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Brassica carinata (carinata), a non‐food oilseed feedstock mainly used for biofuel, is a relatively new alternative winter crop in the southeastern (SE) United States (US). However, there are limited N rate and N application timing data available at the regional scale. These data are needed to expand production in the SE US. An N rate study was conducted during the winter–spring growing seasons during 2017–2018 and 2018–2019 in Florida, US, and at three locations during 2018–2019 in Georgia, US, to quantify the effects of N rate (0, 45, 90, 134, and 179 kg N ha−1) on carinata nutrient uptake, biomass, seed yield, and seed chemical composition. Seed yield showed a linear response up to 134 kg N ha−1. Seed protein and glucosinolate concentrations decreased from 0 to 90 kg N ha−1, then increased from 90 to 179 kg N ha−1. Seed oil concentration was inversely related to seed protein concentration. A two‐factor N application timing study (4 N application timing: at‐plant, pre‐bolting, at‐plant + pre‐bolting, at‐plant + pre‐bolting + bolting × 4 N rates: 0, 45, 90, and 134 kg N ha−1) was conducted in Georgia, US, over three site‐years to quantify the effect of N application timing on yield and agronomic and economic optimum N rates (AONR and EONR, respectively). All split applications increased AONR by at least 10 kg N ha−1 compared to a single at‐plant application. A two‐split N application was more profitable than either a single N application or a three‐split N application based on marginal return. A two‐way split application (at‐plant + pre‐bolting) at 134 kg N ha−1 is recommended to optimize yield and economical production. Based on uncertainty analyses, the 50% credible interval of EONR occurred between 116 and 152 kg N ha−1, with a median estimate at 130 kg N ha−1.

Carinata (Brassica carinata) is an oilseed crop which, because of its non‐edible oil composition and favorable fatty acid profile, is proposed as a “green” sustainable aviation fuel. It can be grown as a winter crop in the southeastern USA or as a summer annual crop in northern latitudes. No crop models exist for carinata because it is a relatively new crop. The CROPGRO model is a mechanistic crop simulation of daily crop growth and development as a function of daily weather, soil properties, crop management, and species parameters. We adapted the CROPGRO model to simulate carinata based on growth analysis data collected over two seasons at three sites: Quincy, FL, Jay, FL, and Shorter, AL. The adaptation process required literature knowledge as well as optimization against field observations. The parameterization of model sensitivities to climatic factors is presented. The adapted model gave good simulations of carinata growth dynamics compared to observed growth during different seasons and locations and in response to N fertilization. While additional testing is appropriate, the model is sufficiently ready to be used for various applications. An example application is presented for the effect of sowing date on carinata yield and maturity over long‐term weather in the Southeastern USA.

The environmental consequences of using nonrenewable fossil fuels have motivated a global quest for sustainable alternatives from renewable sources. Carinata has been developed as a low carbon intensity, non‐food oilseed biomolecular platform to produce advanced drop‐in renewable fuels, meal, and co‐products. The crop is widely adaptable to grow in the humid subtropical and humid continental climatic regions of Asia, Africa, North America, South America, Europe, and Australia as a spring or winter crop. Carinata is heat tolerant, resistant to diseases and seed shattering with lower water‐use requirements than other oilseed brassicas. Adopting carinata in double‐cropping systems would require continuing research to integrate crop biology with agronomy, to understand growth and development and its interaction with agricultural inputs and management. Site‐specific best management agronomic practices and crop improvement research to develop frost‐tolerant, early‐maturing, nutrient use‐efficient, and high yielding varieties with desirable oil content and fatty acid profile will enhance the crop's adaptability and economic viability. The exploitation of intra‐ and interspecific and intra‐ and intergeneric diversity will further enhance carinata productivity and resistance to biotic and abiotic stresses. This review attempts to present a comprehensive description of carinata's biology, beginning with its origin and current state of distribution, availability of genetic and genomic resources, and a discussion of its morphology, phenology, and reproduction. A detailed analysis of the agronomy of the crop, including planting and germination and management practices, is presented in the context of crop growth and development. This will facilitate global adoption, sustainable production, and commercialization of carinata as a dedicated biofuel oilseed crop in diverse cropping systems and growing regions of the world, including the Southeast United States.

Peanut (Arachis hypogaea L.) yield and financial returns are often low for smallholder farmers in Ghana. Additionally, aflatoxin concentration in foods derived from peanut can be high enough to adversely affect human health. Eight experiments were conducted in 2016 and 2017 in northern Ghana to compare yield, financial returns, pest reaction, and aflatoxin contamination at harvest with traditional farmer versus improved practices. Relative to the farmer practice, the improved practice consisted of weeding one extra time, applying local potassium-based soaps to suppress arthropods and pathogens, and application of either homogenized oyster shells or a commercial blend of fertilizer containing calcium. Each of these field treatments were followed by either drying peanut on the soil surface and storing in traditional poly bags or drying peanut on tarps and storing in hermetically-sealed bags for 4 months. Peanut yield and financial returns were significantly greater when a commercial blend of fertilizer or oyster shells were applied compared to the farmer practice of not applying any fertilizer. Yield and financial returns were greater when a commercial fertilizer blend was applied compared with oyster shells. Severity of early leaf spot [caused by Passalora arachidicola (Hori) U. Braun] and late leaf spot [caused by Nothopassalora personata (Berk. & M.A. Curtis) U. Braun, C. Nakash., Videira & Crous], scarring and penetration of pods by arthropods, and the number of arthropods at harvest were higher for the farmer practice than for either fertility treatment; no difference was noted when comparing across fertility treatments. Less aflatoxin was observed for both improved practices in the field compared with the farmer practice. Drying peanut on tarps resulted in less aflatoxin compared to drying peanut on the ground regardless of treatments in the field. Aflatoxin concentration after storage was similar when comparing post-harvest treatments of drying on soil surface and storing in poly bags vs. drying on tarps and storing in hermetically-sealed bags. These results demonstrate that substantial financial gain can be realized when management in the field is increased compared with the traditional farmer practice. While aflatoxin concentrations differed between the farmer practice and the improved practices at harvest and after drying, these differences did not translate into differences after storage.

Aflatoxin in peanut (Arachis hypogaea L.) and other crops can negatively affect human health, especially in countries where regulatory agencies do not have limits on aflatoxin entering the food supply chain. While considerable research has been conducted addressing aflatoxin contamination in peanut at individual steps in the supply chain, studies that quantify aflatoxin contamination following combinations of interventions to crop management, drying, and storage are limited. Research was conducted during 2016 and 2017 in two villages in southern Ghana to follow aflatoxin contamination along the supply chain and to compare improved practices with traditional farmer practices used by smallholders. The farmer practice of only a single weeding was compared with improved practices during the growing season up to harvest that included applying local soaps to suppress aphids (Aphis gossypii Golver) that transmit peanut rosette virus disease (Umbravirus: Tombusviridaee), one additional weeding, and calcium applied at pegging. The improved practice for drying included placing pods removed from plants onto tarps compared with the traditional practice of drying on the ground. Storing peanut for four months in hermetically-sealed bags was the improved practice compared with storing in traditional poly bags. All improved practices individually resulted in lower aflatoxin contamination as compared to the farmer practices. While aflatoxin levels were very low (

In silico plant modelling is the use of dynamic crop simulation models to evaluate hypothetical plant traits (phenology, processes and plant architecture) that will enhance crop growth and yield for a defined target environment and crop management (weather, soils, limited resource). To be useful for genetic improvement, crop models must realistically simulate the principles of crop physiology responses to the environment and the principles by which genetic variation affects the dynamic crop carbon, water and nutrient processes. Ideally, crop models should have sufficient physiological detail of processes to incorporate the genetic effects on these processes to allow for robust simulations of response outcomes in different environments. Yield, biomass, harvest index, flowering date and maturity are emergent outcomes of many interacting genes and processes rather than being primary traits directly driven by singular genetics. Examples will be given for several grain legumes, using the CSM-CROPGRO model, to illustrate emergent outcomes simulated as a result of single and multiple combinations of genotype-specific parameters and to illustrate genotype by environment interactions that may occur in different target environments. Specific genetically influenced traits can result in G × E interactions on crop growth and yield outcomes as affected by available water, CO2 concentration, temperature, and other factors. An emergent outcome from a given genetic trait may increase yield in one environment but have little or negative effect in another environment. Much work is needed to link genetic effects to the physiological processes for in silico modelling applications, especially for plant breeding under future climate change.

Multi-genotype multi-environment trials, associated with characterization of the environment, marker information for the genotypes and measurements of the phenotypic traits of interest can potentially provide the basis for models to predict the behavior of untested genotypes in new environments. However, there is as yet no clear indication of the best form of such models, nor how to parameterize them. The purpose of this study was to propose and test an approach to crop-QTL modeling, applied to prediction of time to flowering in common bean (Phaseolus vulgaris), which avoids the pitfall of estimating separately the parameters for each genotype. The environmental model is a dynamic model with development rates that depend on daily temperature and day length. Three of the model parameters are expressed as linear functions of the QTLs for time to flowering, resulting in a model that combines environmental variables and QTLs. An innovative approach to parameter estimation is proposed, based on least squares, which makes it quite easy to estimate all the parameters of this model simultaneously, using all the data. The parameterized model explains most of the genotypic and environmental variability in the data, and 47% of the genotype by environment (GxE) interaction. Cross validation shows that the model extrapolates well to new genotypes in the same environments as those of the data, and also to new environments if they are similar in terms of temperature and photoperiod to those in the training data.

Crop models are increasingly being used as tools to simulate climate change effects or effects of virtual heat-tolerant cultivars; therefore it is important that upper temperature thresholds for seed-set, seed growth, phenology, and other processes affecting yield be developed and parameterized from elevated temperature experiments whether field or controlled-environment chambers. In this paper, we describe the status of crop models for dry bean (Phaseolus vulgaris L.), peanut (Arachis hypogaea L.), soybean (Glycine max L.), chickpea (Cicer arietinum L.), sorghum (Sorghum bicolor (L.) Moench), and millet (Pennisetum glaucum L. (R.) Br) in the Decision Support System for Agrotechnology Transfer (DSSAT) for response to elevated temperature by comparison to observed data, and we review where changes have been made or where needed changes remain. Temperature functions for phenology and photosynthesis of the CROPGRO-Dry Bean model were modified in 2006 for DSSAT V4.5, based on observed growth and yield of Montcalm cultivar grown in sunlit, controlled-environment chambers. Temperature functions for soybean and peanut models were evaluated against growth and yield data in the same chambers and found to adequately predict growth and yield, thus have not been modified since 1998 release of V3.5. The temperature functions for the chickpea model were substantially modified for many processes, and are updated for V4.6. The millet model was re-coded and modified for its temperature sensitivities, with a new function to allow the 8–10 day period prior to anthesis to affect grain set, as parameterized from field observations. For the sorghum model, the temperature effect on grain growth rate was modified to improve yield and grain size response to elevated temperature by comparison to data in controlled-environment chambers. For reliable assessments of climate change impact, it is critically important to gather additional temperature response data and to update parameterization and code of all crop models including DSSAT.

A study was conducted in four compartments of a polycarbonate greenhouse at Gainesville, FL, USA to investigate how a soybean (Glycine max L. Merr.) cultivar, Maverick (maturity group III, indeterminate), responded to three elevated temperatures, ELT, (day/night of 34/26 °C, 38/30 °C, and 42/34 °C) in comparison to a control growth temperature (30/22 °C). Carbon dioxide (CO2) concentration was maintained at 700 μmol mol−1 in each compartment by a processor controlled air-sampling and CO2-injection system. Three sequential experiments were conducted at different times of year (summer, autumn, and early spring) to investigate the effect of intensity, timing, and duration of ELT on soybean node number, internode elongation, mainstem length, and number of pods set per plant. At the control temperature, the soybean plants grown in the polycarbonate greenhouse were taller than field-grown plants. When plants were grown under continuous ELT applied soon after sowing or at initial flowering, the number of nodes increased with increasing ELT intensity, whereas the length of individual internodes decreased. When ELT treatment was applied during the beginning of flowering stage (R1–R2) or earlier, more nodes were produced and the length of affected internodes was decreased. When the ELT was imposed later at reproductive stage R5+ just before the beginning of seed filling, effects on node numbers and internode lengths were negligible. Short-term (10-day) duration of ELT applied at four stages from V3 to R5+ did not significantly affect final mean numbers of nodes or mean mainstem lengths. Possible mechanisms of elevated temperature effects on soybean internode elongation and node number (internode number) are discussed. Total pod numbers per plant increased linearly with mainstem node numbers and mainstem length. Furthermore, total pod numbers per plant were greatest at 34/26 °C rather than at the control temperature of 30/22 °C (and remained high at 38/30 °C). Mild increases in temperature might not threaten, but actually increase, yields of soybean in northerly zones where this crop is currently grown at slightly suboptimal temperatures. However, a sustained increase in ambient temperature would likely threaten soybean yields.

The common bean is a tropical facultative short-day legume that is now grown in tropical and temperate zones. This observation underscores how domestication and modern breeding can change the adaptive phenology of a species. A key adaptive trait is the optimal timing of the transition from the vegetative to the reproductive stage. This trait is responsive to genetically controlled signal transduction pathways and local climatic cues. A comprehensive characterization of this trait can be started by assessing the quantitative contribution of the genetic and environmental factors, and their interactions. This study aimed to locate significant QTL (G) and environmental (E) factors controlling time-to-flower in the common bean, and to identify and measure G × E interactions. Phenotypic data were collected from a biparental [Andean × Mesoamerican] recombinant inbred population (F11:14, 188 genotypes) grown at five environmentally distinct sites. QTL analysis using a dense linkage map revealed 12 QTL, five of which showed significant interactions with the environment. Dissection of G × E interactions using a linear mixed-effect model revealed that temperature, solar radiation, and photoperiod play major roles in controlling common bean flowering time directly, and indirectly by modifying the effect of certain QTL. The model predicts flowering time across five sites with an adjusted r-square of 0.89 and root-mean square error of 2.52 d. The model provides the means to disentangle the environmental dependencies of complex traits, and presents an opportunity to identify in silico QTL allele combinations that could yield desired phenotypes under different climatic conditions.

Crop production is greatly impacted by growing season duration, which is driven by prevailing environmental conditions (mainly temperature) and agronomic management practices (particularly changes in cultivars and shifts in sowing dates). It is imperative to evaluate the impact of climate change and crop husbandry practices on phenology to devise future management strategies to prepare for climate change. Historical changes in spring and autumn maize phenology were observed in Punjab, Pakistan during 1980–2014. Sowing (S) of spring maize was earlier by an average of 4.6 days decade−1, while autumn maize ‘S’ and emergence (E) were delayed on average 3.0and 1.9 days decade−1. Observed anthesis (A) plus maturity (M) dates were earlier by 7.1 and 9.2 days decade−1 and 2.8 and 4.4 days decade−1for spring and autumn maize, respectively. Similarly, S-A, S-M and A-Mphases were shortened on average by 2.4, 4.6 and 1.9 days decade−1 and 5.5, 7.8 and 2.2 days decade−1 for spring and autumn maize, respectively. The variability in phenological phases of spring and autumn maize had significant correlation,with the increase in temperature during 1980–2014. Employing the CSM-CERES-Maize model using standard hybrid for all locations and years illustrated that model-predicted phenology has accelerated with climate change more than infield-observed phenology. These findings suggest that earlier late sowing and shifts of cultivars requiring high total growing degree day during 1980–2014, have partially mitigated the negative impact of climate change on phenology of both spring and autumn grown maize.

Brachiaria and Cynodon are two of the most important pasture grasses worldwide. Computer model simulations can be used to study pasture species growth and physiological aspects to identify gaps of knowledge for genetic improvement and management strategies. The objective of this research was to compare the performance relative to calibrated parameters of the CROPGRO‐Perennial Forage Model (CROPGRO‐PFM) for simulating three different species (“Marandu” palisadegrass, “Convert HD 364®” brachiariagrass and “Tifton 85” bermudagrass) grown under similar management. The field experiment consisted of two harvest frequencies, 28 and 42 days, under irrigated and rainfed conditions. Data used to calibrate the model included regular forage harvests, plant‐part composition, leaf photosynthesis, leaf area index, light interception and plant nitrogen concentration. The simulation of biomass production of the three grasses presented d‐statistic values higher than 0.80, RMSE ranging from 313 to 619 kg/ha and ratio observed/simulated ranging 0.968 to 1.027. Harvest frequency treatments of 28 and 42 days were well simulated by the model. A sensitivity analysis was conducted to evaluate the most influential parameters needed for model calibration and to contrast the grasses, showing that the differences among the three grasses are mostly driven by plant‐part composition and assimilate partitioning among plant organs.

Weeds and diseases can reduce peanut (Arachis hypogaea L.) yield or increase cost of production to maintain acceptable yield. While herbicides and fungicides have limited availability in many areas...

To reduce the risks of climate change, governments agreed in the Paris Agreement to limit global temperature rise to less than 2.0 °C above pre-industrial levels, with the ambition to keep warming to 1.5 °C. Charting appropriate mitigation responses requires information on the costs of mitigating versus associated damages for the two levels of warming. In this assessment, a critical consideration is the impact on crop yields and yield variability in regions currently challenged by food insecurity. The current study assessed impacts of 1.5 °C versus 2.0 °C on yields of maize, pearl millet and sorghum in the West African Sudan Savanna using two crop models that were calibrated with common varieties from experiments in the region with management reflecting a range of typical sowing windows. As sustainable intensification is promoted in the region for improving food security, simulations were conducted for both current fertilizer use and for an intensification case (fertility not limiting). With current fertilizer use, results indicated 2% units higher losses for maize and sorghum with 2.0 °C compared to 1.5 °C warming, with no change in millet yields for either scenario. In the intensification case, yield losses due to climate change were larger than with current fertilizer levels. However, despite the larger losses, yields were always two to three times higher with intensification, irrespective of the warming scenario. Though yield variability increased with intensification, there was no interaction with warming scenario. Risk and market analysis are needed to extend these results to understand implications for food security.

Development of management tools is essential to explore the potential of grassland systems and such tools include simulation models used for management, planning and research purposes. The simulation models account for temperature effects on forage growth in various ways, and most of them use degree-day-based sub-models to simulate plant growth. Little or no growth is expected for tropical grasses when temperatures are between 10 and 15 °C; thus, the assumption of 15 °C as the base temperature for growth of these plants is not uncommon. The objective of this paper is to test an approach, commonly used for row crops, for determination of pasture grasses base temperature using a Panicum spp. dataset, and to compare different methods of calculation. Data was collected from well-established plots (4 m × 10 m) of five Panicum spp. cultivars (Atlas, Massai, Mombaca, Tanzânia and Tobiata), arranged in four randomized complete blocks, sampled from December 2002 to April 2004 in Piracicaba, SP, Brazil. Light interception measurements from three summer and one winter growth cycles were used to determine thermal time to reach 95% canopy light interception. Base-temperature was calculated using iteration method, the b-coefficient method, minimum coefficient of variation of accumulated degree-days, and minimum standard deviation in degree-days and in days. The order of best methods was iteration, coefficient of variation of accumulated degree-days and b-coefficient method, respectively. The standard deviation method in degree-days and in days resulted in high base temperatures and was not able to detect differences among cultivars. Overall base temperatures were different among cultivars: Massai: 16 °C, Atlas: 15 °C, Mombaca: 11 °C, Tobiata: 10 °C and Tanzânia: 7 °C.

Maintaining high levels of productivity under climate change will require developing cultivars that are able to perform under varying drought and heat stresses and with maturities that match water availability. The CSM-CERES-Sorghum model was used to quantify the potential benefits of altering crop life cycle, enhancing yield potential traits, and incorporating drought and heat tolerance in the commonly grown cultivar types at two sites each in India (cv. CSV 15 at both Akola and Indore) and Mali (cv. CSM 335 at Samanko and cv. CSM 63E at Cinzana), West Africa. Under current climate CSV 15 on average matured in 108 days and produced 3790 kg ha−1 grain yield at Akola; whereas at Indore it matured in 115 days and produced 3540 kg ha−1 grain yield. Similarly under current climate, CSM 335 matured in 120 days and produced 2700 kg ha−1 grain yield at Samanko; whereas CSM 63E matured in 85 days at Cinzana and produced 2210 kg ha−1 grain yield. Decreasing crop life cycle duration of cultivars by 10% decreased yields at all the sites under both current and future climates. In contrast, increasing crop life cycle by 10% increased yields up to 12% at Akola, 9% at Indore, 8% at Samanko and 33% at Cinzana. Enhancing yield potential traits (radiation use efficiency, relative leaf size and partitioning of assimilates to the panicle each increased by 10%) in the longer cycle cultivars increased the yields by 11–18% at Akola, 17–19% at Indore, 10–12% at Samanko and 14–25% at Cinzana under current and future climates of the sites. Except for the Samanko site, yield gains were larger by incorporating drought tolerance than heat tolerance under the current climate. However, under future climates yield gains were higher by incorporating heat tolerance at Akola, Samanko and Cinzana, but not at Indore. Net benefits of incorporating both drought and heat tolerance increased yield up to 17% at Akola, 9% at Indore, 7% at Samanko and 16% at Cinzana under climate change. It is concluded that different combinations of traits will be needed to increase and sustain productivity of sorghum in current and future climates at these target sites and that the CSM-CERES-Sorghum model can be used to quantify benefits of incorporating certain traits.

Common bean production in Goias, Brazil is concentrated in the same geographic area, but spread across three distinct growing seasons, namely, wet, dry and winter. In the wet and dry seasons, common beans are grown under rainfed conditions, whereas the winter sowing is fully irrigated. The conventional breeding program performs all varietal selection stages solely in the winter season, with rainfed environments being incorporated in the breeding scheme only through the multi environment trials (METs) where basically only yield is recorded. As yield is the result of many interacting processes, it is challenging to determine the events (abiotic or biotic) associated with yield reduction in the rainfed environments (wet and dry seasons). To improve our understanding of rainfed dry bean production so as to produce information that can assist breeders in their efforts to develop stress-tolerant, high-yielding germplasm, we characterized environments by integrating weather, soil, crop and management factors using crop simulation models. Crop simulations based on two commonly grown cultivars (Perola and BRS Radiante) and statistical analyses of simulated yield suggest that both rainfed seasons, wet and dry, can be divided in two groups of environments: highly favorable environment and favorable environment. For the wet and dry seasons, the highly favorable environment represents 44% and 58% of production area, respectively. Across all rainfed environment groups, terminal and/or reproductive drought stress occurs in roughly one fourth of the seasons (23.9% for Perola and 24.7% for Radiante), with drought being most limiting in the favorable environment group in the dry TPE. Based on our results, we argue that even though drought-tailoring might not be warranted, the common bean breeding program should adapt their selection practices to the range of stresses occurring in the rainfed TPEs to select genotypes more suitable for these environments.

Using CROPGRO-Chickpea model (revised version), we investigated the impacts of climate change on the productivity of chickpea (Cicer arietinum L.) at selected sites in South Asia (Hisar, Indore and Nandhyal in India and Zaloke in Myanmar) and East Africa (Debre Zeit in Ethiopia, Kabete in Kenya and Ukiriguru in Tanzania). We also investigated the potential benefits of incorporating drought and heat tolerance traits in chickpea using the chickpea model and the virtual cultivars approach. As compared to the baseline climate, the climate change by 2050 (including CO2) increased the yield of chickpea by 17% both at Hisar and Indore, 18% at Zaloke, 25% at Debre Zeit and 18% at Kabete; whereas the yields decreased by 16% at Nandhyal and 7% at Ukiriguru. The yield benefit due to increased CO2 by 2050 ranged from 7 to 20% across sites as compared to the yields under current atmospheric CO2 concentration; while the changes in temperature and rainfall had either positive or negative impact on yield at the sites. Yield potential traits (maximum leaf photosynthesis rate, partitioning of daily growth to pods and seed-filling duration each increased by 10%) increased the yield of virtual cultivars up to 12%. Yield benefit due to drought tolerance across sites was up to 22% under both baseline and climate change scenarios. Heat tolerance increased the yield of chickpea up to 9% at Hisar and Indore under baseline climate, and up to 13% at Hisar, Indore, Nandhyal and Ukiriguru under climate change. At other sites (Zaloke, Debre Zeit and Kabete) the incorporation of heat tolerance under climate change had no beneficial effect on yield. Considering varied crop responses to each plant trait across sites, this study was useful in prioritizing the plant traits for location-specific breeding of chickpea cultivars for higher yields under climate change at the selected sites in South Asia and East Africa.

Late leaf spot (LLS) caused by Cercosporidium personatum (Berk. and Curt.) Deighton leads to significant reductions in peanut (Arachis hypogaea L.) yield worldwide. This study was conducted to improve the mechanisms and methods by which LLS effects on defoliation and photosynthesis are linked to the CSM-CROPGRO-Peanut model for simulating growth and yield reductions in peanut cultivars. Field experiments were conducted in 2008 and 2009 to collect data on the effects of LLS on biomass accumulation and partitioning, leaf necrosis and defoliation, and total canopy photosynthesis (TCP) in peanut cultivars with more (York) and less (Carver) quantitative resistance to LLS. After incorporating LLS damage as defoliation percentage and necrotic area, the model accurately simulated crop growth and development for both cultivars despite different disease dynamics. Simulated TCP and leaf, total crop, and pod yield values were in good agreement with measured data. A modification in the model code to directly reduce leaf photosynthesis and quantum efficiency according to empirical observations resulted in improved simulations of LLS effects on growth and yield. Correlations among measured defoliation and necrotic area with disease ratings indicated that visual disease ratings could be successfully used to estimate necrosis and defoliation for model inputs. Results indicated that the CSM-CROPGRO-Peanut model has adequate capability to simulate LLS effects on growth and yield in peanut cultivars with differing levels of resistance to LLS when inputs on canopy necrotic area and defoliation are provided.

A better understanding of the mechanisms of peanut adaptation to pre-flowering drought is important for improving pod yield productivity. Nevertheless, the mechanisms of drought tolerance are under different genetic controls, and pod yield is a complex trait. Therefore, the aim of this study was to investigate the mechanism for drought tolerance of peanut genotypes with different pod yield responses under pre-flowering drought conditions. Field experiments were conducted during February to July, 2007 and during February to July, 2009. A split-plot experiment in a randomized complete block design was used. Two water management treatments were assigned as the main plots, i.e. field capacity (F.C.) and pre-flowering stress (PFD), and six peanut genotypes as the sub-plots. Relative water content (RWC) and stomatal conductance were recorded at 5, 10, 15, 20, 25, 30, 35 and 40 days after emergence (DAE). Leaf area index was measured at 25 DAE, R5 and R7. Total dry matter samples, including shoots, roots and pods, were obtained at 25 DAE, R5, R7 and harvest. Shoot growth rate, root growth rate and pod growth rate were then calculated. Major finding, the first mechanism is explained by high water uptake of the root systems that provide sufficient water for normal transpiration, as the response of ICGV 98305 to PFD. It may induce the improvement of peanut pod growth rate in pod filling stage due to the change of assimilate proportion, resulting in increasing pod yield to PDF comparing with adequate water conditions. In contrast, such as the response of ICGV 98330, pre-flowering drought can increase the ability of peanut to save more water by reduction of transpiration, but rooting traits are not changed. This could conserve more water by reducing transpiration to maintain high RWC. Nevertheless, the ability to reduce transpiration did not support the improvement of peanut pod yield under these conditions. The increasing peanut productivity to pre-flowering drought was contributed by the improvement of assimilate proportion to economic part in reproductive phase. This knowledge will be useful for breeding of peanut for pre-flowering drought environment.

Water deficit is a major factor responsible for soybean yield gap in Southern Brazil and tends to increase under climate change. An alternative to reduce such gap is to identify soybean cultivars with traits associated to drought tolerance. Thus, the aim of this study was to assess soybean adaptive traits to water deficit that can improve yield under current and future climates, providing guidelines for soybean cultivar breeding in Southern Brazil. The following soybean traits were manipulated in the CSM-CROPGRO-Soybean crop model: deeper root depth in the soil profile; maximum fraction of shoot dry matter diverted to root growth under water stress; early reduction of transpiration under mild stress; transpiration limited as a function of vapor pressure deficit; N2 fixation drought tolerance; and sensitivity of grain filling period to water deficit. The yields were predicted for standard and altered traits using climate data for the current (1961–2014) and future (middle-century) scenarios. The traits with greater improvement in soybean yield were deeper rooting profile, with yield gains of ≈300 kg ha−1, followed by transpiration limited as a function of vapor pressure deficit and less drought-induced shortening of the grain filling period. The maximum fraction of shoot dry matter diverted to root and N2 fixation drought tolerance increased yield by less than 75 kg ha−1, while early reduction of transpiration resulted in a small area of country showing gains. When these traits were combined, the simulations resulted in higher yield gains than using any single trait. These results show that traits associated with deeper and greater root profile in the soil, reducing transpiration under water deficit more than photosynthesis, creating tolerance of nitrogen fixation to drought, and reducing sensitivity of grain filling period to water deficit should be included in new soybean cultivars to improve soybean drought tolerance in Southern Brazil.

Climate change is projected to intensify drought and heat stress in groundnut (Arachis hypogaea L.) crop in rainfed regions. This will require developing high yielding groundnut cultivars that are both drought and heat tolerant. The crop growth simulation model for groundnut (CROPGRO-Groundnut model) was used to quantify the potential benefits of incorporating drought and heat tolerance and yield-enhancing traits into the commonly grown cultivar types at two sites each in India (Anantapur and Junagadh) and West Africa (Samanko, Mali and Sadore, Niger). Increasing crop maturity by 10 % increased yields up to 14 % at Anantapur, 19 % at Samanko and sustained the yields at Sadore. However at Junagadh, the current maturity of the cultivar holds well under future climate. Increasing yield potential of the crop by increasing leaf photosynthesis rate, partitioning to pods and seed-filling duration each by 10 % increased pod yield by 9 to 14 % over the baseline yields across the four sites. Under current climates of Anantapur, Junagadh and Sadore, the yield gains were larger by incorporating drought tolerance than heat tolerance. Under climate change the yield gains from incorporating both drought and heat tolerance increased to 13 % at Anantapur, 12 % at Junagadh and 31 % at Sadore. At the Samanko site, the yield gains from drought or heat tolerance were negligible. It is concluded that different combination of traits will be needed to increase and sustain the productivity of groundnut under climate change at the target sites and the CROPGRO-Groundnut model can be used for evaluating such traits.

Anticipated climate change will alter the temperature and rainfall characteristics of crop growing seasons. This will require genetic improvement of crops for adapting to future climates for higher yields. The CROPGRO model for groundnut was used to evaluate genetic traits of Virginia and Spanish types of groundnut for various climate scenarios of India. The analysis revealed that productivity of groundnut can be increased in current and future climates by adjusting the duration of various life-cycle phases, especially the seed-filling to physiological maturity (SD-PM). Increased maximum leaf photosynthesis rate (AMAX), increased partitioning to reproductive organs (XFRT) and increased individual seed-fill duration (SFDUR) all contributed to the increase in pod yield in all climates. More determinate pod set (shorter PODUR) was beneficial only in the water deficit environments. The positive effect of increasing specific leaf area (SLA) and leaf size (SIZLF) on pod yield was greater in environments more favourable for plant growth. Increasing reproductive tolerance to high temperature by 2 °C increased pod yield of groundnut in warmer environments, especially where the crop often suffers from drought. Increased adaptive partitioning to roots (ATOP) increased drought resistance of groundnut on high water-holding capacity soils. Combination of traits had additive effects and pod yield increased substantially. These results indicate that the CROPGRO model can be used to assess the potential of individual or combination of plant traits for guiding breeding of improved groundnut varieties for current and future climates.

Eleven species of picture-winged flies (Diptera: Ulidiidae: Lipsanini) have been reported attacking maize [Zea mays L. (Poaceae)] ears in the Americas. Four of these species are sweet corn pests in America north of Mexico: Chaetopsis massyla (Walker), Euxesta annonae (Fabricius), E. eluta Loew, and E. stigmatias Loew. Adults of these four species appear at the beginning of each season following maize-free periods, suggesting other plants act as food sources for maintenance and development of these flies. Studies were conducted in Florida, USA, to evaluate the suitability of several crop and non-crop plants commonly occurring near maize plantings as developmental hosts for these flies. Laboratory trials were conducted using laboratory colonies of C. massyla, E. eluta ,a ndE. stigmatias to determine their developmental rates and pupal survivorship on roots, stems, leaves, or fruits of 14 cropandweedspecies.Allthreeflyspeciescompleteddevelopment onalltestedcrops(Brassicaoleracea L., Capsicum chinense Jacquin, Capsicum annum L., Carica papaya L., Persea americana Mill., RaphanussativusL.,SaccharumofficinarumL., andSolanumlycopersicumL.)andweedspecies [Amaranthus spinosus L., Portulaca oleracea L., Sorghum halepense (L.), and Typha spp.], except for Daucus carota L. roots and Solanum tuberosum L. tubers. Findings of the current study suggest that the presence of multiple host crops in areas surrounding maize fields may help explain the occurrence of thesemaize-infestingulidiidsimmediatelyafterprolongedabsencesofmaize.

Peanut root distribution patterns are not well understood and have not been studied extensively. There is a lack of information on the classification of root distribution patterns for many peanut genotypes and the relationship between rooting traits and yield under mid-season drought, which could be useful for breeding for drought tolerance. In this study the root distribution of 40 peanut genotypes with different drought tolerance levels and different sources of origin was evaluated during the dry seasons of 2007 and 2008 at Khon Kaen University, Thailand. A randomized complete block design with four replications was used in both years. All plots were well-irrigated except when water was withheld from 50 to 83 days after planting (DAP) during the first season and from 50 to 87 DAP during the second season to emulate a mid-season drought. Top dry weight was observed at the most water-stressed date and at harvest, while root data were measured at the most water-stressed date using the auger method. The soil was sampled to a depth of 90 cm and was separated into the upper (0–30 cm), middle (30–60 cm) and deeper (60–90 cm) soil layers. For each peanut genotype, the relative contribution to each layer was calculated and defined as root length density percentage (%RLD). Pod yield was observed at final harvest date and pod harvest index (PHI) was calculated as pod dry weight per unit of total biomass. The forty peanut genotypes were categorized as either high or low %RLD depending on the mean of %RLD in each layer for the three soil layers. These peanut genotypes were then categorized into six combinative groups, based on the high vs. low %RLD for each of the three layers. The relationship between %RLD in the lower soil layer and yield was significant and positive for both seasons, indicating that %RLD in the lower layer is an important trait that affects pod yield under mid-season drought conditions. There was a negative relationship to %RLD in the upper layer in one season and no relationship to %RLD in the middle soil layer for both seasons. The results from this study also indicated that PHI was an important trait that is associated with maintaining pod yield under mid-season drought.

Late leaf spot (LLS) caused by Cercosporidium personatum (Berk. & Curt.) Deighton reduces leaf CO 2 assimilation rate (A sat ) and accelerates leaf defoliation, which together lead to major reduc- tions in peanut (Arachis hypogaea L.) yield world- wide. This study was conducted to determine whether differences in photosynthetic response to LLS severity exist among peanut cultivars of differing resistance. Field experiments were con- ducted in 2008 and 2009 to study the effects of LLS on A sat of tagged leaf cohorts, and photo- synthetic response of similar age leaves to LLS in peanut cultivars with more (York) and less (Carver) quantitative resistance. A nonlinear model, y = (1 − x) β was used to analyze A sat data, where y is relative A sat , x is measured visual lesion area, and β represents the relationship between virtual and visual lesion area. Progression of LLS severity on leaf cohorts was slower in York than in Carver. However, the reduction in A sat with leaf cohort age was similar across the cultivars. This paradox could be explained by a higher β value in York (4.6) than in Carver (3.6), indicating a greater relative reduction in A sat beyond the necrotic lesion area in York. This greater reduction in A sat in York compared to Carver was most closely related to a reduction in maximum carboxylation velocity. Results indicated that future efforts to improve LLS resistance should include sustain- ing A sat in response to LLS infection along with slower disease progress.

Maize and grain sorghum seeds were sown in pots and grown for 39 days in sunlit controlled-environment chambers at 360 (ambient) and 720 (double-ambient, elevated)μmol mol(-1) carbon dioxide concentrations [CO(2)]. Canopy net photosynthesis (PS) and evapotranspiration (TR) was measured throughout and summarized daily from 08:00 to 17:00h Eastern Standard Time. Irrigation was withheld from matched pairs of treatments starting on 26 days after sowing (DAS). By 35 DAS, cumulative PS of drought-stress maize, compared to well-watered plants, was 41% lower under ambient [CO(2)] but only 13% lower under elevated [CO(2)]. In contrast, by 35 DAS, cumulative PS of drought-stress grain sorghum, compared to well-watered plants, was only 9% lower under ambient [CO(2)] and 7% lower under elevated [CO(2)]. During the 27-35 DAS drought period, water use efficiency (WUE, mol CO(2)Kmol(-1)H(2)O), was 3.99, 3.88, 5.50, and 8.65 for maize and 3.75, 4.43, 5.26, and 9.94 for grain sorghum, for ambient-[CO(2)] well-watered, ambient-[CO(2)] stressed, elevated-[CO(2)] well-watered and elevated-[CO(2)] stressed plants, respectively. Young plants of maize and sorghum used water more efficiently at elevated [CO(2)] than at ambient [CO(2)], especially under drought. Reductions in biomass by drought for young maize and grain sorghum plants were 42 and 36% at ambient [CO(2)], compared to 18 and 14% at elevated [CO(2)], respectively. Results of our water stress experiment demonstrated that maintenance of relatively high canopy photosynthetic rates in the face of decreased transpiration rates enhanced WUE in plants grown at elevated [CO(2)]. This confirms experimental evidence and conceptual models that suggest that an increase of intercellular [CO(2)] (or a sustained intercellular [CO(2)]) in the face of decreased stomatal conductance results in relative increases of growth of C(4) plants. In short, drought stress in C(4) crop plants can be ameliorated at elevated [CO(2)] as a result of lower stomatal conductance and sustaining intercellular [CO(2)]. Furthermore, less water might be required for C(4) crops in future higher CO(2) atmospheres, assuming weather and climate similar to present conditions.

Carbohydrate and N reserves are important for perennial grass regrowth after defoliation. The objective of this study was to quantify the effects of N fertilization on dynamics of reserve accumulation and utilization for regrowth of a C 4 perennial grass. A field study was conducted at Gainesville, FL, on established 'Tifton 85' bermudagrass (Cynodon spp.) in 2006 and 2007. Treatments were N rates of 0, 45, 90, and 135 kg N ha ―1 regrowth period ―1 . Total nonstructural carbohydrate (TNC) and N concentrations, leaf area index (LAI), and canopy carbon exchange rate (CER) were measured weekly during 28-d regrowth periods. Stem and rhizome TNC concentrations decreased with increasing N rate, ranging from 20 to 80 mg g ―1 for stem and 45 to 145 mg g ―1 for rhizome, and followed quadratic time trends, with minima between 7 and 14 d of regrowth, suggesting reserve utilization up to 2 wk after defoliation. Leaf, stem, rhizome, and root N concentrations increased with N rate. Leaf and stem N concentrations followed quadratic time trends, with maxima between 7 and 14 d of regrowth, and ranged from 15 to 50 mg g ―1 for leaf and 10 to 40 mg g ―1 for stem. Rhizome N concentrations were constant throughout regrowth. Canopy CER and LAI followed logistic time trends within each 28-d regrowth period, with upper asymptotes raised by increased N rate. Nitrogen fertilization increased TNC reserve utilization, LAI, and canopy CER, thereby increasing shoot regrowth at rates up to 90 kg N ha ―1 period ―1 .

'Tifton 85' bermudagrass (Cynodon spp.) has been widely adopted as a forage and hay crop and is being considered as a cellulosic ethanol feedstock. The objective of this study was to evaluate the effects of N fertilization rate on Tifton 85 regrowth dynamics. A field study was conducted near Gainesville, FL, on established Tifton 85 in 2006 and 2007. The treatments were N rates of 0, 45, 90, and 135 kg N ha ―1 regrowth period ―1 . Tissue mass, leaf:stem ratio, and tiller number and mass were measured weekly during 28-d regrowth periods. Leaf mass followed logistic time trends with the upper asymptote varying between 50 and 225 g m ―2 depending on N rate and season (summer and autumn). Stem mass lagged behind leaf mass for 7 to 14 d, subsequently following linear or quadratic time trends to reach between 75 and 300 g m- 2 by 28 d. Increasing N rate from 0 to 135 kg ha ―1 period ―1 increased tiller mass at 28 d from 1.5 to 3 g tiller ―1 in summer and 1 to 1.5 g tiller ―1 in autumn. Leaf:stem ratio increased to 1.0 within 14 to 21 d, followed by a subsequent decrease. Rhizome and root mass were not affected by N fertilization. Increasing N rate primarily affected mass and proportion of above-ground plant parts, with little effect on mass of below-ground parts. Nitrogen nutrition index values were similar whether calculated from samples taken to a 10-cm stubble height or from samples taken to the soil surface. Regrowth was not enhanced by N rate beyond 90 kg N ha ―1 regrowth period ―1 .

The picture-winged fly Euxesta stigmatias Loew (Diptera: Ulidiidae) has been a serious pest of sweet corn (Zea mays L.) in Florida since 1930. Several other species in the family are known to infest corn grown in the Caribbean, Central America, and South America. Surveys were conducted throughout Florida to evaluate species richness and distribution of corn-infesting Ulidiidae. Adults were sampled with sweep nets and reared from fly larvae-infested corn ears collected from representative corn fields in 16 and 27 counties in 2007 and 2008, respectively. Four Ulidiidae species were found in corn fields using both sampling techniques. Euxesta eluta Loew and Chaetopsis massyla (Walker) were found throughout the state on field and sweet corn. Euxesta stigmatias was only found in Martin, Miami-Dade, Okeechobee, Palm Beach, and St. Lucie Counties on field and sweet corn. Euxesta annonae (F.) was found in sweet corn in Miami-Dade, Okeechobee, and Palm Beach Counties, but field corn was not sampled in the...

Warm-season grasses are economically important for cattle production in tropical regions, and tools to aid in management and research of these forages would be highly beneficial. Crop simulation models synthesize numerous physiological processes and are important research tools for evaluating production of warm-season grasses. This research was conducted to adapt the perennial CROPGRO Forage model to simulate growth of the tropical species palisadegrass [ Brachiaria brizantha (A. Rich.) Stapf. cv. Xaraes] and to describe model adaptation for this species. In order to develop the CROPGRO parameters for this species, we began with values and relationships reported in the literature. Some parameters and relationships were calibrated by comparison with observed growth, development, dry matter accumulation and partitioning during a 2-year experiment with Xaraes palisadegrass in Piracicaba, SP, Brazil. Starting with parameters for the bahiagrass ( Paspalum notatum Flugge) perennial forage model, dormancy effects had to be minimized, and partitioning to storage tissue/root decreased, and partitioning to leaf and stem increased to provide for more leaf and stem growth and less root. Parameters affecting specific leaf area (SLA) and senescence of plant tissues were improved. After these changes were made to the model, biomass accumulation was better simulated, mean predicted herbage yield per cycle was 3573 kg ha −1 , with a RMSE of 538 kg DM ha −1 ( D -Stat = 0.838, simulated/observed ratio = 1.028). The results of the adaptation suggest that the CROPGRO model is an efficient tool to integrate physiological aspects of palisadegrass and can be used to simulate growth.

Made available in DSpace on 2019-10-04T12:35:43Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-01 Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) Crop models are important tools for assisting farmers and crop consultants to make decisions about fertilisation, irrigation and harvest management, because they allow users to understand productivity from the view of integrated sensitivities of basic plant physiological processes. The first objective of this study was to evaluate the performance of the CSM-CROPGRO-Perennial Forage model (PFM) to simulate regrowth of Urochloa brizantha (Hochst. ex A. Rich.) R.D. Webster cv. Marandu under varying irrigation and nitrogen levels. The second objective was to evaluate the water-balance module of the model under soil and climatic conditions in the Cerrado biome of central-eastern Brazil. The experimental data for model evaluation were obtained from a field experiment conducted during 2015, 2016 and 2017, and included herbage production, plant-part composition and plant nitrogen (N) concentration. The results suggest that the model can be used to simulate growth of Marandu palisade grass adequately under different managements of irrigation and N fertilisation. The findings indicate also that the agreement between simulations and field-observed soil moisture shows good performance of the water-balance module of CSM-CROPGRO-PFM. The most important parameterisation required by the model was the determination and calibration of inputs such as the stable soil carbon pool(SOM3) for N mineralisation, which affected the N response, and the soil water-holding characteristics, which affected the irrigation response. The default parameterisation ( species, ecotype, cultivar) of cv. Marandu inCSM-CROPGRO-PFM was sufficient for adequate performance of the model for this new environment and new crop management. However, minor modifications of species parameters were helpful to account for winter-kill of foliage. Sao Paulo State Univ, Coll Agr & Veterinarian Sci, Dept Rural Engn, BR-14884900 Jaboticabal, SP, Brazil Univ Florida, Agron Dept, Gainesville, FL 32611 USA Univ Florida, Inst Sustainable Food Syst & Agr, Gainesville, FL 32611 USA Univ Florida, Biol Engn Dept, Gainesville, FL 32611 USA Sao Paulo State Univ, Coll Agr & Veterinarian Sci, Dept Rural Engn, BR-14884900 Jaboticabal, SP, Brazil

Cercosporidium personatum (Berk. & Curt.) Deighton causes late leaf spot (LLS) in peanut (Arachis hypogaea L.), which leads to necrotic lesions, early leaf senescence and yield losses. Detailed physiological analyses can contribute to an improved understanding of peanut-disease interactions and cultivar improvement. A study was conducted evaluating two peanut cultivars with more (York) and less (Carver) quantitative resistance to C. personatum grown under fungicide-sprayed and nonsprayed conditions in the field at Citra, FL over 2 yr. Data were collected on disease severity using the Florida 1 to 10 visual rating scale and by direct measurement of percent canopy lesion area. Leaflifespan, total canopy photosynthesis (TCP), plant growth, and pod yield were also measured. Disease severity based on canopy lesion area was reduced by 30% in York compared to Carver. No additive effects of combining the resistant cultivar with fungicide were seen, as fungicide use increased yield by 364 kg ha -1 for both cultivars. Yield was more strongly related to disease severity based on canopy lesion area than to the Florida scale. Yield improvement with York was not as closely related to disease severity with only a 6% gain in pod yield in York compared to Carver. In addition, reduction in TCP was greater in York compared to Carver given their respective disease severity. These results indicated that combining resistance with the maintenance of physiological function during LLS infection could result in improved peanut yields under diseased conditions.

Water stress during the vegetative development normally is not detrimental and sometimes actually increases yield of peanut (Arachis hypogaea L.). Root growth might play an important role in response to early season drought in peanut and might result in an increase in yield. Information on the response of root characters of diverse peanut genotypes to these conditions will provide useful information for explaining mechanisms and improving peanut genotypes for exploiting positive interaction for pod yield under pre-flowering drought. The aim of this study, therefore, was to investigate the root dry weight and root length density of peanut genotypes with different yield responses to pre-flowering drought stress and their relationships with pod yield. Field experiments were conducted at the Field Crop Research Station of Khon Kaen University, Khon Kaen, Thailand during February to July 2007 and during February to July 2009. A split-plot experiment in a randomized complete block design was used. Two water management treatments were assigned as the main plots, i.e. field capacity and pre-flowering stress, and six peanut genotypes as the sub-plots. Total crop dry matter, root dry weight and root length density were recorded at 25 DAE, R5 and R7. Top dry weight and pod yield were measured at harvest and pod harvest index (PHI) was computed using the data on pod yield and biomass. Peanut genotypes were categorized into three groups based on their responses to drought for pod yield, e.g. increasing, decreasing and non-responsive groups. The genotypes of each group showed a differential response for root quantity and distribution. The increasing pod yield group had more root dry weight and root length density in the deeper soil layers during pre-flowering stress compared to the non-stress treatment. The non-responsive group showed no root response under pre-flowering drought conditions compared to the non-stress treatment. A larger root system alone without considering distribution may not contribute much to pod yield but a higher RLD at deeper layers may allow plants to mine more available water in the sub-soil. However, as yield is a complex trait, several mechanisms may be involved. The increasing pod yield group also had the ability to maintain a high PHI.

The picture-winged fly Euxesta stigmatias Loew (Diptera: Ulidiidae) has been a serious pest of sweet corn in Florida since the 1930s and had been considered the only fly infesting Florida corn. In a sweet corn variety trial to evaluate E. stigmatias resistance in 2007, adult Chaetopsis massyla (Walker) (Diptera: Ulidiidae) was reared from the ears. Choice and no-choice trials were conducted in 2007 and 2008 to determine the pest nature of C. massyla on corn. In no choice tests, C. massyla pairs were caged on uninfested corn ears in green house and field trials. In choice tests, field collected corn ears were held for fly emergence. No choice tests showed that C. massyla could infest and complete development in ears that had no previous damage. Chaetopsis massyla emerged from corn ears with and without prior infestation by other insect species in choice tests. Subsequently, C. massyla were reared from corn ears collected from locations throughout the major sweet corn growing region of southern Flo...

Grain sorghum (Sorghum bicolor) crop yield is significantly compromised by high temperature stress-induced male sterility, and is attributed to reduced cell wall invertase (CWI)-mediated sucrose hydrolysis in microspores and anthers leading to altered carbohydrate metabolism and starch deficiency in pollen (Jain et al., 2007). Sorghum plants were grown under season-long ambient (30/20 degrees C day-time maximum/night-time minimum) or high temperature stress (HS, 36/26 degrees C) environments, or reciprocally transferred for 5-10 days between either temperature regimens through panicle and microspore developmental stages. Quantitative RT-PCR analyses for CWI gene SbIncw1, plasma membrane H(+)-ATPase (Mha1) and sugar transporter proteins (OsSUT3 and OsMST7 homologs in sorghum), starch deficiency and pollen sterility data are presented to confirm HS-sensitivity of pre- and post-meiotic stages of sorghum microsporogenesis. Heat stress-induced reduction in Incw transcriptional activity during microspore meiosis was irreversible despite return of optimal growth temperature conditions through further reproductive development.

A greenhouse experiment was conducted using a Soil-N Uptake Monitoring (SUM) system to determine nitrogen (N) and water uptake dynamics of citrus (CIT), perennial peanut (PP) (Arachis glabrata Benth), and common bermudagrass (BG) (Cynodon dactylon L.) over time. We also assessed the competition for water and N uptake between citrus and groundcover species and compared citrus N uptake measured using the SUM system with the 15N method. Nitrogen uptake followed cyclic patterns and was greatest for bermudagrass-based systems, while values were similar for PP and citrus systems. Competition for N uptake did occur during the summer months between citrus and BG, while no obvious competition for N uptake occurred between citrus and PP. Water uptake was greatest for the mixed systems and BG monoculture. Citrus, PP, and BG competed for water during the spring and summer seasons. None of the groundcovers significantly affected overall citrus tree growth. Nitrogen use efficiency was greatest for mixed systems and ber...

SUMMARYPrior on-station research showed that sowing dates, sowing density and applications of fungicide and phosphorus (P) increased groundnut (Arachis hypogaea) pod yield by 60–80%. Farmer-managed trials were conducted in the Wa district of the Upper West Region of Ghana from 2004 to 2007 to test the yield response to sowing density, fungicide and P and to assess economic returns of these technologies to farmers. Treatments included: an early maturing groundnut cultivar, Chinese, sown at farmers' density (5–8 plant m−2) without fungicide and without P application (T1, control), with fungicide sprays alone (T2), or with fungicide and P application (T3), cultivar Chinese sown at recommended (higher) density (20 plant m−2) with fungicide and P application (T4), and a full season cultivar, Manipinter, with fungicide and P application (T5). Soil fertility, sowing density, days from sowing to first weeding, incidence and severity of leaf-spot disease and plant population at final harvest were recorded. Relative to farmers' practice, pod yield of cultivar Chinese was significantly increased by 80% with fungicide sprays alone, 108% with fungicide and P application, and 113% with fungicide and P application at higher sowing density. Cultivar Manipinter treated with fungicide and P gave 107% increase in pod yield relative to farmers' practice. Correlation and stepwise regression analyses suggested that major determinants of groundnut pod yield in farmers' fields were plant density, leaf-spot disease and P availability. The increase in yield with fungicide and P application translated into a 4–5-fold increase in gross margin for farmers in the region. Returns to labour and labour productivity were doubled with combined use of fungicide and P fertilizer.