Simulation of rice planthopper damage for developing pest management decision support tools

Rice planthoppers' damage on Pusa Basmati 1 cultivar was simulated with InfoCrop, a generic crop growth simulation model. The model was calibrated and validated with two experimental data sets on planthopper population and rice yield that were generated through differential insecticide application during the rainy season 2006 and 2007. Simulated yield and total dry matter (TDM) in various treatments over the two experiments were found to be proximal to the observed yields (R² = 0.972, RMSE = 4.61%) and TDM (R² = 0.949, RMSE = 3.25%), respectively. Likewise, the simulated yield and TDM losses were also respectively close to observed yield losses (R² = 0.938, RMSE = 13.53%) and TDM losses (R² = 0.835, RMSE = 19.12%), suggesting appropriate validation of planthopper damage mechanism on Pusa Basmati 1 rice. Economic injury levels (EILs) of planthoppers were simulated with two control expenditures involving two applications with each of monocrotophos and imidacloprid, and three market prices of Pusa Basamti 1 rice. The EIL exhibited a negative relationship with market value of produce but a positive one with expenditure on control measures. Simulated EILs were comparable to earlier established empirical EILs, indicating utility of simulation models for developing location specific EILs that may help in doing away with the use of blanket EILs. Iso-loss curves, devised through validated model, depicted combinations of crop age and planthopper population that resulted in similar yield losses. Both the EILs and iso-loss curves can be useful in monitoring planthopper populations and promoting judicious pesticide applications that would avoid unwarranted control expenditure and environmental contamination. The simulation models being based on detailed crop ecological and physiological processes and pest damage mechanism can thus aid in development of location-specific decision support tools and ensure precision in pest management decisions.     

Quantification of fructan concentration in grasses using NIR spectroscopy and PLSR

Near-infrared reflectance (NIR) spectroscopy combined with chemometrics was used to quantify fructan concentration in samples from seven grass species. Savitzky–Golay first derivative with filter width 7 and polynomial order 2 with mean centering was applied as a spectral pre-treatment method to remove unimportant baseline signals. In order to model the NIR spectroscopy data the partial least squares regression (PLSR) approach was used on the full spectra. Variable selection based on PLSR by jack-knifing within a cross-model validation (CMV) framework was applied in order to remove non-relevant spectral regions. PLSR was also used to model fructan concentrations from an augmented matrix [X|G], where X is spectra and G is correlation matrix of band specific information and X, in order to integrate the chemical band information in regression models. The present analysis showed that rapid quantification of fructans by NIR spectroscopy is possible and that jack-knifing PLSR within a CMV framework is an effective way to eliminate the wavelengths of no interest. Jack-knifing PLSR did not improve the predictive ability because the root mean square error of prediction (RMSEP) increased (1.37) compared to the full model (1.26). This was possibly due to signals from carbohydrates, which could act as cofactor in the prediction of fructans. However, jack-knifing PLSR within a CMV framework simplified the interpretation of the regression model with r² = 0.90 and RMSEP = 1.37.     

Canopy reflectance in two castor bean varieties (Ricinus communis L.) for growth assessment and yield prediction on coastal saline land of Yancheng District, China

A field experiment was conducted in 2007-2009 in coastal saline regions of Yancheng city in Jiangsu province of China (120°13′E, 33°38′N). The experiment was to investigate relationships among canopy spectral reflectance, canopy chlorophyll density (CCD), leaf area index (LAI), and yield of two Chinese castor varieties (Zi Bi var. and Yun Bi var.) across four N fertilizer rates of 0, 90, 180, and 360 kg N ha⁻¹. These N rates were used to generate a wide range of difference in canopy structure and seed yield. Measurements of canopy reflectance were made throughout the growing season using a hand-held spectroradiometer. Samples for CCD and LAI were obtained on days that reflectance measurements were made. Fifteen hyperspectral reflectance indices were calculated. Canopy spectral characteristics were heavily influenced by saline soil background in the rapid growing period (RGP), thus hyperspectral data obtained in this period were not suited for reflecting castor growth condition or predicting final yield. CCD increased linearly with most reflectance indices in the full coverage period (FCP) and senescent period (SP) for the two castor varieties, whereas LAI did not. Most of reflectance indices were significantly correlated with yield of two varieties in different growing periods. The OSAVI model provided the best yield prediction for Zi Bi var. with predicted values very close to observed ones (R² = 0.799), and the mSRVI705 model was well used for Yun Bi var. yield estimation (R² = 0.759). These results indicate that the hyperspectral data measured at appropriate time could be well used for castor yield estimation.     

A model for simulating plant N accumulation,growth and yield of diverse rice genotypes grown under different soil and climatic conditions

The objective of this study was to develop a whole-process model for explaining genotypic and environmental variations in the growth and yield of irrigated rice by incorporating a newly developed sub-model for plant nitrogen (N) uptake into a previously reported model for simulating growth and yield based on measured plant N. The N-uptake process model was developed based on two hypotheses: (1) the rate of root system development in the horizontal direction is proportional to the rate of leaf area index (LAI) development, and (2) root N-absorption activity depends on the amount of carbohydrate allocated to roots. The model employed two empirical soil parameters characterizing indigenous N supply and N loss. Calibration of the N-uptake process sub-model and validation of the whole-process model were made using plant N accumulation, and growth and yield data obtained from a cross-locational experiment on nine rice genotypes at seven locations in Asia, respectively. Calibration of the N-uptake process sub-model indicated that a large genotypic difference exists in the proportionality constant between rate of root system development and that of LAI development during early growth stages. The whole-process model simultaneously explained the observed genotypic and environmental variation in the dynamics of plant N accumulation (R² = 0.91 for the entire dataset), above-ground biomass growth (R² = 0.94), LAI development (R² = 0.78) and leaf N content (R² = 0.79), and spikelet number per unit area (R² = 0.78) and rough grain yield (R² = 0.81). The estimated value of the site (field)-specific soil parameter representing the rate of N loss was negatively correlated with cation exchange capacity of the soil and was approximated by a logarithmic function of cation exchange capacity for seven sites (R² = 0.95). Large yearly and locational variations were estimated in the soil parameter for representing the rate of indigenous N supply at 25 °C. With the use of these two soil parameters, the whole-system model explained the observed genotypic and environmental variations in plant N accumulation, growth and yield of rice in Asia.     

Quantification of the cardinal temperatures and thermal time requirement of opium poppy (Papaver somniferum L.) seeds to germinate using non-linear regression models

The response of plant development rate (including germination rate) to temperature might be described as a non-linear function. We compared 3 non-linear regression models (Dent-like, segmented and beta) to describe the germination rate-temperature relationships of opium poppy (Papaver somniferum L.) over 6 constant temperatures to find cardinal temperatures and thermal time required to reach different germination percentiles. Two replicated experiments were performed with the same temperatures. An iterative optimization method was used to calibrate the models and different statistical indices (mean absolute error, coefficient of determination (R²), intercept and slope of the regression equation of predicted vs. observed germination rate) were applied to compare their performance. The segmented was found to be the best model to predict germination rate (R² = 0.92, MAE = 0.0011 and CV of 1.4-3.6%). Estimated cardinal temperatures were similar for different germination percentiles (P < 0.05). Base on the model outputs, the base, the optimum and the maximum temperatures for germination were estimated as 3.02, 27.36 and 36.31 °C. The thermal time required to reach 50 and 95% germination was 57.27 and 87.55 degree-days, respectively. Model predictions of the time required for seed germination agreed reasonably well with the observed times (MAE = 0.56 day, R² = 0.887). All model parameters may be readily used in crop simulation models.     

Hyperspectral remote sensing of yellow mosaic severity and associated pigment losses in Vigna mungo using multinomial logistic regression models

Yellow mosaic disease (YMD) has been a serious threat to blackgram cultivation especially during post-monsoon season. Visual assessment of disease severity is qualitative and time consuming. Rapid and non-destructive estimation of YMD by hyperspectral remote sensing has not been attempted so far on any of its hosts. Field studies were conducted for two seasons with eight blackgram genotypes having differential response to YMD. Comparison of mean reflectance spectra of the healthy and YMD infested leaves showed changes in all the broad band regions. However, reflectance sensitivity analysis of the narrow-band hyperspectral data revealed a sharp increase in reflectance from the diseased leaves compare to healthy at 669 (red), 505 and 510 nm (blue). ANOVA showed a significant decrease in leaf chlorophyll (p < 0.0001) with increase in disease severity, while no such relationship was observed for relative water content. By plotting coefficients of determination (R²) between leaf chlorophyll and percent reflectance at one nm wavelength interval, two individual bands (R₅₇₁; R₇₀₅) and two band ratios (R₅₇₁/R₇₂₁; R₇₀₅/R₅₉₃) with highest R² values were selected. These bands showed a significant linear relationship with SPAD chlorophyll readings (R² range 0.781–0.814) and spectrometric estimates of total chlorophyll content (R² range 0.477–0.565). Further, the relationship was stronger for band ratios compared to single bands. With optimal spectral reflectance ratios as inputs, disease prediction models were built using multinomial logistic regression (MLR) technique. Based on model fit statistics, reflectance ratios R₅₇₁/R₇₂₁ and R₇₀₅/R₅₉₃ were found better than the individual bands R₅₇₁ and R₇₀₅. Validation of MLR models using an independent test data set showed that the overall percentage of correct classification of the plant into one of the diseased categories was essentially same for both the ratios (68.75%). However, the MLR model using R₇₀₅/R₅₉₃ as dependent variable was of greater accuracy as it gave lower values of standard errors for slopes (β_G range 9.79–36.73) and highly significant estimates of intercept and slope (p < 0.05). Thus the models developed in this study have potential use for rapid and non-destructive estimation of leaf chlorophyll and yellow mosaic disease severity in blackgram.     

Baseline and differential sensitivity to mandipropamid among isolates of Peronophythora litchii, the causal agent of downy blight on litchi

Litchi downy blight caused by Peronophythora litchii is a devastating disease of litchi plants in China. Control of litchi downy blight requires numerous fungicide applications. A new carboxylic acid amide (CAA) fungicide, mandipropamid, was examined for its in vitro effects on multiple asexual stages of four single-sporangium P. litchii isolates and protective activity against downy blight in detached fruit assays. Though mandipropamid did not affect discharge of zoospores from sporangia, it strongly inhibited mycelial growth (mean EC₅₀ = 0.0048 μg ml⁻¹), sporangia production (mean EC₅₀ = 0.0032 μg ml⁻¹), germination of encysted zoospores (mean EC₅₀ = 0.0023 μg ml⁻¹), and germination of sporangia (mean EC₅₀ = 0.0061 μg ml⁻¹). On detached fruit, 0.39, 1.56 and 6.25 μg ml⁻¹ of mandipropamid were superior in reducing downy blight compared to metalaxyl and flumorph, however, the 25 μg ml⁻¹ application rate was necessary for all three CAA fungicides to completely inhibit the disease. In 2007, 100 isolates from Fujian, Guangdong, and Guangxi Provinces of China were characterized for the baseline sensitivity to mandipropamid. The isolates obtained from different provinces showed similar baseline sensitivities to mandipropamid. Baseline sensitivities formed a unimodal curve with mean EC₅₀ values of 0.0055 ± 0.0012 μg ml⁻¹ for inhibition of mycelial growth. The described baseline sensitivities of P. litchii populations will be useful for monitoring possible shifts in sensitivity to mandipropamid.     

Prediction of maize seed attributes using a rapid single kernel near infrared instrument

Non-destructive measurements of seed attributes would significantly enhance breeder selection of seeds with specific traits, and could potentially improve hybrid development. A single kernel near infrared reflectance (NIR) instrument was developed for rapidly predicting maize grain attributes, which would enable plant breeders to quickly select promising individual seeds. With the overall goal being to develop spectrometric calibrations, absorbance spectra from 904 to 1685 nm were collected from 87 maize samples, with 30 kernels of each sample (2610 kernels total), representing a wide variability in the essential amino acids tryptophan and lysine, crude protein, oil and soluble sugar contents. Average sample spectra were matched to bulk reference values. Partial least squares regression (PLSR) calibration models with cross-validation were developed for both relative (% dry matter) and absolute (mg kernel⁻¹) constituent contents. Similarly, models using bagging PLSR were developed. The best model obtained was for relative crude protein content, with an R²p of 0.75 and a SEP of 0.47%. Kernel mass was also highly predictable (R²p=0.76, SEP=0.03 g). Tryptophan, lysine and oil were less predictable, but showed good potential for segregating individual seeds using NIR. Soluble sugar contents produced poor model statistics. Bagging PLSR yielded models with similar levels of prediction.     

Ecophysiological determinants of biomass and grain yield of wheat under P deficiency

Grain yield of crops can be expressed as a function of the intercepted radiation, the radiation use efficiency and the partitioning of above-ground biomass to grain yield (harvest index). When a wheat crop is grown under P deficiency the grain yield is reduced but it is not clear how these three components are affected. Our aim was (i) to identify which of these components were affected in spring bread wheat under P deficiency at field conditions and (ii) to relate the grain yield responses to processes of grain yield formation during the spike growth period. Three field experiments were conducted in the potentially high wheat yielding environment of southern Chile. All experiments had two levels of P availability: with (155 kg P ha⁻¹) or without P fertilization (average soil P-Olsen concentration of 10 ppm, a medium level of P availability). High wheat grain yields were obtained varying between 815 and 1222 g m⁻² with P applications. Experiments showed a grain yield reduction caused by P deficiencies of 35, 16 and 18% in experiments 1, 2 and 3, respectively. This was related (R² = 0.99, P < 0.01) to a reduction in the total above-ground biomass at harvest and not to the harvest index. Reductions in above-ground biomass were due to a reduction in radiation intercepted under P deficiency without effecting radiation use efficiency. Grain number per square meter was the main yield component (R² = 0.99, P < 0.01) that explained the grain yield reduction caused by the P deficiency which was due to low spike biomass at anthesis (R² = 0.96, P < 0.05). The reduction in spike biomass at anthesis was related (R² = 0.86, P < 0.01) to reductions in crop growth rate during the spike growth period as a consequence of a lower radiation intercepted during this period. This study showed that under high wheat yield conditions the main effect of a P deficiency on grain yield reduction was a negative impact on the total above-ground biomass due to the negative impact on intercepted radiation, particularly during the spike growth period, affecting negatively spike biomass at anthesis and consequently grain number and yield.     

A model for explaining genotypic and environmental variation in vegetative biomass growth in rice based on observed LAI and leaf nitrogen content

The objectives of this study are to propose a model for explaining the genotypic and environmental variation in above-ground biomass growth via photosynthesis and respiration processes from transplanting to heading for different rice genotypes grown under a wide range of environments, and to identify the physiological traits associated with genotypic difference in the biomass growth based on model analysis. Cross-locational experiments were conducted with nine different rice genotypes at eight locations in Asia covering a wide climate range under irrigated conditions with sufficient nitrogen application. The crop growth rate observed during the period from transplanting to heading ranged from 3.4 to 19.4 g m⁻² d⁻¹ among the genotypes grown at the eight locations. About one-third of the data sets were utilized for model calibration and the remaining sets were used for model validation. An above-ground biomass growth model was developed by integrating processes of single leaf photosynthesis as a function of stomatal conductance and leaf nitrogen content, growth and maintenance respiration and crop development. To rigorously examine the validity of this process model, measured data were input as external variables for leaf area index (LAI) development and leaf nitrogen content per unit leaf area. The model well explained the observed dynamics in above-ground biomass growth (R² = 0.95*** for validation dataset) of nine rice genotypes grown under a variety of environments in Asia. The model simulation suggested that genotypic difference in the biomass growth was closely related to the difference in the stomatal conductance and leaf nitrogen content, as well as to LAI. This paper proposes the model structure, algorithms and all parameter values contained in the model, and discuss its effectiveness as a component of a more comprehensive model for simulating dynamics of biomass growth, LAI development and nitrogen uptake as a function of genotypic coefficients and environments.     

Spectral measurements of the total aerial N and biomass dry weight in maize using a quadrilateral-view optic

Heterogeneous crop stands require locally adapted nitrogen fertilizer application based on rapid and precise measurements of the local crop nitrogen status. In the present study, we validated a promising technique for the latter, namely a tractor-mounted field spectrometer with an oblique quadrilateral-view measuring optic, measuring solar radiation and canopy reflectance in four directions simultaneously. Dry matter yield (kg ha⁻¹), total N content (g N g⁻¹ dry matter) and total aerial N (aboveground N-uptake) (kg N ha⁻¹) in maize were determined in 10 m² calibration areas in 60 plots differing in their N treatment and seeding density three times in each of three years under field conditions. Results show that the sensor used can reliably determine total aerial N ranging from as little as 5 kg N to 150 kg N ha⁻¹ with R²-values ≥0.81 in 2002 and 2004, and with R²-values ranging from ≥0.57 to 0.84 in 2003. Dry matter yields from as low as 0.3–4.2 t ha⁻¹ could be determined with R²-values ranging from 0.67 to 0.91 in 2002 to 2004. The capacity to ascertain DM yield spectrally was drastically reduced in the higher yield range (>6 t ha⁻¹) probably due to decreased sensitivity of the spectral signal. N-contents were generally not well determined. Taken together there is a good potential to determine reliably differences in total aerial N or DM yield from the five leaf stages unfolded to the five node stage where typically nitrogen applications are carried out.     

Kernel number determination differs among maize hybrids in response to nitrogen

In maize, the effects of nitrogen (N) deficiencies on the determination of kernel number per plant (KNP) have been described only by changes in plant growth rate during the critical period for kernel set (PGRcp). We hypothesize that N availability affects KNP also through variations in biomass allocation to the ear, which determines a stable N concentration in this organ. Six maize hybrids of different breeding origin were evaluated in field experiments at two N levels (0 and 400 kg N ha⁻¹ applied). Traits included were KNP and per apical ear (KN_E1), and the allometric estimation of PGRcp, ear growth rate during the critical period (EGRcp), and N content and N concentration in different plant organs. We demonstrated that (i) N availability promoted differences among genotypes (G) in the response of EGRcp and KNP to PGRcp, (ii) variations in KN_E1 were explained by EGRcp (r² = 0.64) and by ear N content at silking + 12 d (r² = 0.64), and (iii) ear N concentration was a highly conservative trait (range between 10.47 and 15.98 mg N g biomass⁻¹) as compared to N concentration in vegetative tissues (range between 4.94 and 18.04 mg N g biomass⁻¹). Three response patterns were detected among hybrids, one for which the relationship between EGRcp and PGRcp did not vary between N levels and experiments, a second one for which N availability affected this relationship, and a third one for which the response was affected by the year (Y) effect. These results, together with the high correlation between EGRcp and ear N content (r² = 0.88), evidenced the importance of both photo-assimilate and N availability on EGRcp and KNP determination. Values of 1.5–2.3 g ear⁻¹ d⁻¹ during the critical period and 0.49–0.70 g of N ear⁻¹ at silking + 12 d were determined as thresholds for maximizing KN_E1, and both could be easily estimated by means of allometric models.     

Mineral fertilizer response and nutrient use efficiencies of East African highland banana (Musa spp., AAA-EAHB,cv. Kisansa)

Poor yields of East African highland bananas (Musa spp., AAA-EAHB) on smallholder farms have often been attributed to problems of poor soil fertility. We measured the effects of mineral fertilizers on crop performance at two sites over two to three crop cycles; Kawanda in central Uganda and Ntungamo in southwest Uganda. Fertilizers were applied at rates of 0N–50P–600K, 150N–50P–600K, 400N–0P–600K, 400N–50P–0K, 400N–50P–250K and 400N–50P–600K kg ha⁻¹ yr⁻¹. In addition 60Mg–6Zn–0.5Mo–1B kg ha⁻¹ yr⁻¹ was applied to all treatments, with the exception of the control plots which received no fertilizer. Fresh bunch mass and yield increased with successive cycles. Yield increases above the control ranged from 3.1 to 6.2 kg bunch⁻¹ (average bunch weight for all treatments 11.5 kg bunch⁻¹) and 2.2–11.2 Mg ha⁻¹ yr⁻¹ (average yield for all treatments 15.8 Mg ha⁻¹ yr⁻¹) at Kawanda, compared with 12.4–16.0 kg bunch⁻¹ (average bunch weight for all treatments 14.7 kg bunch⁻¹) and 7.0–29.5 Mg ha⁻¹ yr⁻¹ (average yield for all treatments 17.9 Mg ha⁻¹ yr⁻¹) at Ntungamo. The limiting nutrients at both sites were in the order K > P > N. Potassium, N and P foliar nutrient mass fractions were below previously established Diagnosis and Recommendation Integrated System (DRIS) norms, with the smallest K mass fractions observed in the best yielding plots at Ntungamo. Total nutrient uptakes (K > N > P) were higher at Ntungamo as compared with Kawanda, probably due to better soil moisture availability and root exploration of the soil. Average N, P and K conversion efficiencies for two crop cycles at both sites amounted to 49.2 kg finger DM kg⁻¹ N, 587 kg finger DM kg⁻¹ P and 10.8 kg finger DM kg⁻¹ K. Calibration results of the model QUEFTS using data from Ntungamo were reasonable (R² = 0.57, RMSE = 648 kg ha⁻¹). Using the measured soil chemical properties and yield data from an experiment at Mbarara in southwest Uganda, the calibrated QUEFTS model predicted yields well (R² = 0.68, RMSE = 562 kg ha⁻¹). We conclude that banana yields can be increased by use of mineral fertilizers, but fertilizer recovery efficiencies need to improve substantially before promoting wide-scale adoption.     

Environmental effects on seed yield determination of irrigated peanut crops: Links with radiation use efficiency and crop growth rate

In Argentina, delayed sowing causes a decrease in seed yield and in radiation use efficiency (RUE) of peanut crops (Arachis hypogaea L.), but it is not known if RUE reduction is mainly due to reduced temperature during late reproductive stages or to a sink limitation promoted by decreased seed number in these conditions. We analyzed seed yield determination and RUE dynamics of two cultivars (Florman and ASEM) in four irrigated field experiments (Exp_n) grown at three sites and five contrasting sowing dates (between 17 October and 21 December) in three growing seasons. An additional field experiment was performed with widely spaced plants (i.e. with no interference among them) to evaluate the effect of peg removal on RUE and leaf carbon exchange rate (CER). Seasonal dynamics of mean air temperature and irradiance, biomass production (total and pods), and intercepted photosynthetically active radiation (IPAR) were followed. Seed yield and seed yield components (pod number, seeds per pod, seed number and seed weight) were determined at final harvest. Crop growth rate (CGR) and pod growth rate (PGR) were computed for growth phases of interest. RUE values for crops sown until 14 November were 1.89–1.98 g MJ⁻¹ IPAR, within the usual range. RUE decreased significantly for cv. Florman in the late sowing of Exp₁ (29 November) and for both cultivars in Exp₃ (21 December sowing). Across experiments, seed yield (4.5-fold variation relative to minimum) was strongly associated (r² = 0.87, P < 0.0001) with variations in seed number (3.5-fold variation relative to minimum), and to a lesser extent (r² ≤ 0.54, P ≤ 0.001) to variations in seed weight (1.9-fold variation relative to minimum). Seed number was positively related (P < 0.01) to CGR (r² = 0.66) and to PGR (r² = 0.72) during the R₃–R_6.5 phase (seed number determination window), while crop growth during the grain-filling phase (i.e. between R_6.5 and final harvest) was positively associated with grain number (r² = 0.80, P < 0.001). No association was found between RUE and mean air temperature, neither for the whole cycle nor for the phase between R_6.5 and final harvest, which showed the largest temperature variation (16.4–22.4 °C) across experiments. Use of mean minimum temperature records (range between 13.8 and 18.5 °C) did no improve the relationship. However, grain-filling phase RUE showed a positive (r² = 0.69, P = 0.003) linear response to seed number across experiments. This apparent sink limitation of source activity was consistent with the reduced RUE (from 2.73 to 1.42 g MJ⁻¹ IPAR) and reduced leaf CER at high irradiance (from ca. 30 to 15 μmol m⁻² s⁻¹) for plants subjected to 75% peg removal.     

Evaluating cultivars in unbalanced on-farm participatory trials

Data from on-farm participatory varietal trials are often highly unbalanced. Using statistically robust techniques we showed that such data are amenable to sophisticated analyses. Data from 38 varieties of wheat tested in 44 mother trials (all test varieties compared) and 663 baby trials (single entries compared with local checks) over 6 years in Lunawada, Gujarat, India, were analysed. Two combined analyses for grain yield were performed by using either a fixed effects model within general linear modelling (GLM) or a mixed effects model using the restricted maximum likelihood (REML) procedure. Both analyses made substantial adjustments over the raw means and the estimated mean values from the two analyses for the fixed set of tested varieties were highly correlated (R² = 0.89) as were the t-value that compared test cultivars with the check variety (R² = 0.96). The GLM detected 15 varieties and REML detected 12 varieties that were significantly superior to the check cultivar with 11 varieties in common. Both methods were similar in identifying the top-most promising varieties but REML was more conservative (i.e. more subject to Type II error) with larger standard errors (S.E.s) of variety means for n > 17. However, for both procedures the S.E.s increased sharply when the number of trials decreased below 17.     

Water and nitrogen balance of sweet sorghum (Sorghum bicolor moench (L.)) cv. Keller under semi-arid conditions

In the framework of the E.U. project Fair CT 96-1913 “Environmental studies on sweet and fibre sorghum, sustainable crops for biomass and energy”, a research has been carried out with the aim to study the water and nitrogen balance and determine the critical N dilution curve of sweet sorghum cv. Keller. A field experiment was performed, where three irrigation treatments (I₀ = dry control, I₅₀ = 50% ETm restoration, I₁₀₀ = 100% ETm restoration) and four nitrogen fertilization levels (N₀ = no nitrogen control, N₆₀ = 60 kg ha⁻¹, N₁₂₀ = 120 kg ha⁻¹; N₁₈₀ = 180 kg ha⁻¹) were studied. The final yield was significantly affected by the amount of water distributed but not by the nitrogen level. The treatments watered up to crop establishment (I₀) produced, in the average, 7.5 t ha⁻¹ of dry matter, against 21.1 and 27.1 t ha⁻¹ of I₅₀ and I₁₀₀, respectively. The crop determined a great reduction in nitrate concentration of soil water, irrespective of nitrogen supplied. The variation between N output and input (Δ) was negative in N₀, N₆₀ and N₁₂₀ and positive in N₁₈₀. The critical value of nitrogen uptake change in relation to the water availability. The amount of nitrogen supplied did not determine significant differences upon WUE. The crop seems to have a great potentiality in Mediterranean environment in terms of yield production.     

Relationship between P and N concentrations in maize and wheat leaves

Simple plant-based diagnostic tools can be used to determine crop P status. Our objectives were to establish the relationships between P and N concentrations of the uppermost collared leaf (P_L and N_L) of spring wheat (Triticum aestivum L.) and maize (Zea mays L.) during the growing season and, in particular, to determine the critical leaf P concentrations required to diagnose P deficiencies. Various N applications were evaluated over six site-years for wheat and eight site-years for maize (2004-2006) with adequate soil P for growth. Phosphorus and N concentrations of the uppermost collared leaf were determined weekly and the relationships between leaf N and P concentrations were established using only the sampling dates from the stem elongation stage for wheat and from the V8 stage of development for maize. Leaf P concentration generally decreased with decreasing N fertilization. Relationships between P_L and N_L concentrations (mg g⁻¹ DM) using all site-years and sampling dates were described by significant linear-plateau functions in both maize (P_L = 0.82 + 0.089 N_L if N_L ≤ 32.1 and P_L = 3.7 if N_L > 32.1; R² = 0.41; P < 0.001) and wheat (P_L = 0.02 + 0.106 N_L if N_L ≤ 33.2 and P_L = 3.5 if N_L > 33.2; R² = 0.42; P < 0.001). Variation among sampling dates in the relationships were noted. By restricting the sampling dates [413-496 growing degree days (5 °C basis) in wheat (i.e., stem elongation) and 1494-1579 crop heat units in maize (i.e., silking), relationships for wheat (P_L = 0.29 + 0.073 N_L, R² = 0.66; P < 0.001) and maize (P_L = 1.04 + 0.084 N_L, R² = 0.66; P < 0.001) were improved. In maize, expressing P and N concentrations on a leaf area basis (P_LA and N_LA) at silking further improved the relationship (P_LA = 0.002 + 0.101 N_LA, R² = 0.80; P < 0.001). Predictive models of critical P concentration as a function of N concentration in the uppermost collared leaf of wheat and maize were established which could be used for diagnostic purposes.     

Genetic gains in grain yield, net photosynthesis and stomatal conductance achieved in Henan Province of China between 1981 and 2008

Knowledge of the changes in agronomic and photosynthetic traits associated with genetic gains in grain yield potential is essential for an improved understanding of yield-limiting factors and for determining future breeding strategies. The objectives of this study were to identify agronomic and photosynthetic traits associated with genetic gains in grain yield of facultative wheat (Triticum aestivum L.) between 1981 and 2008 in Henan Province, the most important wheat producing area in China. During the 2006-2007 and 2007-2008 crop seasons, a yield potential trial comprising 18 leading and new cultivars released between 1981 and 2008 was conducted at two locations, using a completely randomised block design of three replicates. Results showed that average annual genetic gain in grain yield was 0.60% or 51.30 kg ha⁻¹ yr⁻¹, and the significant genetic improvement in grain yield was directly attributed to increased thousand grain weight which also contributed to the significant increase in harvest index. The genetic gains in rates of net photosynthesis at 10, 20 and 30 days after anthesis were 1.10% (R² = 0.46, P < 0.01), 0.68% (R² = 0.31, P < 0.05) and 6.77% (R² = 0.34, P < 0.05), respectively. The rates of net photosynthesis at 10 (r = 0.58, P < 0.05), 20 (r = 0.59, P < 0.05) and 30 (r = 0.65, P < 0.01) days after anthesis were closely and positively correlated with grain yield. A slight decrease in leaf temperature and an increase in stomatal conductance after anthesis were also observed. Grain yield was closely and positively associated with stomatal conductance (r = 0.69, P < 0.01) and transpiration rate (r = 0.63, P < 0.01) at 30 days after anthesis. Therefore, improvement of those traits was the likely basis of increasing grain yield in Henan Province between 1981 and 2008. The genetic improvement in yield was primarily attributed to the utilization of two elite parents Yumai 2 and Zhou 8425B. The future challenge of wheat breeding in this region is to maintain the genetic gain in grain yield and to improve grain quality, without increasing inputs for the wheat-maize double cropping system.     

Predicting hot-press wheat tortilla quality using flour,dough and gluten properties

A cost-effective, faster and efficient way of screening wheat samples suitable for tortilla production is needed. This research aimed to develop prediction models for tortilla quality (diameter, specific volume, color and texture parameters) using grain, flour and dough properties of 16 wheat flours. Another set of 18 samples was used to validate the models. The prediction models were developed using stepwise multiple regression. Dough rheological tests had higher correlations with tortilla quality than grain and flour chemical tests. Mixograph mixing time and dough resistance to extension (from extensibility test using a texture analyzer) were correlated best with tortilla quality, particularly tortilla diameter (r = −0.87 and −0.86 respectively, P < 0.01). Insoluble polymeric proteins (IPP) and gluten index were significantly correlated with tortilla diameter (r = −0.70 and −0.67 respectively, P < 0.01) and specific volume (r = −0.73, P < 0.01). Tortilla diameter was the quality parameter best explained (R² = 0.86) by the prediction models using mixing time and dough resistance to extension. Rheological parameters such as rupture distance and maximum force were also successfully predicted. These prediction models, developed from linear equations, will be an easy and fast tool for breeders to advance or eliminate wheat lines specifically bred for tortilla production.     

Stratification of sorghum hybrid testing sites in southern Africa based on grain yield

Sequential retrospective (SeqRet) pattern analysis technique was applied to classify sorghum hybrid testing sites in accordance with their similarity for yield differentiation among genotypes. Historical grain yield data from 150 multi-environment trials (METs) conducted at 23 sites in the Southern Africa Development Community (SADC) region during 1987/1988–1992/1993 was used. The sites were clustered into six major environment groups in the SADC region with a model fit of R² = 68%. Analysis of these 6 years’ data together with additional data from 1999/2000 stratified the 23 sites in the same six major groups (R² = 69%), the additional five sites in 1999/2000 classified with appropriate site groups. These results suggest that future sorghum hybrid testing could be cost-effectively conducted in a few representative sites selected from within each of the six identified site groups.