This document describes a simulation model of cauliflower growth and development under conditions where water and nutrients are not limiting. The model consists of four linked processes: crop development, leaf area expansion, increase in curd diameter, and growth of dry matter. The model aims to describe variability between plants in time of curd initiation and harvest. A verification of the model against field data showed that the model was able to reproduce variability in curd diameter, indicating that variability in curd size is caused by variability in time of curd initiation.
This study examined the sensitivity of autumn wheat (Omid variety) to under irrigation in Shahrekord, Iran. A field experiment was conducted with 9 irrigation treatments and 4 replications. Irrigation was applied starting in June, with the amount reduced based on the treatment. Yield and yield components were measured. Relationships between yield decrease and water consumption decrease were nonlinear, indicating the wheat variety had little sensitivity to under irrigation. For a 30% decrease in water, yield decreased only 3%, showing tolerance to drought conditions.
Climate change is projected to outpace rates of niche change in grasses. The authors analyzed 236 grass species across three time-calibrated phylogenies to estimate past rates of climatic niche change. They compared these rates to projected rates of climate change by 2070 under different climate change scenarios. They found that projected rates of climate change for temperature and precipitation were consistently faster than past rates of niche change in grasses, often by thousands of times. This suggests that without rapid niche changes, many grass species may face extinction due to inability to adapt quickly enough to climate change through niche shifts. As grasses are fundamental to grassland ecosystems and human agriculture, these findings have troubling implications for global biodiversity and food security.
This document discusses plant growth analysis methodologies. It provides background on the classical approach of calculating relative growth rate (RGR) and net assimilation rate (NAR) between two harvests. More recent methods use curve-fitting to model plant weight and leaf area over time. The objectives are to quantify effects of environmental influences on growth rates and analyze differences between crop varieties. The literature review discusses studies on sugar beet growth response to potassium fertilizer. Key growth parameters discussed include leaf area, leaf area index (LAI), crop growth rate (CGR), and relative growth rate (RGR). Formulas for calculating each parameter are provided.
Crop weather modeling is important for understanding how weather impacts crop growth and productivity. Various factors like temperature, solar radiation, rainfall, and wind influence agricultural production at different growth stages. Crop weather models simulate these relationships and can be used for yield prediction, climate change evaluation, and identifying optimal management practices. Common crop models include DSSAT, BAMnut, and CROPWAT, which model processes like phenology, photosynthesis, and water balance to estimate biomass, yield, and water use over time based on weather and soil inputs. Such models provide useful insights for farmers and researchers.
The document discusses various theories on crop growth factors proposed by scientists over time, including:
1. Liebig's law of the minimum from 1840 which states that plant growth is limited by the least available nutrient.
2. Mitscherlich's 1909 equation relating growth to the supply of limiting nutrients.
3. Studies showing that increased CO2 concentration can increase yields, but regulating CO2 in open fields remains a challenge.
4. The effects of increased global CO2 levels on temperature and potential agricultural impacts.
Effects of Water Deficiency on the Physiology and Yield of Three Maize GenotypesAgriculture Journal IJOEAR
Three maize genotypes research experiment was carried out in the experimental farm of University of Debrecen, Hungary. The genotypes were subjected to two different treatments, (irrigated and non-irrigated) where the irrigated was the control experiment. Physiological parameters (SPAD, LAI, HEIGHT) and grain yield (kg ha-1) were measured and statistically computed. From our results, SPAD, LAI and HEIGHT values were significantly affected by water stress in the three studied genotypes. Grain yield was reduced in two of the studied genotypes (S.Y Zephir and S.Y Chorintos). But no significant difference was notice in the KWS 4484 cultivar. LAI was not affected in the second measurement in the S.Y Chorintos genotype and, plant height did not record any difference in the first measurement in the KWS 4484 cultivar. Our results suggest second experiment to specifically look at the critical stage in the genotypes growth where water stress has the severe effect on the studied genotypes.
Water Requirement and Crop Coefficient of Onion (Red Bombay) in the Central R...paperpublications3
This document discusses a study on determining the crop coefficient (Kc) of Red Bombay onion in central Ethiopia. Researchers grew Red Bombay onion in lysimeters to directly measure crop evapotranspiration (ETc) over four years. They also calculated reference evapotranspiration (ETo) from weather data. The Kc was then determined as the ratio of ETc to ETo. Results showed Kc values of 0.34, 0.70, 1.01 and 0.68 for the initial, development, mid-season and late stages respectively. These locally determined Kc values can be used for irrigation planning and management in similar agroclimatic conditions.
This study examined the sensitivity of autumn wheat (Omid variety) to under irrigation in Shahrekord, Iran. A field experiment was conducted with 9 irrigation treatments and 4 replications. Irrigation was applied starting in June, with the amount reduced based on the treatment. Yield and yield components were measured. Relationships between yield decrease and water consumption decrease were nonlinear, indicating the wheat variety had little sensitivity to under irrigation. For a 30% decrease in water, yield decreased only 3%, showing tolerance to drought conditions.
Climate change is projected to outpace rates of niche change in grasses. The authors analyzed 236 grass species across three time-calibrated phylogenies to estimate past rates of climatic niche change. They compared these rates to projected rates of climate change by 2070 under different climate change scenarios. They found that projected rates of climate change for temperature and precipitation were consistently faster than past rates of niche change in grasses, often by thousands of times. This suggests that without rapid niche changes, many grass species may face extinction due to inability to adapt quickly enough to climate change through niche shifts. As grasses are fundamental to grassland ecosystems and human agriculture, these findings have troubling implications for global biodiversity and food security.
This document discusses plant growth analysis methodologies. It provides background on the classical approach of calculating relative growth rate (RGR) and net assimilation rate (NAR) between two harvests. More recent methods use curve-fitting to model plant weight and leaf area over time. The objectives are to quantify effects of environmental influences on growth rates and analyze differences between crop varieties. The literature review discusses studies on sugar beet growth response to potassium fertilizer. Key growth parameters discussed include leaf area, leaf area index (LAI), crop growth rate (CGR), and relative growth rate (RGR). Formulas for calculating each parameter are provided.
Crop weather modeling is important for understanding how weather impacts crop growth and productivity. Various factors like temperature, solar radiation, rainfall, and wind influence agricultural production at different growth stages. Crop weather models simulate these relationships and can be used for yield prediction, climate change evaluation, and identifying optimal management practices. Common crop models include DSSAT, BAMnut, and CROPWAT, which model processes like phenology, photosynthesis, and water balance to estimate biomass, yield, and water use over time based on weather and soil inputs. Such models provide useful insights for farmers and researchers.
The document discusses various theories on crop growth factors proposed by scientists over time, including:
1. Liebig's law of the minimum from 1840 which states that plant growth is limited by the least available nutrient.
2. Mitscherlich's 1909 equation relating growth to the supply of limiting nutrients.
3. Studies showing that increased CO2 concentration can increase yields, but regulating CO2 in open fields remains a challenge.
4. The effects of increased global CO2 levels on temperature and potential agricultural impacts.
Effects of Water Deficiency on the Physiology and Yield of Three Maize GenotypesAgriculture Journal IJOEAR
Three maize genotypes research experiment was carried out in the experimental farm of University of Debrecen, Hungary. The genotypes were subjected to two different treatments, (irrigated and non-irrigated) where the irrigated was the control experiment. Physiological parameters (SPAD, LAI, HEIGHT) and grain yield (kg ha-1) were measured and statistically computed. From our results, SPAD, LAI and HEIGHT values were significantly affected by water stress in the three studied genotypes. Grain yield was reduced in two of the studied genotypes (S.Y Zephir and S.Y Chorintos). But no significant difference was notice in the KWS 4484 cultivar. LAI was not affected in the second measurement in the S.Y Chorintos genotype and, plant height did not record any difference in the first measurement in the KWS 4484 cultivar. Our results suggest second experiment to specifically look at the critical stage in the genotypes growth where water stress has the severe effect on the studied genotypes.
Water Requirement and Crop Coefficient of Onion (Red Bombay) in the Central R...paperpublications3
This document discusses a study on determining the crop coefficient (Kc) of Red Bombay onion in central Ethiopia. Researchers grew Red Bombay onion in lysimeters to directly measure crop evapotranspiration (ETc) over four years. They also calculated reference evapotranspiration (ETo) from weather data. The Kc was then determined as the ratio of ETc to ETo. Results showed Kc values of 0.34, 0.70, 1.01 and 0.68 for the initial, development, mid-season and late stages respectively. These locally determined Kc values can be used for irrigation planning and management in similar agroclimatic conditions.
Influence of Row Covers on Soil Loss & Plant Growth in White Cabbage Cultivation; Gardening Guidebook for Stuttgart, Germany ~ University of Hohenheim~ For more information, Please see websites below:
`
Organic Edible Schoolyards & Gardening with Children =
http://scribd.com/doc/239851214 ~
`
Double Food Production from your School Garden with Organic Tech =
http://scribd.com/doc/239851079 ~
`
Free School Gardening Art Posters =
http://scribd.com/doc/239851159 ~
`
Increase Food Production with Companion Planting in your School Garden =
http://scribd.com/doc/239851159 ~
`
Healthy Foods Dramatically Improves Student Academic Success =
http://scribd.com/doc/239851348 ~
`
City Chickens for your Organic School Garden =
http://scribd.com/doc/239850440 ~
`
Huerto Ecológico, Tecnologías Sostenibles, Agricultura Organica
http://scribd.com/doc/239850233
`
Simple Square Foot Gardening for Schools - Teacher Guide =
http://scribd.com/doc/239851110
1. The document discusses crop response production functions, which relate crop yield to input levels like water. It examines early studies on this relationship and more recent physiological and semi-empirical approaches.
2. Physiological studies show crop yields are affected by complex interactions between water deficits and growth processes. Semi-empirical models relate yield to soil moisture, evapotranspiration, and applied irrigation.
3. The document reviews studies showing relationships between crop yield and factors like transpiration, evapotranspiration, and applied water. Growth stage is also found to impact the effect of evapotranspiration on yield.
This study aimed to develop allometric equations to predict the aboveground biomass of Agave lechuguilla plants in Mexico. Researchers directly measured the biomass of 533 A. lechuguilla plants across three Mexican states by harvesting representative plants and weighing their biomass. They then developed potential and Schumacher-Hall allometric equations relating biomass to plant height and crown diameter measurements. The Schumacher-Hall equation had the best fit and predictive performance. However, including dummy variables revealed population differences between the three states, suggesting separate equations are needed for each state location. The developed equations can help quantify carbon storage in arid and semi-arid regions of Mexico.
This document analyzes wheat yield trial data from 25 years across 76 countries to assess sensitivity to temperature and breeding gains in hot environments. Wheat yields were most sensitive to warming during grain-filling, the hottest season stage, though sites with high vapor pressure deficit showed less sensitivity due to transpirational cooling. Genetic improvements were estimated by correcting yields for environmental changes over time. Elite Spring Wheat trials showed gains closest to optimal temperatures, with no gains in hottest areas. Semi-Arid Wheat trials targeting stress showed strongest gains in hottest areas, implying targeted breeding improves heat tolerance.
This document presents a summary of several classical theories on plant growth response to nutrients:
1) Liebig's Law of the Minimum states that plant growth is limited by the scarcest nutrient.
2) Blackman's Law of the Limiting Factor states that the growth rate is determined by the slowest acting growth factor.
3) Willcox's Theory of the Nitrogen Constant found plants absorb about 318 lbs of nitrogen per acre at optimum conditions.
4) Spillman's Equation models the relationship between growth amount, maximum possible yield, growth factor quantity, and a constant.
5) Baule Unit defines the amount of nitrogen, phosphorus, or potassium needed to produce 50% of maximum possible
- The document discusses a study on the combined effects of water and high temperature stress on maize yield and growth. It provides background on maize types and importance, as well as factors that affect maize growth such as biotic and abiotic stresses including drought, temperature, and their interaction.
- The literature review covers definitions of heat and water stress, their documented impacts on maize morphology and yield, and critical growth periods for water availability. Methods to mitigate stresses through irrigation, tillage practices, and mulching are also examined.
- The conclusion emphasizes the need to develop maize cultivars tolerant to heat, water, and their combined stresses given current global warming trends.
Effect of Regulated Deficit Irrigation (RDI) on Smith's Early Navel OrangeEmily Wieber
My research aims to determine a sensitive and continuous plant-based measure for irrigation scheduling in citrus trees. My two research hypotheses are: 1. Navel orange trees can withstand a moderate irrigation reduction below their full crop evapo-transpiration requirement (ETc); and 2. Sap flow (SF) will be the most sensitive continuous indicator of the onset of plant water stress. Previous research has shown that regulated deficit irrigation (RDI) during the early fruit growth and the fruit ripening phases can save water without compromising yield. I am conducting this research in 2013 – 2015, using Navel orange trees at the Citrus Experiment Station at UC Riverside. The study consists of one control and three treatment groups (RDI1, RDI2, and RDI3). The control receives 100% ETc. during all phases. The RDI1 group receives 25% ETc in late spring and 100% ETc al other times. The RDI2 group receives 100% ETc during late spring and 75% ETc during fall. During the first year, I was unable to apply RDI in the fall. For the second year, 25% ETc in spring was achieved by installing 18 gate vale regulators; and 75% ETc in the fall is currently achieved by installing 18 inline vale regulators. I have been going out to the field twice a month to download data from sap flow sensors and dendrometers and once a month to measure stem water potential. The remaining research tasks are to complete the irrigation treatments this winter and measure orange yield for each treatment.
This study compared two indices for quantifying summer dormancy in tall fescue populations and examined the relationship between dormancy and spring forage quality. Index A, based on summer to autumn dry matter yield ratios, and Index B, based on summer yield relative to the highest yielding variety, both accurately ranked populations' dormancy levels. Summer dormant populations flowered earlier in spring than summer active KY-31 fescue, resulting in lower forage quality earlier in the season due to increased stemminess. While dormant varieties produced lower quality forage in early spring, one variety had higher crude protein later compared to KY-31 despite being at a more advanced growth stage.
effects of climate change on vegetation in mediterranean forestsIJEAB
A systematic literature review was undertaken to analyze the effects of climate change concerning the forests in the Mediterranean region as it is a climate and a global hot spot of biological diversity and the richest biodiversity region in Europe. Climate change threatens several eco-systems (e.g. forests) with ecological and socioeconomic importance. It is noteworthy that all warming scenarios in the Mediterranean predict an increase of drought and heat events, and a reduction in precipitation within the next hundred years in the Mediterranean basin with im-portant consequences in local vegetation communities. Forests can therefore be used as a tool in developing so-lutions to the problem of climate change. Nowadays, is considered necessary firstly to continue monitoring and research concerning climate change patterns and impacts on regional scales and secondly to implement manage-ment strategies in order to preserve Mediterranean habi-tats.
This document discusses opportunities for improving photosynthesis in crops to increase food security. It begins by outlining the scale of increased crop yields needed by 2050 due to population growth. Current yield increases are not keeping pace. The theoretical framework for analyzing yield considers light interception efficiency, conversion efficiency of intercepted light to biomass, and harvest index. While light interception and harvest index improvements are limited, conversion efficiency or radiation use efficiency could be improved through photosynthesis. Strategies discussed include modifying crop canopy architecture, improving Rubisco, bypassing photorespiration, and applying technologies like genetic engineering. A case study models how reducing chlorophyll in upper canopy leaves with more in lower leaves could increase canopy photosynthesis with little penalty.
Influence of Plant Density and Mulching on Growth and Yield of Lettuce (Lactu...Agriculture Journal IJOEAR
This document summarizes a study on the effects of plant density and mulching on the growth and yield of romaine lettuce. The study found that planting lettuce in a seven-row bed scheme and mulching with well-rotted horse manure had the most positive effects. The seven-row bed scheme and horse manure mulch led to increased plant height, diameter, weight, and total yield compared to the other treatments. Specifically, the combination of the seven-row bed scheme and horse manure mulch increased total yield by 18% compared to the non-mulched control plots with the same planting scheme.
Effects of Climate Change on Agriculture Particularly in Semi 2008Almaz Demessie
This document summarizes the effects of climate change on agriculture, particularly in semi-arid tropical regions like Ethiopia. It finds that climate change is causing higher temperature and more variable rainfall, negatively impacting crop yields. Statistical analysis of meteorological and crop yield data from Ethiopia over 30 years shows decreasing rainfall trends and increasing temperatures. This has reduced the length of the growing period and increased evapotranspiration, limiting water availability for crops. The document concludes climate change is a serious threat to agriculture in semi-arid developing countries like Ethiopia that rely on rain-fed agriculture.
Seasonal growth patterns of Arundo donax L. in the United States | IJAAR @sli...Innspub Net
Giant reed (Arundo donax L.) has been extensively evaluated as a dedicated energy crop for biomass and biofuel production in southern Europe and the United States, with very favorable results. Current agronomic and biologic research on giant reed focuses on management practices, development of new cultivars, and determining differences among existing cultivars. Even though detailed information on the growth patterns of giant reed would assist in development of improved management practices, this information is not available in the United States. Therefore, the objective of this 2-year field study was to describe the seasonal growth patterns of giant reed in Alabama, United States. Changes in both plant height and biomass yield of giant reed with time were well described by a Gompertz function. The fastest growing period occurred at approximately 66 d after initiation of regrowth (mid-May), when the absolute maximum growth rate was of 0.045 m d-1 and 0.516mg ha-1 d-1. After mid-May, the rate of growth decreased until maturation at approximately 200 d after initiation of regrowth (mid- to late September). The observed maximum average plant height and biomass yield were 5.28 m and 48.56mg ha-1, respectively. Yield decreased following maturation up to 278 d after initiation (early to mid-December) of growth in spring, partly as a result of leaf loss, and was relatively stable thereafter.
Crop is defined as an “Aggregation of individual plant species grown in a unit area for economic purpose”.
Growth is defined as an “Irreversible increase in size and volume and is the consequence of differentiation and distribution occurring in the plant”.
Simulation is defined as “Reproducing the essence of a system without reproducing the system itself”. In simulation the essential characteristics of the system are reproduced in a model, which is then studied in an abbreviated time scale.
Yield response of intercropped maize (zea mays l.) and okra (abelmoschus escu...Alexander Decker
This document summarizes a study on the yield response of intercropped maize and okra under different seasonal conditions in Makurdi, Nigeria. The study found that:
1) Okra yield was higher in the wet season than the dry season, and monocropped okra yielded more than intercropped okra. Intercropping reduced okra yield more in the dry season.
2) Maize yield was unaffected by intercropping and was higher in the wet season for both sole and intercropped maize.
3) Total intercrop yield and land equivalent ratio were higher in the wet season, indicating intercropping was more productive in the wet season.
Crop modelling is useful for optimizing rice production. The document discusses rice crop modelling methodology and applications. It provides an overview of different types of crop models and their purposes. Statistical, mechanistic, deterministic, and stochastic models are described. The document also discusses important rice crop simulation models like DSSAT, APSIM, ORYZA1, and InfoCrop. It explains how these models work and the types of inputs they require. The validation of model outputs against observed field data is also demonstrated through sample tables and figures. Crop models help address issues in rice crops, optimize management practices, and evaluate impacts of climate change.
Effects of regulated deficit irrigation (rdi) on fruit yield, quality, and ph...Emily Wieber
Citrus orchards are irrigated with enough water to meet or exceed demands by crop evapotranspiration (ETc). The research objective was to measure fruit yield and the plant’s physiological responses when the trees were subjected to regulated deficit irrigation (RDI). The study consisted of one control group and three irrigation treatment groups (RDI1, RDI2, and RDI3). Research has shown that applying RDI during the early fruit growth (phase IIA) and fruit ripening (phase III) phases can save water without compromising fruit yield. These two phases occurred from May 16th to July 15th and from October 16th through December 15th, respectively. The first hypothesis was that Navel orange trees can withstand a moderate irrigation reduction below full ETc during phase IIA and III without compromising fruit yield. The second hypothesis was that sap flow (SF) would be a sensitive and continuous indicator of the onset of plant water stress. During phase IIA, RDI1 and RDI3 trees were subjected to 25% ETc; while during phase III, RDI2 and RDI3 trees were subjected to 75% ETc. Pressure chamber, SF sensors, and point dendrometers were used to detect plant water stress. Signal intensity of midday stem and MDS was determined by dividing the average of RDI1 and RDI3 to that of the control. Signal intensity of SF was determined by dividing the average of the control to the average of RDI1 and RDI3. The results indicated that RDI enhanced fruit quality while did not significantly reduce total fruit yield. RDI1 had a 19% total water savings and a 36% reduction in profit. RDI2 had a 2% total water savings and an 18% increase in profit. RDI3 had a 21% total water savings but an 18% reduction in profit. Considering the benefits of water savings and the lost in profits, RDI3 and RDI2 were better irrigation strategies than RDI1. There was inconsistency in plant-based parameters (including stem, SF, and MDS) in showing the effects of RDI. stem had highest signal intensity, following by MDS and SF. Comparing to MDS, SF had higher signal to noises ratio, which suggested that SF was a better water stress indicator than MDS. Because the irrigation was not set up in 2013, signal intensity of SF or MDS was not established to use for irrigation scheduling in 2014.
Food Security Production Challenges in Indonesia as Impact of Global Climate ...Agriculture Journal IJOEAR
— Global food availability, including national as well as local, is highly dependent on the natural resources that will affect crop production. Although there is rain, soil temperatures and conditions have formed a natural system that will support agricultural efforts, but this state is unstable and always changes according to atmospheric conditions in an integrated manner. Human beings on certain boundaries can intervene with the natural resources. Climate (generally a combination of rain, temperature, and sunlight) is the most important growth factor in crop production in the field. Any change in climatic conditions will have far-reaching effects on global food production. Global climate change, excessive land and land exploitation, inaccurate land management, in its time will have an impact on the food production and availability of a region. Knowing well the of nature characteristics, then anticipating the impact that will arise and determine the ways of handling it, is a series of business and activities that must be done to achieve food security. To anticipate climate change and its impacts on crop production, a broad outline can be made by considering the following physical technic aspects: 1) adjusting cropping patterns; 2) increasing the area of forest cover and catchment areas; 3) application of land and crop management technology. Some application of land and crop management technologies include: organic farming, implementation of Surjan system, food diversification, large tree planting, water pond production, etc. The policies that need to be taken as a solution in anticipating the impact of global climate change are 1) the preparation and stipulation of special food agriculture scenarios, including the zoning of production potential and zonation of climate risk (drought, flood, landslide, etc.) with the updating of data every year; 2) reducing the conversion of agricultural land (food); 3) incentives for farmers; 4) changing the consumption pattern of the people, from the consumption of rice to alternative staple foods; 5) subsidies and protection of food farming; 6) climate monitoring and prediction (early rainy season, long growing period, and potential water availability; 7) Revitalization of watershed (DAS) functions; 8) Multiply the artificial water absorption area.
Seed viability equations and application of nomograohs in storagekartoori sai santhosh
The document discusses the development of seed viability equations over time to better predict seed longevity in storage. Key developments include adopting international gene bank standards, incorporating the effects of temperature, moisture content, and seed quality on longevity, and relating longevity to the glass transition temperature of seeds. The equations have evolved from basic forms involving three or four constants to a single improved equation incorporating constants for species and storage conditions.
Evaluation of vernalization requirement in wheat inbred lines and cultivars u...Innspub Net
An understanding of vernalization requirement is a prerequisite for the development of cold tolerant cultivars for
high stress regions. Vernalization requirement in winter wheat (Triticum aestivum L.) has not been adequately
addressed. Therefore, the objective of the present study was to understand how the vernalization dates are
related to cold tolerance, phenological development and photosynthesis in four inbred lines (inbred line 1, 2, 3
and 4) and two wheat cultivars (Mironovskaya-808 and Pishtaz). These genotypes were subjected to vernalization temperature (5 C) on 30.11.2012, 17.12.2012, 09.01.2013, 13.02.2013 and 08.03.2013 as different vernalization dates. Control plants were grown under 25/20 C, day/night condition. Final leaf number was determined at intervals throughout the growth period to measure vernalization status. Number of days until heading was registered and lethal temperature (LT50) was determined. Photosynthesis rate was measured at the end of winter and flowering stages. According to the results the individual effect of genotype and vernalization date was significant on final leaf number, number of days until flowering and LT50. However, photosynthesis rate was just affected by vernalization date. In addition, interaction between vernalization date and genotype was significant on final leaf number, number of days until flowering and LT50. These results support the hypothesis that vernalization responses regulate phenological growth and affect cold tolerance through their influence on the rate of plant development.
Influence of Row Covers on Soil Loss & Plant Growth in White Cabbage Cultivation; Gardening Guidebook for Stuttgart, Germany ~ University of Hohenheim~ For more information, Please see websites below:
`
Organic Edible Schoolyards & Gardening with Children =
http://scribd.com/doc/239851214 ~
`
Double Food Production from your School Garden with Organic Tech =
http://scribd.com/doc/239851079 ~
`
Free School Gardening Art Posters =
http://scribd.com/doc/239851159 ~
`
Increase Food Production with Companion Planting in your School Garden =
http://scribd.com/doc/239851159 ~
`
Healthy Foods Dramatically Improves Student Academic Success =
http://scribd.com/doc/239851348 ~
`
City Chickens for your Organic School Garden =
http://scribd.com/doc/239850440 ~
`
Huerto Ecológico, Tecnologías Sostenibles, Agricultura Organica
http://scribd.com/doc/239850233
`
Simple Square Foot Gardening for Schools - Teacher Guide =
http://scribd.com/doc/239851110
1. The document discusses crop response production functions, which relate crop yield to input levels like water. It examines early studies on this relationship and more recent physiological and semi-empirical approaches.
2. Physiological studies show crop yields are affected by complex interactions between water deficits and growth processes. Semi-empirical models relate yield to soil moisture, evapotranspiration, and applied irrigation.
3. The document reviews studies showing relationships between crop yield and factors like transpiration, evapotranspiration, and applied water. Growth stage is also found to impact the effect of evapotranspiration on yield.
This study aimed to develop allometric equations to predict the aboveground biomass of Agave lechuguilla plants in Mexico. Researchers directly measured the biomass of 533 A. lechuguilla plants across three Mexican states by harvesting representative plants and weighing their biomass. They then developed potential and Schumacher-Hall allometric equations relating biomass to plant height and crown diameter measurements. The Schumacher-Hall equation had the best fit and predictive performance. However, including dummy variables revealed population differences between the three states, suggesting separate equations are needed for each state location. The developed equations can help quantify carbon storage in arid and semi-arid regions of Mexico.
This document analyzes wheat yield trial data from 25 years across 76 countries to assess sensitivity to temperature and breeding gains in hot environments. Wheat yields were most sensitive to warming during grain-filling, the hottest season stage, though sites with high vapor pressure deficit showed less sensitivity due to transpirational cooling. Genetic improvements were estimated by correcting yields for environmental changes over time. Elite Spring Wheat trials showed gains closest to optimal temperatures, with no gains in hottest areas. Semi-Arid Wheat trials targeting stress showed strongest gains in hottest areas, implying targeted breeding improves heat tolerance.
This document presents a summary of several classical theories on plant growth response to nutrients:
1) Liebig's Law of the Minimum states that plant growth is limited by the scarcest nutrient.
2) Blackman's Law of the Limiting Factor states that the growth rate is determined by the slowest acting growth factor.
3) Willcox's Theory of the Nitrogen Constant found plants absorb about 318 lbs of nitrogen per acre at optimum conditions.
4) Spillman's Equation models the relationship between growth amount, maximum possible yield, growth factor quantity, and a constant.
5) Baule Unit defines the amount of nitrogen, phosphorus, or potassium needed to produce 50% of maximum possible
- The document discusses a study on the combined effects of water and high temperature stress on maize yield and growth. It provides background on maize types and importance, as well as factors that affect maize growth such as biotic and abiotic stresses including drought, temperature, and their interaction.
- The literature review covers definitions of heat and water stress, their documented impacts on maize morphology and yield, and critical growth periods for water availability. Methods to mitigate stresses through irrigation, tillage practices, and mulching are also examined.
- The conclusion emphasizes the need to develop maize cultivars tolerant to heat, water, and their combined stresses given current global warming trends.
Effect of Regulated Deficit Irrigation (RDI) on Smith's Early Navel OrangeEmily Wieber
My research aims to determine a sensitive and continuous plant-based measure for irrigation scheduling in citrus trees. My two research hypotheses are: 1. Navel orange trees can withstand a moderate irrigation reduction below their full crop evapo-transpiration requirement (ETc); and 2. Sap flow (SF) will be the most sensitive continuous indicator of the onset of plant water stress. Previous research has shown that regulated deficit irrigation (RDI) during the early fruit growth and the fruit ripening phases can save water without compromising yield. I am conducting this research in 2013 – 2015, using Navel orange trees at the Citrus Experiment Station at UC Riverside. The study consists of one control and three treatment groups (RDI1, RDI2, and RDI3). The control receives 100% ETc. during all phases. The RDI1 group receives 25% ETc in late spring and 100% ETc al other times. The RDI2 group receives 100% ETc during late spring and 75% ETc during fall. During the first year, I was unable to apply RDI in the fall. For the second year, 25% ETc in spring was achieved by installing 18 gate vale regulators; and 75% ETc in the fall is currently achieved by installing 18 inline vale regulators. I have been going out to the field twice a month to download data from sap flow sensors and dendrometers and once a month to measure stem water potential. The remaining research tasks are to complete the irrigation treatments this winter and measure orange yield for each treatment.
This study compared two indices for quantifying summer dormancy in tall fescue populations and examined the relationship between dormancy and spring forage quality. Index A, based on summer to autumn dry matter yield ratios, and Index B, based on summer yield relative to the highest yielding variety, both accurately ranked populations' dormancy levels. Summer dormant populations flowered earlier in spring than summer active KY-31 fescue, resulting in lower forage quality earlier in the season due to increased stemminess. While dormant varieties produced lower quality forage in early spring, one variety had higher crude protein later compared to KY-31 despite being at a more advanced growth stage.
effects of climate change on vegetation in mediterranean forestsIJEAB
A systematic literature review was undertaken to analyze the effects of climate change concerning the forests in the Mediterranean region as it is a climate and a global hot spot of biological diversity and the richest biodiversity region in Europe. Climate change threatens several eco-systems (e.g. forests) with ecological and socioeconomic importance. It is noteworthy that all warming scenarios in the Mediterranean predict an increase of drought and heat events, and a reduction in precipitation within the next hundred years in the Mediterranean basin with im-portant consequences in local vegetation communities. Forests can therefore be used as a tool in developing so-lutions to the problem of climate change. Nowadays, is considered necessary firstly to continue monitoring and research concerning climate change patterns and impacts on regional scales and secondly to implement manage-ment strategies in order to preserve Mediterranean habi-tats.
This document discusses opportunities for improving photosynthesis in crops to increase food security. It begins by outlining the scale of increased crop yields needed by 2050 due to population growth. Current yield increases are not keeping pace. The theoretical framework for analyzing yield considers light interception efficiency, conversion efficiency of intercepted light to biomass, and harvest index. While light interception and harvest index improvements are limited, conversion efficiency or radiation use efficiency could be improved through photosynthesis. Strategies discussed include modifying crop canopy architecture, improving Rubisco, bypassing photorespiration, and applying technologies like genetic engineering. A case study models how reducing chlorophyll in upper canopy leaves with more in lower leaves could increase canopy photosynthesis with little penalty.
Influence of Plant Density and Mulching on Growth and Yield of Lettuce (Lactu...Agriculture Journal IJOEAR
This document summarizes a study on the effects of plant density and mulching on the growth and yield of romaine lettuce. The study found that planting lettuce in a seven-row bed scheme and mulching with well-rotted horse manure had the most positive effects. The seven-row bed scheme and horse manure mulch led to increased plant height, diameter, weight, and total yield compared to the other treatments. Specifically, the combination of the seven-row bed scheme and horse manure mulch increased total yield by 18% compared to the non-mulched control plots with the same planting scheme.
Effects of Climate Change on Agriculture Particularly in Semi 2008Almaz Demessie
This document summarizes the effects of climate change on agriculture, particularly in semi-arid tropical regions like Ethiopia. It finds that climate change is causing higher temperature and more variable rainfall, negatively impacting crop yields. Statistical analysis of meteorological and crop yield data from Ethiopia over 30 years shows decreasing rainfall trends and increasing temperatures. This has reduced the length of the growing period and increased evapotranspiration, limiting water availability for crops. The document concludes climate change is a serious threat to agriculture in semi-arid developing countries like Ethiopia that rely on rain-fed agriculture.
Seasonal growth patterns of Arundo donax L. in the United States | IJAAR @sli...Innspub Net
Giant reed (Arundo donax L.) has been extensively evaluated as a dedicated energy crop for biomass and biofuel production in southern Europe and the United States, with very favorable results. Current agronomic and biologic research on giant reed focuses on management practices, development of new cultivars, and determining differences among existing cultivars. Even though detailed information on the growth patterns of giant reed would assist in development of improved management practices, this information is not available in the United States. Therefore, the objective of this 2-year field study was to describe the seasonal growth patterns of giant reed in Alabama, United States. Changes in both plant height and biomass yield of giant reed with time were well described by a Gompertz function. The fastest growing period occurred at approximately 66 d after initiation of regrowth (mid-May), when the absolute maximum growth rate was of 0.045 m d-1 and 0.516mg ha-1 d-1. After mid-May, the rate of growth decreased until maturation at approximately 200 d after initiation of regrowth (mid- to late September). The observed maximum average plant height and biomass yield were 5.28 m and 48.56mg ha-1, respectively. Yield decreased following maturation up to 278 d after initiation (early to mid-December) of growth in spring, partly as a result of leaf loss, and was relatively stable thereafter.
Crop is defined as an “Aggregation of individual plant species grown in a unit area for economic purpose”.
Growth is defined as an “Irreversible increase in size and volume and is the consequence of differentiation and distribution occurring in the plant”.
Simulation is defined as “Reproducing the essence of a system without reproducing the system itself”. In simulation the essential characteristics of the system are reproduced in a model, which is then studied in an abbreviated time scale.
Yield response of intercropped maize (zea mays l.) and okra (abelmoschus escu...Alexander Decker
This document summarizes a study on the yield response of intercropped maize and okra under different seasonal conditions in Makurdi, Nigeria. The study found that:
1) Okra yield was higher in the wet season than the dry season, and monocropped okra yielded more than intercropped okra. Intercropping reduced okra yield more in the dry season.
2) Maize yield was unaffected by intercropping and was higher in the wet season for both sole and intercropped maize.
3) Total intercrop yield and land equivalent ratio were higher in the wet season, indicating intercropping was more productive in the wet season.
Crop modelling is useful for optimizing rice production. The document discusses rice crop modelling methodology and applications. It provides an overview of different types of crop models and their purposes. Statistical, mechanistic, deterministic, and stochastic models are described. The document also discusses important rice crop simulation models like DSSAT, APSIM, ORYZA1, and InfoCrop. It explains how these models work and the types of inputs they require. The validation of model outputs against observed field data is also demonstrated through sample tables and figures. Crop models help address issues in rice crops, optimize management practices, and evaluate impacts of climate change.
Effects of regulated deficit irrigation (rdi) on fruit yield, quality, and ph...Emily Wieber
Citrus orchards are irrigated with enough water to meet or exceed demands by crop evapotranspiration (ETc). The research objective was to measure fruit yield and the plant’s physiological responses when the trees were subjected to regulated deficit irrigation (RDI). The study consisted of one control group and three irrigation treatment groups (RDI1, RDI2, and RDI3). Research has shown that applying RDI during the early fruit growth (phase IIA) and fruit ripening (phase III) phases can save water without compromising fruit yield. These two phases occurred from May 16th to July 15th and from October 16th through December 15th, respectively. The first hypothesis was that Navel orange trees can withstand a moderate irrigation reduction below full ETc during phase IIA and III without compromising fruit yield. The second hypothesis was that sap flow (SF) would be a sensitive and continuous indicator of the onset of plant water stress. During phase IIA, RDI1 and RDI3 trees were subjected to 25% ETc; while during phase III, RDI2 and RDI3 trees were subjected to 75% ETc. Pressure chamber, SF sensors, and point dendrometers were used to detect plant water stress. Signal intensity of midday stem and MDS was determined by dividing the average of RDI1 and RDI3 to that of the control. Signal intensity of SF was determined by dividing the average of the control to the average of RDI1 and RDI3. The results indicated that RDI enhanced fruit quality while did not significantly reduce total fruit yield. RDI1 had a 19% total water savings and a 36% reduction in profit. RDI2 had a 2% total water savings and an 18% increase in profit. RDI3 had a 21% total water savings but an 18% reduction in profit. Considering the benefits of water savings and the lost in profits, RDI3 and RDI2 were better irrigation strategies than RDI1. There was inconsistency in plant-based parameters (including stem, SF, and MDS) in showing the effects of RDI. stem had highest signal intensity, following by MDS and SF. Comparing to MDS, SF had higher signal to noises ratio, which suggested that SF was a better water stress indicator than MDS. Because the irrigation was not set up in 2013, signal intensity of SF or MDS was not established to use for irrigation scheduling in 2014.
Food Security Production Challenges in Indonesia as Impact of Global Climate ...Agriculture Journal IJOEAR
— Global food availability, including national as well as local, is highly dependent on the natural resources that will affect crop production. Although there is rain, soil temperatures and conditions have formed a natural system that will support agricultural efforts, but this state is unstable and always changes according to atmospheric conditions in an integrated manner. Human beings on certain boundaries can intervene with the natural resources. Climate (generally a combination of rain, temperature, and sunlight) is the most important growth factor in crop production in the field. Any change in climatic conditions will have far-reaching effects on global food production. Global climate change, excessive land and land exploitation, inaccurate land management, in its time will have an impact on the food production and availability of a region. Knowing well the of nature characteristics, then anticipating the impact that will arise and determine the ways of handling it, is a series of business and activities that must be done to achieve food security. To anticipate climate change and its impacts on crop production, a broad outline can be made by considering the following physical technic aspects: 1) adjusting cropping patterns; 2) increasing the area of forest cover and catchment areas; 3) application of land and crop management technology. Some application of land and crop management technologies include: organic farming, implementation of Surjan system, food diversification, large tree planting, water pond production, etc. The policies that need to be taken as a solution in anticipating the impact of global climate change are 1) the preparation and stipulation of special food agriculture scenarios, including the zoning of production potential and zonation of climate risk (drought, flood, landslide, etc.) with the updating of data every year; 2) reducing the conversion of agricultural land (food); 3) incentives for farmers; 4) changing the consumption pattern of the people, from the consumption of rice to alternative staple foods; 5) subsidies and protection of food farming; 6) climate monitoring and prediction (early rainy season, long growing period, and potential water availability; 7) Revitalization of watershed (DAS) functions; 8) Multiply the artificial water absorption area.
Seed viability equations and application of nomograohs in storagekartoori sai santhosh
The document discusses the development of seed viability equations over time to better predict seed longevity in storage. Key developments include adopting international gene bank standards, incorporating the effects of temperature, moisture content, and seed quality on longevity, and relating longevity to the glass transition temperature of seeds. The equations have evolved from basic forms involving three or four constants to a single improved equation incorporating constants for species and storage conditions.
Evaluation of vernalization requirement in wheat inbred lines and cultivars u...Innspub Net
An understanding of vernalization requirement is a prerequisite for the development of cold tolerant cultivars for
high stress regions. Vernalization requirement in winter wheat (Triticum aestivum L.) has not been adequately
addressed. Therefore, the objective of the present study was to understand how the vernalization dates are
related to cold tolerance, phenological development and photosynthesis in four inbred lines (inbred line 1, 2, 3
and 4) and two wheat cultivars (Mironovskaya-808 and Pishtaz). These genotypes were subjected to vernalization temperature (5 C) on 30.11.2012, 17.12.2012, 09.01.2013, 13.02.2013 and 08.03.2013 as different vernalization dates. Control plants were grown under 25/20 C, day/night condition. Final leaf number was determined at intervals throughout the growth period to measure vernalization status. Number of days until heading was registered and lethal temperature (LT50) was determined. Photosynthesis rate was measured at the end of winter and flowering stages. According to the results the individual effect of genotype and vernalization date was significant on final leaf number, number of days until flowering and LT50. However, photosynthesis rate was just affected by vernalization date. In addition, interaction between vernalization date and genotype was significant on final leaf number, number of days until flowering and LT50. These results support the hypothesis that vernalization responses regulate phenological growth and affect cold tolerance through their influence on the rate of plant development.
Evaluation of vernalization requirement in wheat inbred lines and cultivars u...Innspub Net
An understanding of vernalization requirement is a prerequisite for the development of cold tolerant cultivars for
high stress regions. Vernalization requirement in winter wheat (Triticum aestivum L.) has not been adequately
addressed. Therefore, the objective of the present study was to understand how the vernalization dates are
related to cold tolerance, phenological development and photosynthesis in four inbred lines (inbred line 1, 2, 3
and 4) and two wheat cultivars (Mironovskaya-808 and Pishtaz). These genotypes were subjected to vernalization temperature (5 C) on 30.11.2012, 17.12.2012, 09.01.2013, 13.02.2013 and 08.03.2013 as different vernalization dates. Control plants were grown under 25/20 C, day/night condition. Final leaf number was determined at intervals throughout the growth period to measure vernalization status. Number of days until heading was registered and lethal temperature (LT50) was determined. Photosynthesis rate was measured at the end of winter and flowering stages. According to the results the individual effect of genotype and vernalization date was significant on final leaf number, number of days until flowering and LT50. However, photosynthesis rate was just affected by vernalization date. In addition, interaction between vernalization date and genotype was significant on final leaf number, number of days until flowering and LT50. These results support the hypothesis that vernalization responses regulate phenological growth and affect cold tolerance through their influence on the rate of plant development.
Ethylene is a plant hormone that regulates various plant processes. A study measured ethylene production in wheat plants under different stress conditions. It found that water stress and salinity stress increased ethylene production in excised wheat leaves but not in intact plants. Exposing whole wheat plants to low oxygen or low pressure reduced ethylene production. The study concluded that ethylene production in response to stress may differ between excised tissues and intact plants.
Degree day concept and phenology forecasting and crop calenderKartik Patel
The document discusses degree days, phenology forecasting, and crop calendars. It defines degree days as a unit that combines time and temperature to measure organism development. Phenology is the study of seasonal natural phenomena in relation to climate and plant/animal life. Accurately forecasting phenology is important for understanding species and ecosystem health. A crop calendar provides the average dates of sowing, growth stages, and harvest for standard crops in a region.
Experiments with duckweed–moth systems suggest thatglobal wa.docxelbanglis
Experiments with duckweed–moth systems suggest that
global warming may reduce rather than promote
herbivory
TJISSE VAN DER HEIDE, RUDI M. M. ROIJACKERS, EDWIN T. H. M. PEETERS AND
EGBERT H. VAN NES
Department of Environmental Sciences, Aquatic Ecology and Water Quality Management group, Wageningen University,
Wageningen, The Netherlands
SUMMARY
1. Wilf & Labandeira (1999) suggested that increased temperatures because of global
warming will cause an increase in herbivory by insects. This conclusion was based on the
supposed effect of temperature on herbivores but did not consider an effect of temperature
on plant growth.
2. We studied the effect of temperature on grazing pressure by the small China-mark moth
(Cataclysta lemnata L.) on Lemna minor L. in laboratory experiments.
3. Between temperatures of 15 and 24 �C we found a sigmoidal increase in C. lemnata
grazing rates, and an approximately linear increase in L. minor growth rates. Therefore, an
increase in temperature did not always result in higher grazing pressure by this insect as
the regrowth of Lemna changes also.
4. At temperatures below 18.7 �C, Lemna benefited more than Cataclysta from an increase in
temperature, causing a decrease in grazing pressure.
5. In the context of global warming, we conclude that rising temperatures will not
necessarily increase grazing pressure by herbivorous insects.
Keywords: Cataclysta, grazing, herbivory, Lemna, temperature
Introduction
Duckweeds (Lemnaceae) are often abundant in dit-
ches and ponds (Landolt, 1986). Especially when
nitrogen and phosphorus concentrations in the water
column are high, the surface area can become covered
with dense floating mats of duckweed (Lüönd, 1980,
1983; Portielje & Roijackers, 1995). These mats have
large impacts on freshwater ecosystems, restricting
oxygen supply (Pokorny & Rejmánková, 1983), light
availability of algae and submerged macrophytes
(Wolek, 1974) and temperature fluxes (Dale &
Gillespie, 1976; Landolt, 1986; Goldsborough, 1993).
These changed conditions often have a negative effect
on the biodiversity of the ecosystem (Janse & van
Puijenbroek, 1998). Other free-floating plants such as
red water fern (Azolla filiculoides), water hyacinth
(Eichhornia crassipes) and water lettuce (Pistia stratiotes)
often cause serious problems in tropical and sub-
tropical regions (Mehra et al., 1999; Hill, 2003).
Various species of herbivorous insects consume
free-floating macrophytes. Several species of weevils
(Coleoptera: Curculionidae) are able to consume large
amounts of red water fern, water hyacinth and water
lettuce (Cilliers, 1991; Hill & Cilliers, 1999; Aguilar
et al., 2003), while the larvae of the semi-aquatic Small
China-mark moth (Cataclysta lemnata) are capable of
removing large parts of floating cover of Lemnaceae
covers (Wesenberg-Lund, 1943). Duckweed is not
only used as food source, but also as building material
Correspondence: Rudi M. M. Roijacker ...
— This study summarizes the results of 30 years of our experiments with Vicia faba L seeds. Our long-term practical observations of different Vicia faba L. cultivars points out the method useful for the higher yield of seeds in terms of their viability and thus higher crop production. Our experiments led to the following important findings regarding of seed viability: 1. Individual and group variability of seeds; 2. Storage condition before germination; and 3. The condition of their germination. All these three influential conditions is possible to optimalize by method of storage effect described in this our report resulting in the improvement of crop production. This is especially important in case of seeds that are rare and/or expensive, i.e. seeds that are genetically modified or with rearranged karyotypes. Keywords— seed color, higher germination, improvement of viability, higher crop production.
The document summarizes the results of a trial evaluating the potential of various accessions of leafy vegetables (amaranth, kale, mustard, paitsai, and rape) for summer production in Taiwan. Some accessions of amaranth (TOT2353 and TOT2355) and mustard (CN078) showed the best yield, largest leaves, and good heat tolerance. While several kale accessions had good yield, the local variety performed poorly. Overall, the trial identified several promising accessions of different crops that warrant further testing for their potential to increase summer leafy vegetable production in Taiwan.
Storage conditions have a significant impact on seed quality and longevity for four vegetable crops. Seeds stored at 5°C had the highest germination percentage and germination coefficient, but the shortest mean germination time. Seeds stored at 35°C had the lowest germination percentage and germination coefficient, and the longest mean germination time. Relative humidity levels up to 58.4% did not significantly affect germination percentage, but higher levels lowered germination percentage and increased mean germination time. Tomato and cucumber seeds maintained higher germination percentages than onion and carrot seeds. Cucumber seeds had the shortest mean germination time and highest germination coefficient, while carrot seeds had the longest mean germination time and lowest germination coefficient
Influence of Storage Conditions on Seed Quality and Longevity of Four Vegetab...Seeds
This document summarizes research on the effects of different storage conditions on seed quality and longevity for four vegetable crops: carrot, cucumber, onion, and tomato. Seeds were stored under combinations of temperature (5, 15, 25, and 35°C) and relative humidity (11.3-84.3%) for periods of 1-12 months. Seed germination percentage, mean germination time, and germination coefficient of velocity were measured to assess seed quality changes over storage. Results showed that seeds stored at 5°C maintained the highest germination rates and shortest germination times, while 35°C storage led to the lowest germination rates and longest times. Higher relative humidity levels above 58.4% significantly lowered
Information about the Effect of Climatic Factors and Soil Moisture Status on ...CrimsonPublishers-SBB
Information about the Effect of Climatic Factors and Soil Moisture Status on Cotton Production using Different Statistical Relations by Zakaria M Sawan in Significances of Bioengineering & Biosciences
Role of climate in crop productivity in salt affected soils.docxBhaskar Narjary
1) Climate factors like temperature, moisture, light, and CO2 concentration have significant impacts on crop growth and productivity. Higher temperatures can reduce crop duration and yields, while changes in moisture availability can stress crops.
2) Analysis of climate data for the Karnal district of Haryana, India from 1972-2010 showed increases in average maximum and minimum temperatures as well as shifts in rainfall patterns, with more rainfall occurring in September.
3) Climate modeling projections for Haryana indicate increases in average maximum temperatures of 1.3°C by mid-century and 4.2°C by late century, with minimum temperatures rising 2.1°C and 4.7°C respectively. Precipitation
Effect of planting pattern, plant density and integration of zeoponix and che...Innspub Net
An experiment was conducted to evaluate the effect of planting pattern, plant density and integration of zeoponix and chemical N fertilizer (urea) on sunflower yield and yield components. The experimental design was analyzed as factorial based on randomized complete block with three replications. Treatments consisted of 3 factors which are different crop densities, including 2 levels. The population of plants was including 5 plants m–2 (d1) and 8 plants m–2 (d2). The second factor was planting patterns which were included twin rectangular rows (A1) and twin zigzag rows (A2). Different fertilizing treatments were selected as third factor consisted of the sole application of zeoponix (f1) and chemical fertilizer urea (f3), and integration of 50%zeoponix +50% chemical fertilizer urea (f2), that were at 3 levels. Results showed that there were significant differences in interaction of planting pattern, plant density and fertilizing system on plant height, stalk diameter, biologic yield, seed yield, number of seeds per head, 1000 seed weight, seed oil content and oil yield, protein content and protein yield and harvest index. LSD test for means of these traits showed that zigzag arrangement × plant population of 8 plants m–2 × 100% zeoponix (a2d2f1) treatment had the best performance and could be recommended to farmers for sunflower cultivation. Get the full articles at: http://www.innspub.net/volume-7-number-6-december-2015-ijaar/
Approaches to mitigate climate change Swati Shukla
1. The document discusses approaches to mitigate climate change through studies on plant responses. It focuses on how environmental stresses like increased temperature and CO2 levels, drought, salinity, and freezing temperatures impact plant development and physiology.
2. It outlines plant developmental responses to these stresses, including altered timing of growth stages and organ development. Adaptation and mitigation strategies are proposed, such as breeding for stress tolerance, adjusting management practices, and using biotechnology to introduce stress resistance genes.
3. The presentation evaluates effects of climate change factors on different crops and suggests developing new varieties with improved heat and drought tolerance to mitigate yield losses from climate change impacts.
This document summarizes the impact of rising temperatures on wheat crops. It discusses how high temperatures above wheat's optimal temperature range can negatively impact various physiological processes during growth and development, including photosynthesis, membrane integrity, grain filling duration, grain formation, leaf senescence, and protein quality. The document also reviews strategies that have shown promise in improving wheat's thermotolerance, such as modifying gene expression of heat shock proteins, antioxidants, and osmolytes.
Morphological and physiological attributes associated to drought tolerance of...Innspub Net
The experiment was conducted to assess the differential morpho-physiological response to stimulated water deficit and to determine the relationship between some of these morphological and physiological traits and yield components of eighteen durum wheat genotypes grown in pots under lathhouse condition. Water deficit significantly affected gas exchange and chlorophyll fluorescence parameters. It reduced the net photosynthesis rate (Pn), transpiration rate (E) and stomatal conductance (gs) measured both at anthesis and grain-filling stages. Similarly, the value of initial fluorescence (Fo) was increased while variable fluorescence (Fv), maximum fluorescence (Fm) and optimum quantum yield fluorescence (Fv/Fm) were decreased under water deficit. RWC of the leaves was decreased by 36.7% while SLA increased by 12.6% due to moisture stress relative to the well-watered control. No significant correlations were found between chlorophyll fluorescence parameters and grain yield under water deficit condition. Similarly, no significant correlations were found between leaf gas exchange parameters and grain yield. On the other hand, peduncle length and excursion were positively correlated with grain yield while negatively correlated with drought susceptibility index under water deficit condition. Leaf posture and rolling had also a profound effect on grain yield and other attributes. Erect-leaved genotypes had more grain yield, HI, kernel numbers per spikelet and grain-filling rate but had lower kernel weight than droopy leaved. Similarly, genotypes exhibited strong leaf rolling under water deficit condition had more grain yield, kernel numbers per spike and water use efficiency. The genetic variability found for leaf posture, leaf rolling, peduncle length and excursion among the Ethiopian durum wheat genotypes suggests the opportunity for selection superior and adapted genotype in water-limited environments. These can be achieved by integrating these morphological traits as indirect selection in conjunction with other yield components. Get the full articles at: http://www.innspub.net/volume-1-number-2-april-2011-2/
Stressful environments such as salinity and drought was assessed on photosynthesis, the most fundamental and intricate physiological process of three oil plants canola (BrassicanapusL.), safflower (Carthamustinctorius L.) and sunflower (Helianthus annusL) grown in different sites in Egypt (Suez road; North Coastal area; El-Kantra East) , is also severely affected in all its phases by such stresses .
Similar to A simulation model of climate effects on plant (20)
Immersive Learning That Works: Research Grounding and Paths ForwardLeonel Morgado
We will metaverse into the essence of immersive learning, into its three dimensions and conceptual models. This approach encompasses elements from teaching methodologies to social involvement, through organizational concerns and technologies. Challenging the perception of learning as knowledge transfer, we introduce a 'Uses, Practices & Strategies' model operationalized by the 'Immersive Learning Brain' and ‘Immersion Cube’ frameworks. This approach offers a comprehensive guide through the intricacies of immersive educational experiences and spotlighting research frontiers, along the immersion dimensions of system, narrative, and agency. Our discourse extends to stakeholders beyond the academic sphere, addressing the interests of technologists, instructional designers, and policymakers. We span various contexts, from formal education to organizational transformation to the new horizon of an AI-pervasive society. This keynote aims to unite the iLRN community in a collaborative journey towards a future where immersive learning research and practice coalesce, paving the way for innovative educational research and practice landscapes.
ESA/ACT Science Coffee: Diego Blas - Gravitational wave detection with orbita...Advanced-Concepts-Team
Presentation in the Science Coffee of the Advanced Concepts Team of the European Space Agency on the 07.06.2024.
Speaker: Diego Blas (IFAE/ICREA)
Title: Gravitational wave detection with orbital motion of Moon and artificial
Abstract:
In this talk I will describe some recent ideas to find gravitational waves from supermassive black holes or of primordial origin by studying their secular effect on the orbital motion of the Moon or satellites that are laser ranged.
Current Ms word generated power point presentation covers major details about the micronuclei test. It's significance and assays to conduct it. It is used to detect the micronuclei formation inside the cells of nearly every multicellular organism. It's formation takes place during chromosomal sepration at metaphase.
The technology uses reclaimed CO₂ as the dyeing medium in a closed loop process. When pressurized, CO₂ becomes supercritical (SC-CO₂). In this state CO₂ has a very high solvent power, allowing the dye to dissolve easily.
The cost of acquiring information by natural selectionCarl Bergstrom
This is a short talk that I gave at the Banff International Research Station workshop on Modeling and Theory in Population Biology. The idea is to try to understand how the burden of natural selection relates to the amount of information that selection puts into the genome.
It's based on the first part of this research paper:
The cost of information acquisition by natural selection
Ryan Seamus McGee, Olivia Kosterlitz, Artem Kaznatcheev, Benjamin Kerr, Carl T. Bergstrom
bioRxiv 2022.07.02.498577; doi: https://doi.org/10.1101/2022.07.02.498577
Describing and Interpreting an Immersive Learning Case with the Immersion Cub...Leonel Morgado
Current descriptions of immersive learning cases are often difficult or impossible to compare. This is due to a myriad of different options on what details to include, which aspects are relevant, and on the descriptive approaches employed. Also, these aspects often combine very specific details with more general guidelines or indicate intents and rationales without clarifying their implementation. In this paper we provide a method to describe immersive learning cases that is structured to enable comparisons, yet flexible enough to allow researchers and practitioners to decide which aspects to include. This method leverages a taxonomy that classifies educational aspects at three levels (uses, practices, and strategies) and then utilizes two frameworks, the Immersive Learning Brain and the Immersion Cube, to enable a structured description and interpretation of immersive learning cases. The method is then demonstrated on a published immersive learning case on training for wind turbine maintenance using virtual reality. Applying the method results in a structured artifact, the Immersive Learning Case Sheet, that tags the case with its proximal uses, practices, and strategies, and refines the free text case description to ensure that matching details are included. This contribution is thus a case description method in support of future comparative research of immersive learning cases. We then discuss how the resulting description and interpretation can be leveraged to change immersion learning cases, by enriching them (considering low-effort changes or additions) or innovating (exploring more challenging avenues of transformation). The method holds significant promise to support better-grounded research in immersive learning.
The binding of cosmological structures by massless topological defectsSérgio Sacani
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
When I was asked to give a companion lecture in support of ‘The Philosophy of Science’ (https://shorturl.at/4pUXz) I decided not to walk through the detail of the many methodologies in order of use. Instead, I chose to employ a long standing, and ongoing, scientific development as an exemplar. And so, I chose the ever evolving story of Thermodynamics as a scientific investigation at its best.
Conducted over a period of >200 years, Thermodynamics R&D, and application, benefitted from the highest levels of professionalism, collaboration, and technical thoroughness. New layers of application, methodology, and practice were made possible by the progressive advance of technology. In turn, this has seen measurement and modelling accuracy continually improved at a micro and macro level.
Perhaps most importantly, Thermodynamics rapidly became a primary tool in the advance of applied science/engineering/technology, spanning micro-tech, to aerospace and cosmology. I can think of no better a story to illustrate the breadth of scientific methodologies and applications at their best.
PPT on Direct Seeded Rice presented at the three-day 'Training and Validation Workshop on Modules of Climate Smart Agriculture (CSA) Technologies in South Asia' workshop on April 22, 2024.
Sharlene Leurig - Enabling Onsite Water Use with Net Zero Water
A simulation model of climate effects on plant
1. A simulation model of climate effects on plant
productivity and variability in cauliflower
(Brassica oleracea L. botrytis)
J.E. Olesena,*
, K. Grevsenb
a
Department of Crop Physiology and Soil Science, Research Centre Foulum,
PO Box 50, 8830 Tjele, Denmark
b
Department of Fruit, Vegetable and Food Science, Kirstinebjergvej 6, 5792 Aarslev, Denmark
Accepted 5 May 1999
Abstract
The paper describes a model of cauliflower (Brassica oleracea L. botrytis) growth and
development under conditions where water and nutrients are not limiting. The model consists of
four linked processes: crop development, leaf area expansion, increase in curd diameter and growth
of dry matter. The model aims to describe variability between plants in time of curd initiation and
harvest. Crop development is described as a function of temperature only. Leaf area expansion is
described by a logistic function where growth rate depends on temperature. Temperature and
available carbohydrates control the rate of increase in curd diameter. Dry matter assimilation is a
function of intercepted radiation and of demand for dry matter growth. The assimilates are
distributed among the organs in proportion to their demand. The model was calibrated for the
cultivar Plana using data from a growth chamber experiment and from a field experiment. A
verification of the model against field data showed that the model was able to reproduce variability
in curd diameter, indicating that variability in curd size is caused by variability in time of curd
initiation. # 2000 Elsevier Science B.V. All rights reserved.
Keywords: Brassica oleracea L. botrytis; Growth; Simulation model; Plant variability; Harvest
duration
Scientia Horticulturae 83 (2000) 83±107
* Corresponding author. Tel.: +45-89991659; fax: +45-89991619.
E-mail address: jorgene.olesen@agrsci.dk (J.E. Olesen).
0304-4238/00/$ ± see front matter # 2000 Elsevier Science B.V. All rights reserved.
PII: S0304-4238(99)00068-0
2. 1. Introduction
Growth and development of cauliflower (Brassica oleracea L. botrytis) are
strongly influenced by environmental conditions such as temperature and
radiation (Salter, 1960; Wurr et al., 1990a). CO2 concentration also affects dry
matter accumulation and hence curd weight (Wheeler et al., 1995).
The time from transplanting to harvest can be divided into three phases (Wiebe,
1972a, b; Wurr et al., 1981a): a juvenile phase, a curd induction phase and a curd
growth phase. Environmental variables, especially temperature, influence growth
and development differently in these phases. Consequently the effect of climate
variability on cauliflower production cannot be predicted without first quantifying
and integrating the impact of the environment on both development and growth.
The duration of the various phases of cauliflower development and growth has
previously been described using simple temperature driven models (Wurr et al.,
1990b, 1994; Grevsen and Olesen, 1994a; Pearson et al., 1994). A simple model
for effects of temperature and radiation on leaf area expansion and dry matter
growth in cauliflower was presented by Olesen and Grevsen (1997).
The variability in growth and development of individual plants (plant
variability) is an important aspect of many horticultural crops including
cauliflower as it affects the product quality and the harvesting process. However,
no attempts have been made to describe effects of climate on plant variability
through the use of dynamic simulation modelling, for example on length of the
harvest period in cauliflower. The length of the cutting period is one of the major
aspects of cauliflower production as it directly influences the costs of the
harvesting operation, and the harvesting costs constitute a large fraction of the
total costs of production (Wheeler and Salter, 1974). A large proportion of the
variation in duration of the harvest period can be attributed to variation in the
duration of curd induction and in temperature during curd growth (Booij, 1990).
Attempts have been made to reduce the length of the harvest period by cold
treatment before transplanting with variable success (Salter and Ward, 1972,
1974; Wiebe, 1975; Wurr et al., 1981b, 1982). The different effects of cold
treatment may be due to the timing of the treatments relative to the crop growth
phases.
A model incorporating effects of environment on both crop growth and
development including plant variability may be used for assessing the
performance of crops under changing environmental conditions such as those
implied by the enhanced greenhouse effect. Cauliflower is a short rotation crop
that is grown throughout the season in many parts of Europe. Such a model may
therefore also be suited for analysis and prediction of crop responses to current
seasonal variation in temperature and radiation.
This paper describes a model for cauliflower growth and development. Growth
in field conditions where water and nutrients are not limiting are simulated,
84 J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107
3. because cauliflower is a high value crop, which in many European countries is
grown under conditions of good water and nutrient supply. The model is
calibrated for the cultivar Plana using data from controlled environments and
from field experiments.
2. Materials and methods
2.1. Model description
The model simulates crop growth and development in a dynamic way, and also
treats variability between plants in the time of curd initiation and harvest. The
model includes four main processes: crop development, leaf area expansion,
increase in curd volume and increase of dry matter. The links between these
processes are illustrated in Fig. 1. The model follows the supply-demand
approach (Gutierrez, 1996) and is structured into a hierarchy of metabolic pools
(Holst et al., 1997). The current state of the crop sets its demands for resources
(carbohydrates) as a function of growth stage and rate of area expansion. The
demand, together with resource availability, sets the supply.
Simulations are started at transplanting, and the model requires initial
information on date of transplanting and on initial leaf area, top dry weight
and root dry weight. In addition plant density must be defined. The model uses
daily minimum and maximum air temperature and global radiation. The
minimum and maximum temperatures are converted to hourly temperatures
assuming a sinusoidal diurnal variation (Allen, 1976).
Fig. 1. Outline of model structure. Model states are indicated by rectangular boxes, processes and
rates by ovals and effects of temperature (T) and global radiation (Q) by circles. Arrows with full
lines indicate flow of assimilates, and arrows with broken lines indicate direction of information
flow.
J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107 85
4. A list of model variables is given in Appendix A, and the model parameters for
cv. Plana are listed in Appendix B.
2.2. Plant organs
Four separate plant organs are considered in the model: roots, stems, leaves and
curds (Fig. 1). All organs are assumed to have a pool of structural dry matter: Wr,
Ws, Wl and Wc (g plantÀ1
) for roots, stems, leaves and curds, respectively. In
addition stems and leaves are assumed to share a pool of reserves (R) (g plantÀ1
).
These organs are assumed to have a capacity for reserve storage (Rc) (g plantÀ1
)
which is set proportional to the weight of structural components:
Rc ˆ aE…Ws ‡ Wl†Y (1)
where aE is a nondimensional constant.
Leaves also have an area (A) (m2
plantÀ1
). Only active green leaves are
considered in the model. Leaves and roots are assumed to have a turn over of dry
matter, whereas dry matter simply accumulates in stems and curds. The ageing of
leaves and roots is described by the distributed delay procedure (Manetch, 1976),
where mass or area flow through a number of age classes from young to old.
Mass entering class 1 at time t will emerge from the last age class (K) at time t‡s
on the average. The spread in developmental times around the average is
described by an Erlang distribution with variance s2
/K.
The ageing of the leaf area and of leaf mass is described by distributed delay
procedures with identical parameters. A temperature sum with a base temperature
of Tblˆ1.98C is used. This is the base temperature for leaf appearance in
cauliflower (Olesen and Grevsen, 1997). The mean age of a leaf at senescence is
called Sl, and the number of classes in the distributed delay procedure is set to
Klˆ30 as suggested by Graf et al. (1990). Leaf death is assumed only to affect
structural leaf dry matter and not the pool of reserves.
Root mass is also handled by a distributed delay procedure. A temperature sum
with a base temperature of Tbrˆ08C is used to describe the ageing of roots. The
mean age of root dry matter is set to Srˆ3008Cd based on root turnover rates in
cauliflower reported by Greenwood et al. (1982). The number of age classes is
arbitrarily set to Krˆ20.
A cauliflower curd is assumed to have the shape of a half sphere with radius
(rc) (mm) and height (hc) (mm) (Kieffer et al., 1998). The curd height is not
necessarily identical to the radius, and the curd shape is therefore not strictly a
hemisphere. The volume of the curd (Vc) (mm3
) is then calculated as
Vc ˆ 2
3 %r2
c hcX (2)
86 J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107
5. The height is assumed to be proportional to the radius, i.e.
hc ˆ chrcY (3)
where ch is a nondimensional constant.
Fresh weights of curds (Fc) and of leaves and stems (Fv) (g plantÀ1
) are
calculated using empirical relationships:
Fc ˆ afWc ‡ bfVcY (4)
Fv ˆ cf…Ws ‡ Wl† ‡ efRY (5)
where af, cf and ef are nondimensional constants, and bf is a constant (g mmÀ3
).
2.3. Crop development
The hourly crop developmental rate (dÇ/dt) is defined as (Grevsen and Olesen,
1994a):
dÇ
dt
ˆ
fd1…Th† Ç ` 1
fd2…Th† 1 Ç ` 2
fd3…Th† 2 Ç
V
`
X
(6)
where fd1, fd2 and fd3 are temperature response functions for the juvenile, curd
induction and curd growth phases, respectively, and Th is hourly temperature (8C).
Ç is the current developmental stage of the crop, ranging from 0 at transplanting
to 3 at end of curd growth. Ç is 1 at end of juvenility, and 2 at time of curd
initiation.
Crop development during the juvenile phase (fd1) is described by a simple
temperature sum with a base temperature of Tdb1ˆ08C and a requirement of
Sd1ˆ83.38Cd in the cv. Plana (Grevsen and Olesen, 1994a). Crop development
during the curd induction phase (fdb2) is described by symmetrical linear
responses to temperature below and above an optimum temperature (Grevsen and
Olesen, 1994a). Grevsen and Olesen (1994b) estimated base and optimum
temperatures of Tdb2ˆ5.18C and Tdo2ˆ15.58C, respectively, and a requirement of
Sd2ˆ108.28Cd in Plana. These values are close to those found by Wheeler et al.
(1995). The duration of the curd growth phase (fd3) is described by a temperature
sum with a base temperature of Tdb3ˆ08C and a requirement of Sd3ˆ10508Cd.
These values were taken from Pearson et al. (1994) as the average of estimates for
three cultivars.
The ageing of plants from transplanting to curd initiation is described by the
distributed delay procedure. Separate delay procedures are used for the juvenile
and the curd induction phases with Kd1 and Kd2 age classes in the delay
procedures, respectively. Plant variability before curd initiation is thus handled
through the use of distributed delay procedures. After curd initiation the
variability is handled through the use of a number of curd cohorts. The growth
J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107 87
6. and development of each cohort is treated separately, whereas before curd
initiation only variability in development is handled in the distributed delay
procedures.
Crop development is updated in hourly steps, and the number of plants
reaching curd initiation is accumulated. If this number exceeds 0.2% of the total
number of plants then a new cohort of curds is generated with an initial curd
diameter of 0.6 mm (Salter, 1969; Wiebe, 1972c). The curd cohorts are all
handled separately.
2.4. Leaf area expansion
The leaf area includes both leaf blades, stalks and midribs although the last two
components do not contribute fully to the photosynthetic active area. Stalks and
midribs constitute about 9% of the total leaf area (Olesen and Grevsen, 1997).
The expansion rate of leaf area (dA/dt) (m2
plantÀ1
dÀ1
) is assumed to be
described by a logistic equation scaled by the vegetative supply demand ratio
(ÈV):
dA
dt
ˆ alA
…Lxad À A†‡
Lxad
fA…Td†ÈVY (7)
where al is the maximum relative expansion rate (dÀ1
), Td the mean daily air
temperature (8C), fA a function of daily mean temperature (0±1), d the plant
density (plants mÀ2
), and Lx the maximum leaf area index (m2
mÀ2
) which
depends on available nitrogen (Grindlay, 1997; Booij et al., 1996). The suffix ‡
denotes that only positive contributions are considered. Lx is set to 6 (van den
Boogard and Thorup-Kristensen, 1997). The effect of temperature on leaf area
expansion rate (fA) is described by the function estimated for Plana by Olesen and
Grevsen (1997), and al is set to 0.179 (Olesen and Grevsen, 1997). The leaf area
is updated in daily time steps using Euler integration.
2.5. Curd volume growth
The maximum growth rate of the curd radius (drc/dt)x is assumed to decline
linearly with crop age during the curd growth phase (Pearson et al., 1994) and
increase linearly with temperature:
drc
dt
x
ˆ ac…3 À dž‡…Th À Tb3†‡rcY (8)
where ac is the maximum relative radius growth rate ((8Cd)À1
). Knowing the
maximum radius growth rate, the maximum daily increase in volume (ÁxVc) may
be calculated using Euler integration in hourly time steps.
88 J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107
7. The actual growth of curd volume is detemined by the vegetative supply
demand ratio (ÈV) which is identical to the supply demand ratio for growth of
curd dry matter:
ÁVc ˆ ÁxVc‰1 À …1 À ÈV†bc
ŠY (9)
where bc is a nondimensional constant. The actual growth in radius is then
calculated by converting the volume growth to radius growth.
2.6. Demands for dry matter growth
The demand rate for growth (D) (g mÀ2
dÀ1
) is composed of five demands
D ˆ Dr ‡ Ds ‡ Dl ‡ Dc ‡ DEY (10)
where Dr is the demand rate for growth of structural dry matter in roots
(g mÀ2
dÀ1
), Ds the demand rate for growth of structural dry matter in stems
(g mÀ2
dÀ1
), Dl is the demand rate for growth of structural dry matter in leaves
including stalks and midribs (g mÀ2
dÀ1
), Dc the demand rate for curd growth
(g mÀ2
dÀ1
), and DE is the demand rate for growth of reserves (g mÀ2
dÀ1
).
Conversion costs are ignored as these are assumed to be approximately identical
for all demand types. Respiration costs are also ignored as the ratio of respiration
to photosynthesis has been found to be constant over a wide range of
temperatures (Gifford, 1995; Dewar, 1996).
The demand rate for growth of leaves, stalks and midribs is assumed to have
two components. One component is related to growth of new leaf area, and one is
related to growth of secondary structures in the leaves:
Dl ˆ d‰slÁAx ‡ aD…slxA À Wl†‡fp…Td†ŠY (11)
where sl is the weight of new leaf area (g mÀ2
), slx is the maximum weight of leaf
area (g mÀ2
), aD is a constant ((8Cd)À1
), d the plant density (plant mÀ2
), ÁAx is
the maximum daily increase in leaf area (m2
dÀ1
plant-
), and fP is the function of
mean daily temperature (0±1) which is also used to adjust assimilation (Eq. (16)).
slx is assumed to be twice the weight of new leaf area (sl), and this weight is
assumed to be attained in 25 days at optimal temperature for assimilation. This
implies that aDˆ0.04 dÀ1
.
The mass of above and below ground vegetative organs are assumed to be in
balance, and the demand rate for root growth is calculated such that this balance
is maintained:
Dr ˆ dbD…cD…Wl ‡ Ws† À Wr†‡Y (12)
where bD is a constant which is arbitrarily set to 1. The ratio of root to leaf weight
is set to cDˆ0.11 based on data from Bligaard (1996).
J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107 89
8. Stem structural dry matter is assumed to be proportional to plant top fresh
weight giving the following demand rate for stem growth:
Ds ˆ dbD…eD…Fv ‡ Fc† À Ws†‡Y (13)
where eD is a nondimensional constant.
The demand rate for curd growth is assumed to be proportional to the
maximum volume increase:
Dc ˆ d‰cc ‡ ec…3 À dž‡ŠÁxVcY (14)
where cc and ec are constants (g mmÀ3
).
The demand rate for growth of reserves depends on the remaining capacity for
reserve storage and on the size of the stem and leaf organs:
DE ˆ d min‰bE…Rc À R†Y cE…Wl ‡ Ws†ŠY (15)
where bE and cE are constants (dÀ1
).
2.7. Dry matter assimilation
The fraction of intercepted PAR () is calculated using an extinction coefficient
which decreases with increasing plant leaf area (Olesen and Grevsen, 1997).
Daily net assimilation (Pa) (g mÀ2
dÀ1
) is calculated using the concept of a
radiation conversion coefficient () (g MJÀ2
) and an effect of sink limitation:
Pa ˆ min‰DY fP…Td†QŠY (16)
where D is the demand rate for dry matter growth (g mÀ2
dÀ1
), Q the
photosynthetic active radiation (MJ mÀ2
dÀ1
), and fP is a function of daily mean
temperature (0±1) which is taken to be the function estimated by Olesen and
Grevsen (1997) for effect on radiation conversion efficiency. is assumed to be a
linear function of mean daily PAR intensity Qi (W mÀ2
], which is calculated by
dividing Q by the day length:
ˆ 1 ‡ 2QiY (17)
where 1 and 2 are constants, which were estimated as 1ˆ5.44 g MJÀ2
and
2ˆÀ0.123 g MJÀ2
WÀ1
m2
from data published by Olesen and Grevsen (1997)
for cauliflower corrected for an additional 9% to root dry matter.
The assimilates available for partitioning (P) (g mÀ2
dÀ1
) is the sum of the net
assimilation and a contribution from the plant reserves (PE) (g mÀ2
dÀ1
):
P ˆ Pa ‡ PEX (18)
90 J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107
9. The contribution of reserves to the growth of various organs is assumed to
depend on both supply and demand (Gutierrez and Baumgaertner, 1984):
PE ˆ …D À Pa† 1 À exp À
EdR
D À Pa
!
Y (19)
where E defines the mobilisation rate of reserves which is set to 0.15 dÀ1
in line
with experience reported by Penning de Vries et al. (1989). The dry matter
growth is partitioned between the organs (roots, stems, leaves and curd) in
proportion to their demand. A fraction of the reserve demand (eEDE) is assumed
to be distributed with the same priority as the vegetative organs. Any assimilates
in excess of that are partitioned to reserves. All organs are thus considered as
being vegetative even if not conventionally so, and the vegetative supply demand
ratio (ÈV) is thus calculated as:
ÈV ˆ min‰Pa…D À …1 À eE†DE†Y 1ŠX (20)
In an experiment with defoliation of cauliflower plants, van den Boogard and
Thorup-Kristensen (1999) found that the total sugar and starch content of
cauliflower leaves, midribs and stems never became lower than 10%. Assuming
that the reserve demand on average is identical to the sum of all vegetative
demands, this gives eEˆ0.1.
Growth of dry matter and actual curd size is calculated in daily time steps using
Euler integration. Each curd cohort is handled separately and assumed to have its
own reserves, but the assimilation is calculated at the stand level.
2.8. Experimental data
Data from two experiments were used to calibrate the model.
2.8.1. Experiment 1
Olesen and Grevsen (1997) conducted an experiment on cauliflower in growth
chambers which provided control of air temperature, air humidity and light
intensity. Nine different treatments with varying temperatures and irradiances
were included in the experiment (Table 1). All treatments were conducted using a
16 h day and 8 h night.
Seeds of summer cauliflower cv. Plana F1 (Royal Sluis) were sown in nutrient
enriched peat soil in rectangular pots with a surface of 30Â40 cm and a depth of
40 cm. The soil was watered to full capacity at time of sowing and subsequently
watered every second day. After sowing all pots were placed under identical
conditions until the plants had reached about 10 initiated leaves. At this time the
plants were thinned to about 6±10 plants per pot. Five pots were then placed in
each chamber and the treatments were initiated.
J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107 91
10. Samples were taken once or twice per week. This meant that the plant density
in the pots was successively reduced. The first sample was taken at onset of the
treatments. Each plant was dissected into stems, leaf blades, midribs and stalks.
Leaf area was measured, and the weight of the each organ was determined before
and after oven drying at 808C for 24 h. The apex diameter of each plant was
determined with a binocular microscope (magnification Â50) after dissection.
Curd initiation was defined as the time when the apex had reached a diameter of
0.6 mm (Salter, 1969; Wiebe, 1972a) and determined by linear interpolation of
the logarithm of apex diameter against time. The duration of the experimental
treatment until curd initiation is shown in Table 1.
2.8.2. Experiment 2
Six transplantings were conducted in the field at Research Centre Aarslev in
Denmark in 1995 using cauliflower cv. Plana (Table 2). Seeds were sown in peat
Table 1
Summary of treatments in the growth chamber experiment on cauliflower reported by Olesen and
Grevsen (1997). The durations from start of experimental treatment until curd initiation and until
the last sampling are shown
Number Mean temperature
(8C)
Daily PAR
(mol mÀ2
)
Duration (days) Number
of samples
Curd initiation Experiment
1 7.0 20.4 39 43 7
2 10.7 20.4 24 27 7
3 14.3 9.3 20 38 10
4 14.3 19.1 21 35 7
5 14.3 32.7 22 38 10
6 14.3 50.8 21 38 10
7 18.0 19.1 26 27 8
8 21.7 19.1 18 20 7
9 25.3 19.1 27 27 8
Table 2
Dates of transplanting, curd initiation and final sample of cauliflower at Aarslev Research Centre in
1995
Planting Transplanting Curd initiation Last sample
1 21 April 24 May 11 July
2 16 May 7 June 29 July
3 7 June 30 June 9 August
4 30 June 25 July 7 September
5 1 August 28 August 23 October
6 21 August 11 September 9 November
92 J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107
11. blocks (5 cm  5 cm  5 cm) and nursery plants were raised under glasshouse
conditions with a minimum temperature of 128C. Transplants with about 10
initiated leaves were conditioned outside in sheltered frames for preferably 5±7
days before transplanting on a sandy loam at Aarslev. The plant density was 6.25
plants mÀ2
. The plant density in transplanting 5 was reduced to approximately 4
plants mÀ2
due to severe attack of cutworms (Agrotis segetum Schiff.).
Fertilisation and irrigation followed guidelines for normal production. A basic
fertilisation of 40 kg P haÀ1
and 200 kg K haÀ1
was applied to the experimental
area. Each transplanting received 150 kg N haÀ1
in calcium ammonium nitrate at
planting followed by 100 kg N haÀ1
in urea 30±40 days after planting.
Samples of 10±40 plants were taken at weekly or biweekly intervals by cutting
plants at the soil surface. The samples were used to determine plant and curd
fresh weights. The dry matter content of subsamples was determined after oven
drying at 808C for 24 h. The area of leaf blades was measured on the subsamples.
Apex diameter was determined by dissection and measurement under stereo
microscope. Curd initiation was determined as in Experiment 1. The diameter and
height of the curd was measured. Meteorological data were taken from the
national meteorological station at Aarslev (10827H
E, 55818H
N) within 500 m of the
experimental site.
2.9. Parameter estimation
Some model constants (af, bf, cf, df, ch, eD) were estimated by multiple linear
regression using the procedure GLM with the no intercept option in the SAS
statistical package (SAS Institute, 1988).
Estimation of aE, cf, ef, bE and cE required observations of plant reserves using
data from Experiment 1. The reserve content (R) was calculated as the difference
between observed stem and leaf dry weights and model estimates of Wl‡Ws. Leaf
structural weight (Wl) was calculated from Eq. (11) using observed leaf area
fitted by a logistic function Eq. (21) to estimate increase in leaf area. It was
assumed that leaf area expansion was not restricted by assimilate supply. Stem
structural dry weight was assumed to be proportional to above ground fresh
weight Eq. (13).
The leaf area development in Experiment 1 was described by a logistic
equation fitted to the observed data (Thornley, 1990):
A ˆ
Ax
1 ‡ exp…a À bt†
Y (21)
where t is number of days from onset of experiment, Ax is the maximum leaf area
(m2
plantÀ1
), and a and b are constants. a may be substituted by ln((AxÀAo)/Ao),
where Ao is leaf area at onset of the treatment. The constants were estimated by
nonlinear regression using the NLIN procedure of SAS (SAS Institute, 1988). The
J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107 93
12. observed values of Ao were used, and Ax was set to 0.6 m2
(Olesen and Grevsen,
1997).
Some model constants (sl, ac and bc) were estimated by running a reduced form
of the model and minimizing the squared difference between observed and
simulated values of either plant leaf area, plant dry weight or curd radius. A
square root transformation was applied to both observed and simulated values of
leaf area, dry weight or curd radius to obtain variance homogeneity. The
simulated values were calculated using subsets of the entire model. A grid
analysis and the downhill simplex method (Nelder and Mead, 1965) were used for
minimizing the difference.
The number of age classes in the distributed delay procedures for crop
development (Kd1 and Kd2) was estimated by adjusting these parameters to
match observed standard deviation in date of curd initiation. Kd1 and Kd2 were
assumed to be identical. Data from treatments 3, 5 and 6 in experiment 1
were used as these were conducted at identical temperatures from the same
set of nursery plants. The curd initiation date was estimated for each plant as the
time when curd diameter was 0.6 mm using the measured apex diameter (dc) and
a linear relationship between ln(dc) and number of days from onset of
experimental treatments (t). The following relationship was estimated using
mean sample apex diameter from the four plant samples embracing date of curd
initiation:
ln…dc† ˆ À6X31 ‡ 0X260tX (22)
Some model constants were subjectively estimated by either using the
characteristics of a few plant samples (Sl) or by visually fitting a line through
selected data points (cc, ec, bE and cE).
3. Results
3.1. Model calibration
The model parameter estimates are described here in the order in which they
were introduced in the model description section. An overview of all model
parameters is given in Appendix B.
The highest observed ratio of reserves to structural top dry matter was 2.4 in the
treatment with the highest irradiance in Experiment 1. The plants had clear
symptoms of reduced growth rate under these conditions indicating that the
capacity for reserve storage was reached. aE in Eq. (1) is thus set to 2.5.
The average age of the first true leaf was found to be 48 days at a mean daily
temperature of 14.38C in Experiment 1. This gives an average leaf area duration
in thermal time of Slˆ5958Cd.
94 J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107
13. The ratio of curd height to curd radius Eq. (3) was estimated by linear
regression as chˆ1.34 (s.e.ˆ0.004) using all measurements of single curds from
Experiment 2.
The constants for estimating curd fresh weight Eq. (4) were estimated by
multiple linear regression as afˆ10.4 (s.e.ˆ0.33) and bfˆ0.077 (s.e.ˆ0.011)
g cmÀ3
using all measurements of single curds from Experiment 2.
The constants for estimating fresh weight of vegetative organs Eq. (5) were
estimated by multiple linear regression as cfˆ10.7 (s.e.ˆ0.19) and efˆ4.5
(s.e.ˆ0.45) using all mean sample values from Experiment 1 prior to curd
initiation.
The data from the four sample dates embracing date of curd initiation in
treatments 3, 5 and 6 in Experiment 1 was used to estimate Kd1 and Kd2 under the
assumption that these constants are identical. The measured standard deviation in
date of curd initiation was 2.59 (nˆ57). This variability was matched by the
distributed delay procedure by setting Kd1ˆKd2ˆ26.
The constants in Eqs. (8) and (9) for calculating curd expansion were estimated
using data from Experiment 2. The constants were estimated simultaneously as
acˆ0.0123 (8Cd)À1
and bcˆ2.9 by minimizing the squared difference between
simulated and observed mean sample curd radius. Increase in curd radius was
simulated from the observed date of curd initiation using Eqs. (8) and (9). The
supply demand ratio (ÈV) was calculated using Eq. (20), and using observed plant
dry matter interpolated linearly to estimate daily supply. The leaf area in Eq. (11)
was taken to be the observed plant leaf area fitted by a logistic equation Eq. (20).
The weight of new leaf area (sl) was estimated at 44.7 g mÀ2
by minimizing the
difference between observed and simulated leaf weight using data from the first
21 days of treatment 3 in Experiment 1. This treatment was carried out at low
irradiance and it was assumed that no reserves were accumulated during this
period. It was also assumed that assimilate supply did not restrict growth of
secondary leaf structures. Leaf dry weight was simulated by Eq. (11) using
observed leaf area fitted by a logistic function Eq. (21).
The ratio of stem dry weight to plant top fresh weight Eq. (13) was estimated
as eDˆ0.010 (s.eˆ0.00024) by linear regression of mean sample stem dry weight
against plant top fresh weight using data from Experiment 1.
The constants for calculating maximum curd density Eq. (14) were estimated
as acˆ0.005 and bcˆ0.12 g cmÀ3
by visually fitting a line through the highest
curd densities from Experiment 2 on a plot of mean sample curd density versus
accumulated temperature from curd initiation.
The constants for calculating reserve demand rate Eq. (15) were estimated as
bEˆ0.075 and cEˆ0.12 dÀ1
using data from Experiment 1 prior to curd initiation.
bE was estimated as the slope of a line visually fitted through the highest data
points on a plot of rate of increase of reserve dry matter to remaining capacity for
reserve storage (RcÀR). cE was estimated as the slope of a line visually fitted
J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107 95
14. through the highest data points on a plot of rate of increase of reserve dry matter
to structural dry matter in leaves and stem.
3.2. Model verification
The calibrated model was used to simulate crop growth and development for
the six plantings in Experiment 2. These experimental data were used to calibrate
the curd growth parameters only. Curd growth is affected by dry matter
accumulation in the model, but the reverse is not the case. The data may therefore
be used to verify the model's simulations of dry matter accumulation. These
experimental data were not used to estimate the parameters related to plant
variability and may therefore also be used to verify the model's simulation of
variability in curd diameter.
The simulation of curd growth is very sensitive to the simulated timing of curd
initiation. The simulation of crop development was therefore adjusted to match
observations, so that the verification of crop growth was not affected by errors in
simulation of development. This was done by adjusting the length of the juvenile
phase to fit the observed dates of curd initiation. The time course of simulated
and observed values are shown for each transplanting in Figs. 2±4 for plant leaf
area, top dry matter and standard deviation of curd diameter, respectively.
Figs. 2 and 3 shows a large variation in growth rate between the different
plantings related to time of year. There was for all plantings a good relationship
between observed and simulated leaf area and top dry matter.
Fig. 4 shows that simulated standard deviation of curd diameter increased with
time reaching a maximum and then declined again as curd relative growth rate
declined with age. There is a good agreement between observed and simulated
results, except for transplanting 4. The decline in standard deviation with age was,
however, not as clear in the observed data as in the simulated results.
4. Discussion
The model incorporates the development model previously described by
Grevsen and Olesen (1994a). The model uses a declining relative rate of increase
in curd diameter with accumulated temperature from curd initiation as suggested
by Pearson et al. (1994). This produces results which are comparable to the use of
a quadratic relationship between the logarithm of curd diameter and accumulated
temperature as suggested by Wurr et al. (1990b). Pearson et al. (1994)
additionally assumed that curd growth rate had an instantaneous optimum
temperature which was found to vary from 168C in cv. Jubro to 258C in cv.
Revito. The present model does not explicitly assume an optimum temperature
for curd growth. The increase in curd diameter is, however, reduced if the demand
96 J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107
15. for growth of curd dry matter cannot be met by the supply. At high temperatures
this will result in reduction in rate of increase of curd diameter with increasing
temperature as assimilation does not increase with temperature for temperatures
above 148C.
The plant variability is simulated by introducing variability in the juvenile and
curd induction phases using distributed delay procedures. The growth of single
curd cohorts from curd initiation and onwards are simulated using deterministic
procedures with no new source of variability. The time course of simulated
standard deviation of curd diameter matched the observations with the exception
of transplanting 4 where simulated curd diameters also were higher than observed
(Fig. 4). In most cases the simulated standard deviation reached its maximum at a
curd diameter of about 10 cm.
Fig. 2. Measured (points) and simulated (lines) time course of mean plant leaf area for each of the
six plantings at Aarslev. The length of the juvenile phase was adjusted to match the observed date of
curd initiation in each of the six plantings.
J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107 97
16. The simulated decline in standard deviation was not fully supported by the data
(Fig. 4). This may indicate that the simulated duration of the curd growth period
was too short. This growth period was not estimated for Plana, but taken from
other cultivars.
The agreement between simulated and observed variability of curd diameter
confirms the assumption that this variability is mainly caused by variation in time
of curd initiation. Booij (1990) found that the majority of the variation in duration
of the harvest period could be explained by the combined effect of variation in
duration of curd initiation and in temperature during curd growth.
The use of the distributed delay procedure provides a convenient way of
introducing variability in maturation rates into an otherwise deterministic model.
Plant and Wilson (1986) discussed the use of this and alternative formulations of
age structured populations. Sequira et al. (1993) also used the distributed delay
Fig. 3. Measured (points) and simulated (lines) time course of mean plant top dry weight for each
of the six plantings at Aarslev. The length of the juvenile phase was adjusted to match the observed
date of curd initiation in each of the six plantings.
98 J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107
17. procedure to include variability in an existing model of cotton growth and
development.
The expansion of leaf area is assumed to be largely independent of the growth
of dry matter as found by Olesen and Grevsen (1997). This independency gives a
potential for large variations in specific leaf area which has been found to depend
on irradiance level (Olesen and Grevsen, 1997) and on CO2 concentration
(Wheeler et al., 1995). Some crop models (e.g. Spitters et al., 1989; Graf et al.,
1990) calculate the expansion of leaf area from increase in leaf dry matter by
assuming a constant or age dependent specific leaf area. This has been found to
give satisfactory descriptions in crops where branching depends on available
assimilates. Cauliflower does not form branches, and a large fraction of the
carbohydrate reserves are stored in the leaves. The use of a constant specific leaf
Fig. 4. Measured (points) and simulated (lines) time course of standard deviation of curd diameter
for each of the six plantings at Aarslev. The length of the juvenile phase was adjusted to match the
observed date of curd initiation in each of the six plantings.
J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107 99
18. area in this crop may result in an unrealistic positive feedback between
assimilation and leaf area expansion.
The model uses a radiation conversion coefficient to convert solar radiation to
dry matter growth. The model does thus not specifically include the photosynthesis
and respiration processes, because several studies have shown that the ratio of
respirationtophotosynthesisisconstantinmanycrops(Gifford,1995;Dewar,1996).
Exceptions are crops where large changes in chemical composition occur during
development, e.g. from carbohydrate storage to storage of proteins or lipids
(Arkebauer et al., 1994).Nosuchchangeoccur in cauliflower, and the use ofa simple
radiation conversion scheme can therefore be justified.
The value of the radiation conversion coefficient used is not assumed to be
constant. The coefficient declines with increasing light intensity as experimen-
tally shown by Olesen and Grevsen (1997) for cauliflower and by Wheeler et al.
(1993) for lettuce. The obtained coefficients are similar to those typically found
under field conditions during summer in Northern Europe (Monteith, 1977;
Gallagher and Biscoe, 1978; Wheeler et al., 1995). The use of a dependency on
average daily light intensity will cause the estimated conversion coefficient to be
higher at higher latitudes and lower at lower latitudes as empirically shown for
wheat (Jamieson et al., 1998). The coefficient is also effectively reduced, if
calculated supply exceeds the demand Eq. (16). This may lead to an additional
downregulation at high irradiance.
The model gave a realistic simulation of leaf area expansion and dry matter
growth of six different transplantings in the field (Figs. 2 and 3). This shows that
model parameters and relationships obtained from controlled environments can
be successfully applied to field grown crops provided the crops in the controlled
environments are grown in semi-stands and under realistic light conditions.
The function of the demands is not only to regulate assimilation, but also to
serve as a mechanism for partitioning assimilates between the various organs.
Many crop models use a simple priority scheme or a set of age dependent
partitioning coefficients (e.g. Weir et al., 1984; Spitters et al., 1989). The use of
supply-demand ratios give a simple way of simulating plant functional responses
on assimilate partitioning (Graf et al., 1990; DeJong and Grossman, 1994).
The model assumes that all organs get a share of the supply in proportion to
their demand. The curd is thus not assumed to have a higher priority than
vegetative organs. Such a higher priority is usually assumed for reproductive
organs (Gutierrez, 1996). The curd is, however, not a true reproductive organ, but
rather an extension of the stem upon which the flowers develop. The change in
dry matter partitioning with time does thus not reflect a higher priority for
assimilates to the curd, but a dramatically increasing demand for growth of curd
dry matter as the curd diameter increases.
The structural leaf dry matter is assumed to be composed of primary and
secondary cell wall material. A similar model concept was used by Lainson and
100 J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107
19. Thornley (1982) for modelling leaf expansion in cucumber. New leaf area will
thus generate a demand for primary structures, whereas thickening of existing
leaves contributes to the demand for secondary structures.
The demands for growth of root and stem dry matter are based on concepts of
balances between various organs. Root dry matter is thus assumed to be
proportional to leaf structural dry matter in leaves and stems. The rationale
behind this is a balance between above ground CO2 assimilation and below
ground uptake of water and nutrients which is reflected in similar sizes of the
assimilative organs, leaves/stems and roots. Stem dry matter is assumed to be
proportional to total top fresh weight, because stems must contain structures to
support this weight.
A fraction of the demand for reserves is distributed with the same priority as
the vegetative organs. The supply in excess of the vegetative demand is simply
accumulated in the pool of reserves. This approach follows concepts of
accumulation and of reserve formation suggested by Chapin et al. (1990).
Accumulation is the increase in compounds that do not directly promote growth,
whereas reserve formation is a metabolically regulated process of storage
formation from resources that might otherwise promote growth.
Vegetative top fresh weight was estimated to be a linear function of structural
dry matter and of reserves. The simulated dry matter contents may thus vary from
10.7% in plants with no reserves to 22.0% in plants saturated with reserves. The
curd fresh weight was estimated to be a linear function of curd dry matter and
curd volume. This results in a reduction in dry matter content of curds if the curd
demand for growth cannot be fulfilled.
The model may be used for predicting time of crop maturity and for design of
schedules for crop planting. Simpler models have already been developed for this
purpose (Wurr et al., 1990b; Pearson et al., 1994). The present model also
simulates growth of dry matter and fresh weight which are important elements of
crop yield and quality. The simulation of curd expansion and of dry matter growth
may form a conceptual basis for modelling quality defects, which depend on
some of the dynamic variables in the model (Olesen and Grevsen, 1993). The
model may also be used for evaluating effects of climate variability and climate
change on cauliflower production.
Acknowledgements
This work was funded under contract EV5V-CT93-0294 of DGXII of the
European Commission. The model is programmed in Pascal, and the source code
may be obtained from the first author or downloaded from the internet web site at
http://www.agrsci.dk/pvj/dyste/caulisim.
J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107 101
20. Appendix A
The variables used in the model are listed below
fraction of PAR intercepted by crop canopy (0±1)
radiation conversion efficiency (g MJÀ1
PAR)
ÁAx maximum daily increase in leaf area (m2
dÀ1
plantÀ1
)
ÁVc daily increase in curd volume (mm3
dÀ1
)
ÁxVc maximum daily increase in curd volume (mm3
dÀ1
)
ÈV vegetative supply demand ratio (0±1)
Ç crop developmental stage (0±3)
A green leaf area (m2
plantÀ1
)
d plant density (plants mÀ2
)
D overall demand rate for dry matter growth (g mÀ2
dÀ1
)
Dc demand rate for growth of curd dry matter (g mÀ2
dÀ1
]
Dl demand rate for growth of structural dry matter in leaves (g mÀ2
dÀ1
)
Dr demand rate for growth of root dry matter (g mÀ2
dÀ1
)
Ds demand rate for growth of structural dry matter in stems (g mÀ2
dÀ1
)
DE demand rate for growth of reserves (g mÀ2
dÀ1
)
Fc curd fresh weight (g plantÀ1
)
Fv fresh weight of leaves and stem (g plantÀ1
)
hc curd height (mm)
P assimilates available for partitioning (g mÀ2
dÀ1
)
Pa dry matter assimilation (g mÀ2
dÀ1
)
PE mobilisation of reserves (g mÀ2
dÀ1
)
Q photosynthetic active radiation (MJ mÀ2
d-1
)
R reserves in leaves and stem (g plantÀ1
)
Rc capacity for reserve storage in leaves and stem (g plantÀ1
)
rc curd radius (mm)
t time (d)
Th hourly air temperature (8C)
Td daily mean air temperature (8C)
Vc curd volume (mm3
)
Wc weight of structural dry matter in curds (g plantÀ1
)
Wl weight of structural dry matter in leaves (g plantÀ1
)
Wr weight of dry matter in roots (g plantÀ1
)
Ws weight of structural dry matter in stems (g plantÀ1
)
Appendix B
The constants used in the model for cv. Plana is listed below along with their
estimated values and the source of this information
102 J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107
21. Constants Value Source
Plant organs
af Eq. (4) 10.4 C
aE Eq. (1) 2.5 C
bf Eq. (4) 0.077 g cm À3
C
cf Eq. (5) 10.7 C
ch Eq. (3) 1.34 C
ef Eq. (5) 4.5 C
Kl 30 4
Kr 20 G
Sl 5958Cd C
Sr 3008Cd 5
Tbl 1.98C 8
Tbr 08C G
Development
Kd1 ˆ Kd2 26 C
Sd1 83.38C 6
Sd2 108.28C 7
Sd3 10508Cd 9
Tdb1 08C 6
Tdb2 5.18C 7
Tdb3 08C 9
Tdo2 15.58C 7
Leaf area expansion
al Eq. (7) 0.179 dÀ1
8
Lx Eq. (7) 6 m2
mÀ2
3
Curd volume growth
ac Eq. (8) 0.0123 (8C)À1
C
bc Eq. (9) 2.9 C
Demands for dry matter growth
aD Eq. (11) 0.04 dÀ1
G
bD Eqs. (12) and (13) 1 dÀ1
G
bE Eq. (15) 0.075 dÀ1
C
cc Eq. (14) 0.005 g cm À3
C
cD Eq. (12) .09 1
cE Eq. (15) 0.12 dÀ1
C
ec Eq. (14) 0.12 g cmÀ3
C
J.E. Olesen, K. Grevsen / Scientia Horticulturae 83 (2000) 83±107 103
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