Determination of genetic Coefficients From Field Experiments For Ceres-Maize and Soygro Crop Growth Models

Lack of genetic coefficients is a reason crop models are not widely used. A project was therefore developed to evaluate a field method to calculate genetic coefficients for crop models. The phenology models fi-om SOYGRO v. 5.42 and CERES-Maize v. 2.1, with the existing genetic coefficients, were tested using data for soybean and maize grown under extreme photoperiods. Identical experiments were performed at two sites on Maui Island, Hawaii, over three years. The treatment design was a factorial of photoperiods (natural, natural + 0.5 h, 14-, 17-, and 20-h) and cultivars ('Bragg', 'Evans', 'Jupiter', and 'Williams' for soybean and Pioneer hybrids X304C, 3165, 3324, 3475, and 3790 for maize). Observations included development stage dates, yield, yield components, aboveground biomass weight, soil chemical analysis, and weather. Comparisons between observed and simulated results showed that soybean and maize development was well simulated. However, soybean yield and maize growth and yield were not well simulated. Further analysis suggested that model bias and parameter uncertainty accounted for nearly equal proportions of variation in soybean grain yield, whereas most maize growth and yield variation was due to model bias. SOYGRO and CERES-Maize genetic coefficients were calculated from the data in the above experiments. One method to recalculate genetic coefficients was to incrementally change the genetic coefficients until simulated matched observed results. Another method was performed according to the maize modeler's suggestion. The fitting method adequately established development genetic coefficients, whereas growth coefficients had similar biases as the original genetic coefficients. The explicit method did not well simulate maize growth. Using the fitted genetic coefficient means ± standard error, a sensitivity analysis was done. The genetic coefficient error that caused the greatest variation in simulated yield and aboveground biomass was identified. The most problematic genetic coefficients and associated model routines for yield and growth was the pod production relationship to nightlength in SOYGRO and juvenile phase duration in CERES-Maize

Allometric Models for Predicting Aboveground Biomass and Carbon Stock of Tropical Perennial C4 Grasses in Hawaii

Biomass is a promising renewable energy option that provides a more environmentally sustainable alternative to fossil resources by reducing the net flux of greenhouse gasses to the atmosphere. Yet, allometric models that allow the prediction of aboveground biomass (AGB), biomass carbon (C) stock non-destructively have not yet been developed for tropical perennial C4 grasses currently under consideration as potential bioenergy feedstock in Hawaii and other subtropical and tropical locations. The objectives of this study were to develop optimal allometric relationships and site-specific models to predict AGB, biomass C stock of napiergrass, energycane, and sugarcane under cultivation practices for renewable energy and validate these site-specific models against independent data sets generated from sites with widely different environments. Several allometric models were developed for each species from data at a low elevation field on the island of Maui, Hawaii. A simple power model with stalk diameter (D) was best related to AGB and biomass C stock for napiergrass, energycane, and sugarcane, (R2 = 0.98, 0.96, and 0.97, respectively). The models were then tested against data collected from independent fields across an environmental gradient. For all crops, the models over-predicted AGB in plants with lower stalk D, but AGB was under-predicted in plants with higher stalk D. The models using stalk D were better for biomass prediction compared to dewlap H (Height from the base cut to most recently exposed leaf dewlap) models, which showed weak validation performance. Although stalk D model performed better, however, the mean square error (MSE)-systematic was ranged from 23 to 43 % of MSE for all crops. A strong relationship between model coefficient and rainfall was existed, although these were irrigated systems; suggesting a simple site-specific coefficient modulator for rainfall to reduce systematic errors in water-limited areas. These allometric equations provide a tool for farmers in the tropics to estimate perennial C4 grass biomass and C stock during decision-making for land management and as an environmental sustainability indicator within a renewable energy system

Field-Based Estimates of Global Warming Potential in Bioenergy Systems of Hawaii: Crop Choice and Deficit Irrigation

Replacing fossil fuel with biofuel is environmentally viable from a climate change perspective only if the net greenhouse gas (GHG) footprint of the system is reduced. The effects of replacing annual arable crops with perennial bioenergy feedstocks on net GHG production and soil carbon (C) stock are critical to the system-level balance. Here, we compared GHG flux, crop yield, root biomass, and soil C stock under two potential tropical, perennial grass biofuel feedstocks: conventional sugarcane and ratoon-harvested, zero-tillage napiergrass. Evaluations were conducted at two irrigation levels, 100% of plantation application and at a 50% deficit. Peaks and troughs of GHG emission followed agronomic events such as ratoon harvest of napiergrass and fertilization. Yet, net GHG flux was dominated by carbon dioxide (CO2), as methane was oxidized and nitrous oxide (N2O) emission was very low even following fertilization. High N2O fluxes that frequently negate other greenhouse gas benefits that come from replacing fossil fuels with agronomic forms of bioenergy were mitigated by efficient water and fertilizer management, including direct injection of fertilizer into buried irrigation lines. From soil intensively cultivated for a century in sugarcane, soil C stock and root biomass increased rapidly following cultivation in grasses selected for robust root systems and drought tolerance. The net soil C increase over the two-year crop cycle was three-fold greater than the annualized soil surface CO2 flux. Deficit irrigation reduced yield, but increased soil C accumulation as proportionately more photosynthetic resources were allocated belowground. In the first two years of cultivation napiergrass did not increase net greenhouse warming potential (GWP) compared to sugarcane, and has the advantage of multiple ratoon harvests per year and less negative effects of deficit irrigation to yield

Biomass production of herbaceous energy crops in the United States: field trial results and yield potential maps from the multiyear regional feedstock partnership

Current knowledge of yield potential and best agronomic management practices for perennial bioenergy grasses is primarily derived from small-scale and short-term studies, yet these studies inform policy at the national scale. In an effort to learn more about how bioenergy grasses perform across multiple locations and years, the U.S. Department of Energy (US DOE)/Sun Grant Initiative Regional Feedstock Partnership was initiated in 2008. The objectives of the Feedstock Partnership were to (1) provide a wide range of information for feedstock selection (species choice) and management practice options for a variety of regions and (2) develop national maps of potential feedstock yield for each of the herbaceous species evaluated. The Feedstock Partnership expands our previous understanding of the bioenergy potential of switchgrass, Miscanthus, sorghum, energycane, and prairie mixtures on Conservation Reserve Program land by conducting long-term, replicated trials of each species at diverse environments in the U.S. Trials were initiated between 2008 and 2010 and completed between 2012 and 2015 depending on species. Field-scale plots were utilized for switchgrass and Conservation Reserve Program trials to use traditional agricultural machinery. This is important as we know that the smaller scale studies often overestimated yield potential of some of these species. Insufficient vegetative propagules of energycane and Miscanthus prohibited farm-scale trials of these species. The Feedstock Partnership studies also confirmed that environmental differences across years and across sites had a large impact on biomass production. Nitrogen application had variable effects across feedstocks, but some nitrogen fertilizer generally had a positive effect. National yield potential maps were developed using PRISM-ELM for each species in the Feedstock Partnership. This manuscript, with the accompanying supplemental data, will be useful in making decisions about feedstock selection as well as agronomic practices across a wide region of the country

Neoadjuvant or adjuvant therapy for resectable esophageal cancer: a systematic review and meta-analysis

BACKGROUND: Carcinoma of the esophagus is an aggressive malignancy with an increasing incidence. Its virulence, in terms of symptoms and mortality, justifies a continued search for optimal therapy. The large and growing number of patients affected, the high mortality rates, the worldwide geographic variation in practice, and the large body of good quality research warrants a systematic review with meta-analysis. METHODS: A systematic review and meta-analysis investigating the impact of neoadjuvant or adjuvant therapy on resectable thoracic esophageal cancer to inform evidence-based practice was produced. MEDLINE, CANCERLIT, Cochrane Library, EMBASE, and abstracts from the American Society of Clinical Oncology and the American Society for Therapeutic Radiology and Oncology were searched for trial reports. Included were randomized trials or meta-analyses of neoadjuvant or adjuvant treatments compared with surgery alone or other treatments in patients with resectable thoracic esophageal cancer. Outcomes of interest were survival, adverse effects, and quality of life. Either one- or three-year mortality data were pooled and reported as relative risk ratios. RESULTS: Thirty-four randomized controlled trials and six meta-analyses were obtained and grouped into 13 basic treatment approaches. Single randomized controlled trials detected no differences in mortality between treatments for the following comparisons: - Preoperative radiotherapy versus postoperative radiotherapy. - Preoperative and postoperative radiotherapy versus postoperative radiotherapy. Preoperative and postoperative radiotherapy was associated with a significantly higher mortality rate. - Postoperative chemotherapy versus postoperative radiotherapy. - Postoperative radiotherapy versus postoperative radiotherapy plus protein-bound polysaccharide versus chemoradiation versus chemoradiation plus protein-bound polysaccharide. Pooling one-year mortality detected no statistically significant differences in mortality between treatments for the following comparisons: - Preoperative radiotherapy compared with surgery alone (five randomized trials). - Postoperative radiotherapy compared with surgery alone (five randomized trials). - Preoperative chemotherapy versus surgery alone (six randomized trials). - Preoperative and postoperative chemotherapy versus surgery alone (two randomized trials). - Preoperative chemoradiation therapy versus surgery alone (six randomized trials). Single randomized controlled trials detected differences in mortality between treatments for the following comparison: - Preoperative hyperthermia and chemoradiotherapy versus preoperative chemoradiotherapy in favour of hyperthermia. Pooling three-year mortality detected no statistically significant difference in mortality between treatments for the following comparison: - Postoperative chemotherapy compared with surgery alone (two randomized trials). Pooling three-year mortality detected statistically significant differences between treatments for the following comparisons: - Preoperative chemoradiation therapy versus surgery alone (six randomized trials) in favour of preoperative chemoradiation with surgery. - Preoperative chemotherapy compared with preoperative radiotherapy (one randomized trial) in favour of preoperative radiotherapy. CONCLUSION: For adult patients with resectable thoracic esophageal cancer for whom surgery is considered appropriate, surgery alone (i.e., without neoadjuvant or adjuvant therapy) is recommended as the standard practice

Review of Biomass Resources and Conversion Technologies for Alternative Jet Fuel Production in Hawai’i and Tropical Regions

There is increasing interest in developing biobased alternative jet fuels to meet rising aviation demand and address environmental concerns. Uncertainty of oil prices, issues of energy security, and rising greenhouse gas concentrations have spurred the development and acceptance of alternative, economically viable, environmentally sustainable production pathways. The objectives of this study were to review alternative jet fuel feedstock candidates and relevant conversion data to provide a baseline of information to be accessed and built upon in developing production scenarios in Hawai’i and other tropical regions bounded by the Tropic of Cancer in the northern hemisphere and the Tropic of Capricorn in the southern hemisphere. Seventeen plants that produce oil, fiber, and sugar feedstocks were identified, and information on cultural practices, yield ranges, invasiveness, and mechanization status was assembled. Available data on pretreatment requirements and conversion processes for the 17 feedstocks, including mass and energy balances, product and byproduct yield and quality, and scale requirements/unit sizes, were reviewed. This effort seeks to inform the development and design of alternative jet fuel production along regional supply chains in Hawai’i and other locations in the tropics

Time series for environmental variables and gas fluxes.

<p>Precipitation, irrigation (a), soil water filled pore space (b) and temperature (air and soil) (c), and greenhouse gas flux (d-f) for one production cycle of commercial field #609 at HC&S. Mean values (± one standard error) are shown for static chamber measurements of CO₂ (d), N₂O (e), and CH₄ (f) flux.</p

N₂O flux increases after fertilization.

<p>N₂O flux following fertilization; values are means (± one standard error).</p