The Role of Fresh versus Old Leaf Damage in the Attraction of Parasitic Wasps to Herbivore-Induced Maize Volatiles

The odor produced by a plant under herbivore attack is often used by parasitic wasps to locate hosts. Any type of surface damage commonly causes plant leaves to release so-called green leaf volatiles, whereas blends of inducible compounds are more specific for herbivore attack and can vary considerably among plant genotypes. We compared the responses of naïve and experienced parasitoids of the species Cotesia marginiventris and Microplitis rufiventris to volatiles from maize leaves with fresh damage (mainly green leaf volatiles) vs. old damage (mainly terpenoids) in a six-arm olfactometer. These braconid wasps are both solitary endoparasitoids of lepidopteran larvae, but differ in geographical origin and host range. In choice experiments with odor blends from maize plants with fresh damage vs. blends from plants with old damage, inexperienced C. marginiventris showed a preference for the volatiles from freshly damaged leaves. No such preference was observed for inexperienced M. rufiventris. After an oviposition experience in hosts feeding on maize plants, C. marginiventris females were more attracted by a mixture of volatiles from fresh and old damage. Apparently, C. marginiventris has an innate preference for the odor of freshly damaged leaves, and this preference shifts in favor of a blend containing a mixture of green leaf volatiles plus terpenoids, after experiencing the latter blend in association with hosts. M. rufiventris responded poorly after experience and preferred fresh damage odors. Possibly, after associative learning, this species uses cues that are more directly related with the host presence, such as volatiles from host feces, which were not present in the odor sources offered in the olfactometer. The results demonstrate the complexity of the use of plant volatiles by parasitoids and show that different parasitoid species have evolved different strategies to exploit these signals.

Increasing the Glutathione Content in a Chilling-Sensitive Maize Genotype Using Safeners Increased Protection against Chilling-Induced Injury

With the aim of analyzing their protective function against chilling-induced injury, the pools of glutathione and its precursors, cysteine (Cys) and gamma -glutamyl-Cys, were increased in the chilling-sensitive maize (Zea mays) inbred line Penjalinan using a combination of two herbicide safeners. Compared with the controls, the greatest increase in the pool size of the three thiols was detected in the shoots and roots when both safeners were applied at a concentration of 5 muM. This combination increased the relative protection from chilling from 50% to 75%. It is interesting that this increase in the total glutathione (TG) level was accompanied by a rise in glutathione reductase (GR; EC 1.6.4.2) activity. When the most effective safener combination was applied simultaneously with increasing concentrations of buthionine sulfoximine, a specific inhibitor of glutathione synthesis, the total gamma -glutamyl-Cys and TG contents and GR activity were decreased to very low levels and relative protection was lowered from 75% to 44%. During chilling, the ratio of reduced to oxidized thiols first decreased independently of the treatments, but increased again to the initial value in safener-treated seedlings after 7 d at 5 degreesC. Taking all results together resulted in a linear relationship between TG and GR and a biphasic relationship between relative protection and GR or TG, thus demonstrating the relevance of the glutathione levels in protecting maize against chilling-induced injury.

Inhibition of glutathione synthesis reduces chilling tolerance in maize

The role of glutathione (GSH) in protecting plants from chilling injury was analyzed in seedlings of a chilling-tolerant maize (Zea mays L.) genotype using buthionine sulfoximine (BSO), a specific inhibitor of gamma-glutamylcysteine (gamma EC) synthetase, the first enzyme of GSH synthesis. At 25 degrees C, 1 mM BSO significantly increased cysteine and reduced GSH content and GSH reductase (GR: EC 1.6.4.2) activity, but interestingly affected neither fresh weight nor dry weight nor relative injury. Application of BSO up to 1 mM during chilling at 5 degrees C reduced the fresh and dry weights of shoots and roots and increased relative injury from 10 to almost 40%. Buthionine sulfoximine also induced a decrease in GR activity of 90 and 40% in roots and shoots, respectively. Addition of GSH or gamma EC together with BSO to the nutrient solution protected the seedlings from the BSO effect by increasing the levels of GSH and GR activity in roots and shoots. During chilling, the level of abscisic acid increased both in controls and BSO-treated seedlings and decreased after chilling in roots and shoots of the controls and in the roots of BSO-treated seedlings, but increased in their shoots. Taken together, our results show that BSO did not reduce chilling tolerance of the maize genotype analyzed by inhibiting abscisic acid accumulation but by establishing a low level of GSH. which also induced a decrease in GR activity.

Yield prediction and inbreeding of maize synthetics generated with lines and single crosses : classic probability

reduce costs and labor associated with predicting the genotypic mean (GM) of a synthetic variety (SV) of maize (Zea mays L.), breeders can develop SVs from L lines and s single crosses (SynL,SC) instead of L+2s lines (SynL). The objective of this work was to derive and study formulae for the inbreeding coefficient (IC) and GM of SynL,SC, SynL, and the SV derived from (L+2s)/2 single crosses (SynSC). All SVs were derived from the same L+2s unrelated lines whose IC is FL, and each parent of a SV was represented by m plants. An a priori probability equation for the IC was used. Important results were: 1) the largest and smallest GMs correspond to SynL and SynL,SC, respectively; 2) the GM predictors with the largest and intermediate precision are those for SynL and SynL,SC, respectively; 3) only when FL=1, or m is large, SynL and SynSC are the same population, but only with SynSC prediction costs and labor undergo the maximum decrease, although its prediction precision is the lowest. To determine the SV to be developed, breeders should also consider the availability of lines, single crosses, manpower and land area; besides budget, target farmers, target environments, etc.

Effect of compost and slow-release fertilizers addition on soil biochemistry and yield of maize (Zea mays L.) in Oaxaca, Mexico

The effect of Bokashi (B, a fermented compost), slow-release fertilizers (SRFs) and their combined application on mycorrhizal colonization (MC), soil invertase, cellulase, acid (AcP) and alkaline (AlP) phosphatases activities and maize (Zea mays L.) yield was investigated in terrace (TS) and valley (VS) soils in Oaxaca, Mexico. A complete randomized design, seven fertilizer treatments and four replications were used: unamended control (C); conventional fertilization (90-46-00 NPK) (CF); B; SRF1 (Multigro 6®, 21-14-10 NPK); SRF2 (Multigro 3®, 24-05-14 NPK); B+SRF1; B+SRF2. Highest root colonization percentage: CF in VS, and SRF2 in TS. Highest extraradical mycelium length: B, B+SRF1, CF in VS, and B+SRF1 in TS. In both soils, B increased the spore number. Highest AcP activity: B, SRF2 in VS, and B+SRF1, B+SRF2 in TS. Highest AlP activity: B+SRF1, CF in VS, and C in TS. Highest invertase activity: B+SRF1, SRF2, CF in VS, and B in TS. Grain yield only increased with B in VS. The significant interaction soil type × fertilizer treatment for the majority of the biological soil properties analyzed suggests that MC and soil enzyme activity response to fertilization was influenced by soil type. Bokashi, alone or combined with SRFs improves biological soil fertility in maize fields.

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

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.