to near normal and very to extremely wet years. Overall, drought reduced N uptake, total N losses, N mineralization and N fixation, the main driver of the soybean carryover N. Given the high cost of fertilizers and concerns over nutrient loss impacts on offsite water quality, farmers are compelled to account for every plant nutrient that is already in the soil. Information from this study could be applied to develop optimal N and P recommendations after droughts, while identification of region-wide potential reductions in N and P applications has implications for conservation efforts aimed at minimizing environmental loading and associated water quality concerns

Soil carbon dynamics and crop productivity as influenced by climate change in a rainfed cereal system under contrasting tillage using EPIC

The issue of soil C sequestration is of special interest in Mediterranean areas, where, due to climatic conditions and agricultural practices, SOC (soil organic carbon) content is low, and is likely to be affected by climate change. Besides, losses of SOC have a relevant role in decreasing agricultural soil quality and could have a negative effect in productivity. Therefore, it is crucial to estimate whether modifying traditional soil management would have beneficial effects under future climate conditions. We used the EPIC model to simulate the interactive effect of climate change, CO2 enrichment, soil management (conventional tillage—CT vs. no tillage—NT) and two crop rotations, durum wheat–sunflower and durum wheat–maize, on crops yields and SOC in central Italy. The model was calibrated using soil and crop yield data collected from a long-term field experiment run in central Italy with CT and NT treatments. Maize and sunflower grain yields were significantly reduced by NT, primarily because of poor establishment, while durum wheat was almost not affected by tillage treatments. Projected durum wheat (Dw) and maize (Ma) grain yields were negatively affected by climate change (up to −25% and −10% respectively) while sunflower (Sf) yield increased. Tillage effects appear to be the most important factor in sequestering/releasing C. No-tillage practices sequestered in all profile (0–100 cm depth) from 0.03 to 0.2 t ha-1 y−1 in 30 years, depending on climate scenario and plant C input, while conventional tillage (CT) led to massive C loss rates (up to −0.9 t ha−1 y−1). Beyond all uncertainties in the use of models, the results demonstrated that soil tillage and, to a certain extent, crop rotation, can play a relevant role in reducing (NT) or reinforcing (CT) the impact of climate change on SOC. No-tillage farming, if sufficient C input is ensured by the cropping system, could effectively contribute to increase soil C sequestration in Mediterranean rainfed environments

Applicazioni del modello APEX per la simulazione dei sistemi colturali della collina centro italiana

I modelli matematici di simulazione opportunamente calibrati e validati, possono rappresentare strumenti utili per la pianificazione e la gestione dei sistemi colturali rispetto alla più dispendiosa sperimentazione di campo (Yu et al., 2006) che comunque è imprescindibile per una corretta interpretazione delle simulazioni (Bouma et al., 2008). Il modello Agricultural Policy/environmental EXtender (APEX) è stato sviluppato per applicazioni a scala di microbacino (Williams and Izaurralde, 2006). APEX estende le capacità di EPIC (Environmental Policy Integrated Climate model) (Williams et al., 1989) su più ampia scala offrendo la possibilità di suddividere il microbacino in subaree omogenee dal punto di vista pedoclimatico e di utilizzo del suolo così da simularne il deflusso superficiale e sottosuperficiale, il trasporto di nutrienti, del sedimento e dei pesticidi dalle subaree all’outlet di bacino. Principalmente APEX è stato impiegato per la gestione dei reflui zootecnici al fine di preservare la qualità delle risorse idriche in Texas (Flowers et al., 1996) e per modellizzare l’impatto della gestione del suolo sul deflusso superficiale, l’erosione del suolo, la produttività delle colture e la dinamica del carbonio nel suolo (Wang et al., 2008). Il presente lavoro rientra in un progetto di ricerca finanziato dal Ministero delle Politiche Agricole Alimentari e Forestali - MiPAAF dal titolo: "Scenari di adattamento dell'agricoltura italiana ai cambiamenti climatici (AGROSCENARI)". Il progetto mira ad individuare, valutandone la sostenibilità, le modalità di adattamento ai cambiamenti climatici dei principali sistemi produttivi agricoli italiani per valutare l’effetto di differenti scenari climatici sulla produttività e l’impatto ambientale dei sistemi colturali. In particolare la ricerca descritta si pone l’obiettivo di valutare la capacità di APEX di simulare i sistemi colturali cerealicolo-industriali centro italiani al fine di identificare strategie gestionali che consentano di ridurne l’impatto ambientale anche in relazione ad ipotetici scenari di cambiamento climatico

APEX model applications for the mediterranean cropping systems simulation

The Agricultural Policy/Environmental eXtender model (APEX) extends the EPIC (Environmental Policy Integrated Climate model) capabilities for applications at the microcatchment scale. The research described aims to calibrate APEX to simulate industrial-cereal cropping systems in order to identify management strategies capable of reducing the environmental impact in relation to hypothetical scenarios of climate change and to develop mitigation strategies that allow for direct agricultural activities towards sustainable production. Good correlations between observed and simulated values were obtained for crop productivity as shown by the low Root Mean Square Error (RMSE) obtained. APEX provided valuable results on the runoff quantification, in particular for the higher levels. In the analyzed context APEX can be a useful tool for environmental planning and implementation of sustainable cropping systems