Uncertainty assessment methodologies applied to Tritium production in fusion lithium breeding blankets

- Need of Tritium production - Neutronic objectives - The Frascati experiment - Measurements of Tritium activity

Future trends in Animal Breeding due to new genetic tecnologies

The Darwin theory of evolution by natural selection is based on three principles: (a) variation; (b) inheritance; and (c) natural selection. Here, I take these principles as an excuse to review some topics related to the future research prospects in Animal Breeding. With respect to the first principle I describe two forms of variation different from mutation that are becoming increasingly important: variation in copy number and microRNAs. With respect to the second principle I comment on the possible relevance of non-mendelian inheritance, the so-called epigenetic effects, of which the genomic imprinting is the best characterized in domestic species. Regarding selection principle I emphasize the importance of selection for social traits and how this could contribute to both productivity and animal welfare. Finally, I analyse the impact of molecular biology in Animal Breeding, the achievements and limitations of quantitative trait locus and classical marker-assisted selection and the future of genomic selection

CSM-IXIM: A New Maize Simulation Model for DSSAT Version 4.5

Th e CERES-Maize model is the most widely used maize (Zea mays L.) model and is a recognized reference for comparing new developments in maize growth, development, and yield simulation. Th e objective of this study was to present and evaluate CSMIXIM, a new maize simulation model for DSSAT version 4.5. Code from CSM-CERES-Maize, the modular version of the model, was modifi ed to include a number of model improvements. Model enhancements included the simulation of leaf area, C assimilation and partitioning, ear growth, kernel number, grain yield, and plant N acquisition and distribution. Th e addition of two genetic coeffi cients to simulate per-leaf foliar surface produced 32% smaller root mean square error (RMSE) values estimating leaf area index than did CSM-CERES. Grain yield and total shoot biomass were correctly simulated by both models. Carbon partitioning, however, showed diff erences. Th e CSM-IXIM model simulated leaf mass more accurately, reducing the CSM-CERES error by 44%, but overestimated stem mass, especially aft er stress, resulting in similar average RMSE values as CSM-CERES. Excessive N uptake aft er fertilization events as simulated by CSM-CERES was also corrected, reducing the error by 16%. Th e accuracy of N distribution to stems was improved by 68%. Th ese improvements in CSM-IXIM provided a stable basis for more precise simulation of maize canopy growth and yield and a framework for continuing future model developments

Real-time image processing for crop/weed discrimination in maize fields

This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving

Optimizing rabbit production under heat stress: cage density and cage size during fattening, and breeding system and water quality on rabbit does

The aim of this work was to evaluate different management strategies to optimize rabbit production under chronic heat stress. To achieve it, three trials were conducted. In the first trial, to find the optimal cage density in tropical very dry forest condition, were measured growth performance, mortality rate, injured animals and carcass performance over an initial population of 300 cross-breed rabbits of New Zealand, California, Butterfly, Dutch and Satin, weaned at 30 days (535 ± 8 g, standard error). Treatments evaluated were: 6, 12, 18 and 24 rabbits/m2 (3, 6, 9 and 12 rabbits/cage, respectively, each cage of 0.5 m2). The maximal temperature-humidity index indicated a severe heat stress from weaning to 2.2 kg body weight (experimental time). At the end of experimental period 10, 20, 30 and 30 rabbits from the treatments of 6, 12, 18 and 24 rabbits/m2, respectively, were slaughtered and carcass performance recorded. Average daily gain and feed intake decreased by 0.31 ± 0.070 and 1.20 ± 0.25 g, respectively, per each unit that the density increased at the beginning of the experiment (P = 0.001). It increased the length of the fattening period by 0.91 ± 0.16 d (P = 0.001) per each unit of increment of density. However, rabbit production (kg/m2) increased linear and quadratically with the density (P < 0.008). Animals housed at the highest density compared to the lower one tended to show a higher incidence of ringworm (68.9 vs 39.4%; P = 0.075), injured animals (16.8 vs 3.03%; P = 0.12) and mortality (20.5 vs 9.63%; P = 0.043). The proportion of scapular fat (P = 0.042) increased linearly with increasing levels of density. Increasing density reduced linearly dorsal length (P = 0.001), and reduced linear and quadratically drip loss percentage (P = 0.097 and 0.018, respectively). In the second trial, 46 nulliparous rabbit does (23 clipped and 23 unclipped) with a BW of 3.67 ± 0.05 kg (s.e.) were used to evaluate heat stress and circadian rhythms comparing unclipped and clipped rabbit does, and to study if a more extensive breeding system increase litters performance at weaning without impairing rabbit doe performance,. Rectal temperature, feed and water 4 intake were recorded for 24 h. Rabbit does were mated 7 d after circadian measurements, and randomly assigned to two breeding systems. Control (C): mated at 14 d after parturition + litter weaned at 35 d of age. Extensive (E): mate at 21 after parturition + litter weaned at 42 d of age. The first three cycles were evaluated concerning to rabbit doe and litter performance. Two hundred twenty eight weaned rabbits, were divided into two cage sizes: 0.5 and 0.25 m2 with same density (16 rabbit/m2) and growing performance was recorded. Farm and rectal temperatures were minimal and feed and water intake maximal during the night (P < 0.001). Unclipped rabbit does showed higher rectal temperature (P = 0.045) and lower feed intake respect to clipped does (P = 0.019) which suggest a lower heat stress in the latter. Kits weaned per litter was reduced by 33% (P=0.038) in C group. This reduction was more important in the 2nd and 3rd cycles compared to the first (P ≤ 0.054). Rabbit doe feed efficiency tended to decrease in E respect C group (P = 0.093), whereas it was impaired from the first to the third cycle by 48% (P = 0.014). Growing rabbits from the E group were heavier at weaning (by 38%. P < 0.001), showed a higher feed intake (+7.4%) and lower feed efficiency (-8.4%) throughout the fattening period (P ≤ 0.056) respect to C group. Cage size had minor influence in growing performance. In the third trial, forty five non pregnant and non lactating rabbit does (21 nulliparous and 24 multiparous) were assigned randomly to farm water and to potable water to study if a water quality improvement can affect positively rabbit doe response to heat stress during pregnancy and lactation. A transponder was implanted in each animal to record subcutaneous temperature at 07:30 and 14:30 h. Experimental period extended from pregnancy (with no lactation) to the next lactation (until day 28). Body temperature and milk production were recorded daily, and body condition, feed and water intake weekly. Water quality did not affect any trait (P ≥ 0.15). Pregnant rabbit does were classified as does that weaned (W: 47%), not weaned (NW: 44%) or those pregnant that did not deliver (NB: 9%). Body temperature and feed intake decreased during pregnancy (P ≤ 0.031), but water intake remained constant. In this period body temperature decreased with metabolic weight (P ≤ 0.009). In W and NW does, 5 from mating to birth energy and protein balance impaired (P≤0.011). Body temperature of W does tended to be the lowest (P ≤ 0.090). Pregnancy length and total number of kits born tended to be longer and higher in NW than in W does (P = 0.10 and 0.053, respectively). Kit mortality at birth and from birth to 14 d of lactation was high, being worse for NW than for W does (97 vs. 40%; P<0.001). Body temperature during lactation was maximal at day 12, and milk production increased it (P ≤ 0.025). . In conclusion, in our heat stress conditions densities higher than 18 rabbits/m2 (34 kg/m2) at the end of fattening, are not recommended despite cage size, gestation and lactation productivity impaired not only when lactation is extended and along successive reproductive cycles but also due to a reduced embryo/kit survival and finally water quality improvement did not attenuate negative effect of heat stress. RESUMEN El propósito de éste trabajo fue evaluar diferentes estrategias de manejo para optimizar la producción de conejos bajo estrés térmico. Para lo cual se desarrollaron tres experimentos. En el primer experimento, para encontrar el número óptimo de gazapos por m2 de jaula durante el cebo en condiciones de bosque muy seco tropical, se estudiaron los rendimientos durante el cebo, mortalidad, animales lesionados y rendimiento de la canal sobre una población inicial de 300 conejos mestizos de Nueva Zelanda, California, Mariposa, Holandés y Satin, destetados a los 30 días de edad (535 ± 8g, error estándar). Los tratamientos evaluados fueron: 6, 12, 18 y 24 conejos/m2 (3, 6, 9 y 12 conejos/jaula, respectivamente, en jaulas de 0.5 m2). Durante el período experimental (destete a 2.2 kg de peso vivo), se observaron valores de THI correspondientes con un estrés térmico severo (THI max. De 31 a 35). Al final del período experimental, 10, 20, 30, y 30 conejos de los tratamientos con densidades de 6, 12, 18 y 24 conejos/m2, respectivamente, fueron sacrificados y su canal fue valorada. El promedio de la ganancia diaria y el consumo de alimento disminuyeron en 0.31 ± 0.070 y 1.20 ± 0.25 g, respectivamente, por cada unidad de incremento en la densidad al inicio del experimento (P=0.001). Esto alargó el período de engorde en 0.91 ± 0.16 d (P=0.001) por cada unidad de incremento de la densidad. Sin embargo, la producción de conejos (kg/m2) aumentó lineal y cuadráticamente con la densidad (P<0.008). Los animales alojados en las mayores densidades en comparación con el resto tendieron a mostrar una mayore incidencia de tiña (68.9 vs 39.4%; P=0.075), de cantidad de animales heridos (16.8 vs 3.03%; P=0.12), así como de mortalidad (20.5 vs 9.63%; P=0.043). El aumento en la densidad aumentó linealmente la proporción de grasa escapular (P=0.042) y redujo linealmente la longitud dorsal (P=0.001), y lineal y cuadráticamente el porcentaje de pérdida por goteo (P=0.018). En el segundo experimento, 46 conejas nulliparas (23 rasuradas y 23 no rasuradas) con un peso vivo de 3.67 ± 0.05 kg (e.e.) fueron usadas para evaluar el estrés 8 térmico y los ritmos circadianos comparando conejas rasuradas o no, y estudiar si un sistema de crianza más extensivo mejora el desempeño de la camada al destete sin perjudicar la productividad de la coneja. Durante 24 h se midió la temperatura rectal, consumo de alimento y de agua. Las conejas fueron montadas 7 días después, y distribuidas en dos sistemas de crianza. El control (C): monta a 14 días posparto y destete a 35 d de edad. El extensivo (E): monta a 21 días posparto y destete a 42 d de edad. Se controló la productividad de la coneja y la camada durante los tres primeros ciclos. Doscientos veintiocho gazapos fueron distribuidos en dos tamaños de jaulas (0.5 y 0.25 m2) con la misma densidad (16 conejos/m2) y se controlaron sus rendimientos productivos. Durante la noche se observaron los valores mínimos para la temperatura ambiental y rectal, y los máximos para consumo de alimento y agua (P< 0.001). Las conejas no rasuradas mostraron mayor temperatura rectal (P=0.045) y menores valores de consumo de alimento con respecto a las conejas rasuradas (P=0.019), lo que sugiere un menor estrés térmico en las últimas. El número de gazapos destetados por camada se redujo en 33% (P=0.038) en el grupo C. Este comportamiento se acentuó en el 2do y 3er ciclo en comparación con el primero (P≤0.054). La eficiencia alimenticia de las conejas tendió a disminuir en el grupo E con respecto al grupo C (P=0.093), dicha tendencia se acentúa del primer al tercer ciclo en un 48% (P=0.014). Los gazapos en fase de crecimiento provenientes del grupo E fueron más pesados al momento del destete (en 38% P<0.001), mostrando un mayor consumo de alimento (+7.4%) y menor eficiencia alimenticia (-8.4%) a lo largo del engorde (P≤0.056) con respecto al grupo C. El tamaño de la jaula tuvo una mínima influencia en el comportamiento durante el crecimiento de éstos gazapos. En el tercer experimento, cuarenta y cinco conejas no gestantes ni lactantes (21 nulíparas y 24 multíparas) se les asignó al azar agua dos tipos de agua: común de la granja y agua potable, con el fin de estudiar si una mejora en la calidad del agua puede afectar positivamente la respuesta de la coneja al estrés térmico durante la gestación y la lactancia. Se les implantó un transponder para registrar la temperatura subcutánea a las 7:30 y a las 14:30 h. El período experimental se extendió desde la gestación (sin 9 lactancia) hasta la lactanción consecutiva (hasta los 28 días). La temperatura corporal y la producción de leche se controlaron diariamente, y la condición corporal, consumo de agua y alimento, semanalmente. La calidad del agua no afectó a ninguna variable (P≥0.15). Las conejas preñadas fueron clasificadas como conejas que destetaron (W: 47%), que no destetaron (NW:44%) o aquellas que no parieron (NB: 9%). La temperatura corporal y consumo de alimento disminuyeron durante la gestación (P≤0.031), mientras que el consumo de agua se mantuvo constante. La temperatura corporal descendió con el peso metabólico durante la gestación (P≤0.009). El balance de energía y proteína disminuyó desde la monta al parto para las conejas W y NW (P≤0.011). Durante la gestación la temperatura corporal tendió a ser menor en las conejas W (P≤0.090). La longitud de la gestación y el número total de gazapos nacidos tendieron a ser mayores en conejas NW que en conejas W (P=0.10 y 0.053, respectivamente). La mortalidad de los gazapos al parto y del parto a los 14 días de lactancia fue alta, siendo peor para las conejas NW que para las W (97 vs 40%; P<0.001). Durante la lactancia la temperatura corporal alcanzó su valor máximo para el día 12, y la producción de leche indujo un incremento en la misma (P≤0.025). En conclusión, en nuestras condiciones de estrés térmico y sin importar el tamaño de la jaula, no se recomiendan densidades mayores a 18 conejos/m2 (34 kg/m2) al final del engorde. La productividad de la gestación y la lactancia disminuyen cuando la lactancia es mayor y se suceden varios ciclos reproductivos seguidos. Esto se debe al efecto negativo del estrés térmico sobre la vitalidad y supervivencia del embrión/gazapo. La mejora de la calidad del agua atenuó el efecto negativo del estrés térmico. Las conejas más productoras parece que son aquéllas que consiguen manejar mejor el estrés térmico.

Climate Change Impacts on Maize and Dry Bean Yields of smallholder farmers in Honduras

The rotation maize and dry bean provides the main food supply of smallholder farmers in Honduras. Crop model assessment of climate change impacts (2070?2099 compared to a 1961?1990 baseline) on a maize?dry bean rotation for several sites across a range of climatic zones and elevations in Honduras. Low productivity systems, together with an uncertain future climate, pose a high level of risk for food security. The cropping systems simulation dynamic model CropSyst was calibrated and validated upon field trail site at Zamorano, then run with baseline and future climate scenarios based upon general circulation models (GCM) and the ClimGen synthetic daily weather generator. Results indicate large uncertainty in crop production from various GCM simulations and future emissions scenarios, but generally reduced yields at low elevations by 0 % to 22 % in suitable areas for crop production and increased yield at the cooler, on the hillsides, where farming needs to reduce soil erosion with conservation techniques. Further studies are needed to investigate strategies to reduce impacts and to explore adaptation tactics.

Effects of different soil management practices on soil mechanic resistance and seed depth placement in a maize crop in Alentejo, Portugal Mediterranean region.

No tillage, minimum tillage and conventional tillage practices are commonly used in maize crops in Alentejo, affecting soil physic conditions and determining seeders performance. Seeders distribution can be evaluated in the longitudinal and vertical planes. Vertical plane is specified by seeding depth (Karayel et al., 2008). If, in one hand seeding depth uniformity is a goal for all crop establishment , in the other hand, seeders furrow openers depth control is never constant depending on soil conditions. Seed depth uniformity affects crop emergence, Liu et al. (2004) showed an higher correlation between crop productivity and emergence uniformity than with longitudinal plants distribution. Neto et al. (2007) evaluating seed depth placement by measuring maize mesocotyl length under no tillage conditions in 38 farms concluded that 20% of coefficient of variation suggests the need of improvement seeders depth control mechanisms. The objective of this study was to evaluate casual relationships and create spatial variability maps between soil mechanic resistance and vertical distribution under three different soil practices to improve seed depth uniformity.

Automatic detection of crop rows in maize fields with high weeds pressure

This paper proposes a new method, oriented to crop row detection in images from maize fields with high weed pressure. The vision system is designed to be installed onboard a mobile agricultural vehicle, i.e. submitted to gyros, vibrations and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of three main processes: image segmentation, double thresholding, based on the Otsu’s method, and crop row detection. Image segmentation is based on the application of a vegetation index, the double thresholding achieves the separation between weeds and crops and the crop row detection applies least squares linear regression for line adjustment. Crop and weed separation becomes effective and the crop row detection can be favorably compared against the classical approach based on the Hough transform. Both gain effectiveness and accuracy thanks to the double thresholding that makes the main finding of the paper.

Crop row detection in maize fields inspired on the human visual perception

This paper proposes a new method, oriented to image real-time processing, for identifying crop rows in maize fields in the images. The vision system is designed to be installed onboard a mobile agricultural vehicle, that is, submitted to gyros, vibrations, and undesired movements. The images are captured under image perspective, being affected by the above undesired effects. The image processing consists of two main processes: image segmentation and crop row detection. The first one applies a threshold to separate green plants or pixels (crops and weeds) from the rest (soil, stones, and others). It is based on a fuzzy clustering process, which allows obtaining the threshold to be applied during the normal operation process. The crop row detection applies a method based on image perspective projection that searches for maximum accumulation of segmented green pixels along straight alignments. They determine the expected crop lines in the images. The method is robust enough to work under the above-mentioned undesired effects. It is favorably compared against the well-tested Hough transformation for line detection.

Even-sowing pattern strategies for a low-input agricultural system in forage maize

The objective of this study was to verify the effectiveness of new patterns of sowing and to achieve a low-input organic system in two different environments (northern and southern Europe). The study was motivated by the hypothesis that more even sowing patterns (triangular and square) would significantly enhance the growth and yield of forage maize under widely varying conditions, compared with traditional mechanised rectangular seed patterns. An experiment was conducted in Madrid and duplicated in Copenhagen during 2010. A random block design was used with a 2 × 2 factorial arrangement based on two seed-sowing patterns: traditional (rectangular) and new (even) and two weed-management conditions (herbicide use and a low-input system). In both weed-management conditions and locations, the production of aerial maize biomass was greater for the new square seed patterns. In addition, the new pattern showed a greater effectiveness in the control of weeds, both at the initial crop stages (36 and 33% fewer weeds m-2 at the 4- and 8-leaf stages, respectively, in the Copenhagen field experiment) and at the final stage. The final weed biomass for the new pattern was 568 kg ha-1 lower for the Copenhagen experiment and 277 kg ha-1 lower in Madrid field experiments. In the light of these results, the new pattern could potentially reduce the use of herbicides. The results of the experiments support the hypothesis formulated at the beginning of this study that even-sowing patterns would be relatively favourable for the growth and yield of the maize crop. In the near future, new machinery could be used to achieve new seed patterns for the optimisation of biomass yield under low-input systems. This approach is effective because it promotes natural crop-weed competition.

Calibration of WAVE in irrigated maize: fallow vs. cover crops.

Nitrate leaching decreases crop available N and increases water contamination. Replacing fallow by cover crops (CC) is an alternative to reduce nitrate contamination, because it reduces overall drainage and soil mineral N accumulation. A study of the soil N and nitrate leaching was conducted during 5 years in a semi-arid irrigated agricultural area of Central Spain. Three treatments were studied during the intercropping period of maize (Zea mays L.): barley (Hordeum vulgare L.), vetch (Vicia villosa L.), and fallow. Cover crops, sown in October, were killed by glyphosate application in March, allowing direct seeding of maize in April. All treatments were irrigated and fertilised following the same procedure. Soil water content was measured using capacity probes. Soil Nmin accumulation was determined along the soil profile before sowing and after harvesting maize. Soil analysis was conducted at six depths every 0.20m in each plot in samples from 0 to 1.2-m depth. The mechanistic water balance model WAVE was applied in order to calculate drainage and plant growth of the different treatments, and apply them to the N balance. We evaluated the water balance of this model using the daily soil water content measurements of this field trial. A new Matlab version of the model was evaluated as well. In this new version improvements were made in the solute transport module and crop module. In addition, this new version is more compatible with external modules for data processing, inverse calibration and uncertainty analysis than the previous Fortran version. The model showed that drainage during the irrigated period was minimized in all treatments, because irrigation water was adjusted to crop needs, leading to nitrate accumulation on the upper layers after maize harvest. Then, during the intercrop period, most of the nitrate leaching occurred. Cover crops usually led to a shorter drainage period, lower drainage water amount and lower nitrate leaching than the treatment with fallow. These effects resulted in larger nitrate accumulation in the upper layers of the soil after CC treatments.

Role of maize stover incorporation on nitrogen oxide emissions in a non-irrigated Mediterranean barley field.

Aims Agricultural soils in semiarid Mediterranean areas are characterized by low organic matter contents and low fertility levels. Application of crop residues and/or manures as amendments is a cost-effective and sustainable alternative to overcome this problem. However, these management practices may induce important changes in the nitrogen oxide emissions from these agroecosystems, with additional impacts on carbon dioxide emissions. In this context, a field experiment was carried out with a barley (Hordeum vulgare L.) crop under Mediterranean conditions to evaluate the effect of combining maize (Zea mays L.) residues and N fertilizer inputs (organic and/or mineral) on these emissions. Methods Crop yield and N uptake, soil mineral N concentrations, dissolved organic carbon (DOC), denitrification capacity, N2O, NO and CO2 fluxes were measured during the growing season. Results The incorporation of maize stover increased N2O emissions during the experimental period by c. 105 %. Conversely, NO emissions were significantly reduced in the plots amended with crop residues. The partial substitution of urea by pig slurry reduced net N2O emissions by 46 and 39 %, with and without the incorporation of crop residues respectively. Net emissions of NO were reduced 38 and 17 % for the same treatments. Molar DOC:NO 3 − ratio was found to be a robust predictor of N2O and NO fluxes. Conclusions The main effect of the interaction between crop residue and N fertilizer application occurred in the medium term (4–6 month after application), enhancing N2O emissions and decreasing NO emissions as consequence of residue incorporation. The substitution of urea by pig slurry can be considered a good management strategy since N2O and NO emissions were reduced by the use of the organic residue.

Spatial variability of seed depth placement of maize under no tillage.

Among the various factors that contribute towards producing a successful maize crop, seed depth placement is a key determinant, especially in a no-tillage system. The main objective of this work was to evaluate the spatial variability of seed depth placement and crop establishment in a maize crop under no-tillage conditions, using precision farming technologies. The obtained results indicate that seed depth placement was significantly affected by soil moisture content, while a very high coefficient of variation of 39% was found for seed depth. Seeding depth had a significant impact on mean emergence time and percentage of emerged plants. Shallow average depth values and the high coefficient of variation suggest a need for improvement in controlling the seeder sowing depth.

How do various maize crop models vary in their responses to climate change factors?

Comments This article is a U.S. government work, and is not subject to copyright in the United States. Abstract Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly 0.5 Mg ha 1 per °C. Doubling [CO2] from 360 to 720 lmol mol 1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.

Automatic expert system based on images for accuracy crop row detection in maize fields

This paper proposes an automatic expert system for accuracy crop row detection in maize fields based on images acquired from a vision system. Different applications in maize, particularly those based on site specific treatments, require the identification of the crop rows. The vision system is designed with a defined geometry and installed onboard a mobile agricultural vehicle, i.e. submitted to vibrations, gyros or uncontrolled movements. Crop rows can be estimated by applying geometrical parameters under image perspective projection. Because of the above undesired effects, most often, the estimation results inaccurate as compared to the real crop rows. The proposed expert system exploits the human knowledge which is mapped into two modules based on image processing techniques. The first one is intended for separating green plants (crops and weeds) from the rest (soil, stones and others). The second one is based on the system geometry where the expected crop lines are mapped onto the image and then a correction is applied through the well-tested and robust Theil–Sen estimator in order to adjust them to the real ones. Its performance is favorably compared against the classical Pearson product–moment correlation coefficient.