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.     

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.     

Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars

Several sensor systems are available for ground-based remote sensing in crop management. Vegetation indices of multiple active and passive sensors have seldom been compared in determining plant health. This work describes a study comparing active and passive sensing systems in terms of their ability to recognize agronomic parameters. One bi-directional passive radiometer (BDR) and three active sensors, including the Crop Circle, GreenSeeker, and an active flash sensor (AFS), were tested for their ability to assess six destructively determined crop parameters. Over 2 years, seven wheat (Triticum aestivum L.) cultivars were grown with nitrogen supplies varying from 0 to 220 kg ha⁻¹. At three developmental stages, the crop reflectance was recorded and sensor-specific indices were calculated and related to N levels and the crop parameters, fresh weight, dry weight, dry matter content, as percent of dry weight to fresh weight, N content, aboveground N uptake, and the nitrogen nutrition index. The majority of the tested indices, based on different combinations of wavelengths in the visible and near infrared spectral ranges, showed high r²-values when correlated with the crop parameters. However, the accuracy of discriminating the influence of varying N levels on various crop parameters differed between sensors and showed an interaction with growing seasons and developmental stage. Visible- and red light-based indices, such as the NDVI, simple ratio (R₇₈₀/R₆₇₀), and related indices tended to saturate with increasing crop stand density due to a decreased sensitivity of the spectral signal. Among the destructively assessed biomass parameters, the best relationships were found for N-related parameters, with r²-values of up to 0.96. The near infrared-based index R₇₆₀/R₇₃₀ was the most powerful and temporarily stable index indicating the N status of wheat. This index was delivered by the BDR, Crop Circle, and AFS. Active spectral remote sensing is more flexible in terms of timeliness and illumination conditions, but to date, it is bound to a limited number of indices. At present, the broad spectral information from bi-directional passive sensors offers enhanced options for the future development of crop- or cultivar-specific algorithms.     

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.     

Effect of water management on dry seeded and puddled transplanted rice: Part 2: Water balance and water productivity

Labour and water scarcity in north west India are driving researchers and farmers to find alternative management strategies that will increase water productivity and reduce labour requirement while maintaining or increasing land productivity. A field experiment was done in Punjab, India, in 2008 and 2009 to compare water balance components and water productivity of dry seeded rice (DSR) and puddled transplanted rice (PTR). There were four irrigation schedules based on soil water tension (SWT) ranging from saturation (daily irrigation) to alternate wetting drying (AWD) with irrigation thresholds of 20, 40 and 70 kPa at 18–20 cm soil depth. There were large and significant declines in irrigation water input with AWD compared to daily irrigation in both establishment methods. The irrigation water savings were mainly due to reduced deep drainage, seepage and runoff, and to reduced ET in DSR. Within each irrigation treatment, deep drainage was much higher in DSR than in PTR, and more so in the second year (i.e. after 2 years without puddling). The irrigation input to daily irrigated DSR was similar to or higher than to daily irrigated PTR. However, within each AWD treatment, the irrigation input to DSR was less than to PTR, due to reduced seepage and runoff, mainly because all PTR treatments were continuously flooded for 2 weeks after transplanting. There was 30–50% irrigation water saving in DSR-20 kPa compared with PTR-20 kPa due to reduced seepage and runoff, which more than compensated for the increased deep drainage in DSR. Yields of PTR and DSR with daily irrigation and a 20 kPa irrigation threshold were similar each year. Thus irrigation and input water productivities (WP_I and WP_I+R) were highest with the 20 kPa irrigation threshold, and WP_I of DSR-20 kPa was 30–50% higher than of PTR-20 kPa. There was a consistent trend for declining ET with decreasing frequency of irrigation, but there was no effect of establishment method on ET apart from higher ET in DSR than PTR with daily irrigation. Water productivity with respect to ET (WP_ET) was highest with a 20 kPa irrigation threshold, with similar values for DSR and PTR. An irrigation threshold of 20 kPa was the optimum in terms of maximising grain yield, WP_I and WP_I+R for both PTR and DSR. Dry seeded rice with the 20 kPa threshold outperformed PTR-20 kPa in terms of WP_I through maintaining yield while reducing irrigation input by 30–50%.     

Estimating N status of winter wheat using a handheld spectrometer in the North China Plain

Excessive nitrogen (N) fertilizer application is very common in the North China Plain. Diagnosis of in-season N status in crops is critical for precision N management in this area. Remote sensing, as a timely and nondestructive tool, could be an alternative to traditional plant testing for diagnosing crop N status. The objectives of this study were to determine which vegetation indices could be used to estimate N status in winter wheat (Triticum aestivum L.) under high N input conditions, develop models to predict winter wheat N uptake using spectral vegetation indices and validate the models with data from farmers’ fields. An N rate experiment and a variety-N experiment were conducted in Huimin, Shandong Province from 2005/2006 to 2006/2007 to develop the models. Positive linear relationships between simple ratio vegetation indices (red vegetation index, RVI and green vegetation index, GVI) and N uptake were observed independent of growth stages and varieties (R², 0.48–0.74). In contrast, the relationships between normalized difference vegetation indices (NDVI and GNDVI), red and green normalized difference vegetation index (RGNDI), and red and green ratio vegetation index (RGVI) were exponentially related to N uptake (R², 0.43–0.79). Subsequently, 69 farmers’ fields in four different villages were selected as datasets to validate the developed models. The results indicated that the prediction using RVI had the highest coefficient of determination (R², 0.60), the lowest root mean square error (RMSE, 39.7 kg N ha⁻¹) and relative error (RE, 30.5%) across different years, varieties and growth stages. We conclude that RVI can be used to estimate nitrogen status for winter wheat in over-fertilized farmers’ fields before heading.     

A model explaining genotypic and environmental variation in leaf area development of rice based on biomass growth and leaf N accumulation

Leaf area index (LAI) is one of the major determinants of crop photosynthesis. The objectives of this study were to clarify the relationship between LAI development and crop growth in diverse rice genotypes grown under widely different climate conditions and to develop a model explaining genotypic and environmental variation in LAI dynamics based on environmental and plant factors. 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 LAI observed at the heading stage ranged from 0.85 to 8.77 among the genotypes grown at the eight locations. A fairly stable allometric relationship was observed between LAI development and above-ground biomass growth during the period from transplanting to 2 weeks before heading over all the genotypes, sites and years (r = 0.91). The allometric relationship was, however, under the influence of leaf nitrogen content per unit leaf area (LNC, g m⁻² leaf) and air temperature. On the basis of these results, we modeled the LAI development as a function of relative crop growth rate (RGR), LNC and air temperature. The rate of LAI decrease associated with leaf senescence was also described as a function of LNC.     

Al toxicity effects on radiation interception and radiation use efficiency of Al-tolerant and Al-sensitive wheat cultivars under field conditions

Soil acidity and Al toxicity are highly extended in agricultural lands of Chile, especially where wheat is widely sown. To evaluate quantitatively the response of wheat biomass and its physiological determinants (intercepted radiation and radiation use efficiency) to Al toxicity, two field experiments were conducted in an Andisol in Valdivia (39°47′S, 73°14′W), Chile, during the 2005–2006 and 2006–2007 growing seasons. Treatments consisted of a factorial arrangement of: (i) two spring wheat cultivars with different sensitivity to Al toxicity (the sensitive cultivar: Domo.INIA and the tolerant cultivar: Dalcahue.INIA) and (ii) five exchangeable Al levels (from 0 to 2.7 cmol₍₊₎ kg⁻¹) with three replicates. Crop phenology and intercepted radiation (IR) were registered during the entire crop cycle, while 10 samples of above-ground biomass were taken at different stages between double ridge and maturity. Both biomass and leaf area index (LAI) were recorded in these 10 stages. Radiation use efficiency (RUE) was calculated as the slope of the relationship between accumulated above-ground biomass and accumulated photosynthetically active radiation intercepted by the canopy (IPARa). Crop phenology was little affected by soil Al treatments, showing only up to 17 days delay in the Al-sensitive cultivar under extreme Al treatments. Above-ground biomass at harvest was closely associated (R² = 0.92) with the crop growth rate but no relationship (R² = 0.14) was found between the crop cycle length. IPARa explained almost completely (R² = 0.93) the above-ground biomass reached by the crop at harvest under the wide range of soil Al concentrations explored in both experiments. On the other hand, a weaker relationship was found between above-ground biomass and RUE. The effect of soil Al concentration on IPARa was mainly explained by LAI as a single relationship (R² = 0.93) between IR (%) and LAI at maximum radiation interception showing a common light attenuation coefficient (k = 0.33).     

Improving in-season nitrogen recommendations for maize using an active sensor

An active crop canopy reflectance sensor could be used to increase N-use efficiency in maize (Zea mays L.), if temporal and spatial variability in soil N availability and plant demand are adequately accounted for with an in-season N application. Our objective was to evaluate the success of using an active canopy sensor for developing maize N recommendations. This study was conducted in 21 farmers’ fields from 2007 to 2009, representing the maize production regions of east central and southeastern Pennsylvania, USA. Four blocks at each site included seven sidedress N rates (0–280 kg N ha⁻¹) and one at-planting N rate of 280 kg N ha⁻¹. Canopy reflectance in the 590 nm and 880 nm wavelengths, soil samples, chlorophyll meter (SPAD) measurements and above-ground biomass were collected at the 6th–7th-leaf growth stage (V6–V7). Relative amber normalized difference vegetative index (ANDVI_relative) and relative SPAD (SPAD_relative) were determined based on the relative measurements from the zero sidedress treatment to the 280 kg N ha⁻¹ at-planting treatment. Observations from the current study were compared to relationships between economic optimum N rate (EONR) and ANDVI_relative, presidedress NO₃ test (PSNT), or SPAD_relative that were developed from a previous study. These comparisons were based on an absolute mean difference (AMD) between observed EONR and the previously determined predicted relationships. The AMD for the relationship between EONR and ANDVI_relative in the current study was 46 kg N ha⁻¹. Neither the PSNT (AMD = 66 kg N ha⁻¹) nor the SPAD_relative (AMD = 72 kg N ha⁻¹) provided as good an indicator of EONR. When using all the observations from the two studies for the relationships between EONR and the various measurements, ANDVI_relative (R² = 0.65) provided a better estimate of EONR than PSNT (R² = 0.49) or SPAD_relative (not significant). Crop reflectance captured similar information as the PSNT and SPAD_relative, as reflected in strong relationships (R² > 0.60) among these variables. Crop canopy reflectance using an active sensor (i.e. ANDVI_relative) provided as good or better an indicator of EONR than PSNT or SPAD_relative, and provides an opportunity to easily adjust in-season N applications spatially.     

Effect of thermal modification on the properties of narrow-leaved ash and chestnut

The concept of thermal modification has evolved from a challenging research program to commercial reality in several European countries in recent years. The aim of this study is to determine the change of various physical properties (oven-dry density, air-dry density, weight loss, swelling and anti-swelling efficiency (ASE)), compression strength parallel to grain, colour difference (ΔE), glossiness and surface roughness of narrow-leaved ash (Fraxinus angustifolia Vahl.) and chestnut (Castanea sativa Mill.) woods after heat treatment under different temperatures and durations. For this study two different temperatures (160 °C and 180 °C) and two different durations (2 h and 4 h) were considered. A stylus method was employed to evaluate the surface characteristics of the samples. Roughness measurements by the stylus method were made in the direction perpendicular to the fiber. Four main roughness parameters which are mean arithmetic deviation of profile (R_a), mean peak-to-valley height (R_z), root mean square roughness (R_q), and maximum roughness (R_y) obtained from the surface of wood were used to evaluate the effect of heat treatment on the surface characteristics of the specimens. The properties studied were significantly different (p = 0.05) at two temperatures and two durations of heat treatment. Based on the findings of this study, the results showed that oven-dry density, air-dry density, swelling, compression strength parallel to grain and surface roughness decreases with increasing heat treatment temperature and time.     

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.     

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.     

Partitioning of glutenin flour of special wheat using aqueous two-phase systems

The partitioning behavior of the glutenin proteins was evaluated in aqueous two-phase systems (ATPSs) formed by sulfate salts (lithium or sodium) and poly(ethylene glycol) (PEG) with average molar mass of 1500 g mol⁻¹ or 4000 g mol⁻¹. The partition coefficients for the glutenin proteins in each ATPS were investigated as a function of the temperature (278.2 K–318.2 K), tie line length (TLL) and electrolyte nature. In all ATPS, the majority of glutenin proteins spontaneously concentrate in the polymer-rich phase (K_p > 1). The partition coefficient is very dependent on the salt nature and the ATPS formed by PEG + lithium sulfate presents higher K_p values as compared with the ATPS formed PEG + sodium sulfate. An increase of molar mass of polymer promotes a decrease of K_p. Thermodynamic parameters of transfer (Δ_trG, Δ_trH and Δ_trS) were obtained by the application of the Van’t Hoff equation (VHE). The values obtained by VHE indicate that the transfer of glutenin proteins to the polymer-rich phase has an enthalpic origin.     

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.     

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.     

基于优化光谱指数的新疆春小麦冠层叶绿素含量估算

为筛选可用于干旱半干旱区春小麦冠层叶绿素含量估算的高光谱植被指数,2017年通过测定春小麦关键生育时期冠层的田间高光谱与叶绿素含量,利用光谱指数波段优化算法分别计算400～1 300 nm光谱波段中不同波段两两组合的比值光谱指数(ration spectral index,RSI)、归一化光谱指数(normalized difference spectral index,NDSI)、叶绿素指数(chlorophyll index,CI)、简化光谱指数(CI/NDSI,NPDI),并将这些参数及其他17个不同高光谱植被指数分别与实测冠层叶绿素含量进行Pearson相关分析,通过变量重要性准则筛选最优光谱参数,使用偏最小二乘回归法建立冠层叶绿素含量的预测模型。结果表明:(1)RSIs、NDSIs、CIs和NPDIs与冠层叶绿素含量的相关性都优于前人研究中定义的17种高光谱植被指数,并且冠层叶绿素含量与NDSI(R_(849),R_(850))、RSI(R_(849),R_(850)),CI(R_(849),R_(850))和NPDI(R_(849),R_(850))表现出强相关性。(2)用此4个优化光谱指数分别建模时,以CI(R_(849),R_(850))、 CI(R_(539),R_(553))、 CI(R_(540),R_(553))、 CI(R_(536),R_(553))为自变量的X-3模型预测精度最高(r~2=0.74,RMSE=0.272 mg·g~(-1))。(3)结合4个优化光谱指数构建的组合模型预测精度,其r~2=0.83,RMSE=0.187 mg·g~(-1)。     

Improvement of growth and gymnemic acid production by altering the macro elements concentration and nitrogen source supply in cell suspension cultures of Gymnema sylvestre R. Br

Gymnema sylvestre is an important medicinal plant which bears bioactive compound namely gymnemic acids. The present work deals with optimization of cell suspension culture system of G. sylvestre for the production of biomass and gymnemic acid and we investigated effects of macro elements (NH₄NO₃, KNO₃, CaCl₂, MgSO₄ and KH₂PO₄ - 0.0, 0.5, 1.0, 1.5 and 2.0× strength) and nitrogen source [NH₄⁺/NO₃⁻ ratio of: 0.00/18.80, 7.19/18.80, 14.38/18.80, 21.57/18.80, 28.75/18.80, 14.38/0.00, 14.38/9.40, 14.38/18.80, 14.38/28.20 and 14.38/37.60 (mM)] of Murashige and Skoog medium on accumulation of biomass and gymnemic acid content. The highest accumulation of biomass (165.00 g l⁻¹ FW and 15.42 g l⁻¹ DW) was recorded in the medium with 0.5× concentration of NH₄NO₃ and the highest production of gymnemic acid content was recorded in the medium with 2.0× KH₂PO₄ (11.32 mg g⁻¹ DW). The NH₄⁺/NO₃⁻ ratio also influenced cell growth and gymnemic acid production; both parameters were greater when the NO₃⁻ concentration was higher than that of NH₄⁺. Maximum biomass growth (159.72 g l⁻¹ of FW and 14.95 g l⁻¹ of DW) was achieved at an NH₄⁺/NO₃⁻ ratio of 7.19/18.80, and gymnemic acid production was also greatest at the same concentration of NH₄⁺/NO₃⁻ ratio (11.35 mg g⁻¹ DW).     

Field-based evaluation of vernalization requirement,photoperiod response and earliness per se in bread wheat (Triticum aestivum L.)

Vernalization requirement, photoperiod response and earliness per se (EPS) of bread wheat cultivars are often determined using controlled environments. However, use of non-field conditions may reduce the applicability of results for predicting field performance as well as increase the cost of evaluations. This research was undertaken, therefore, to determine whether field experiments could replace controlled environment studies and provide accurate characterization of these three traits among winter wheat cultivars. Twenty-six cultivars were evaluated under field conditions using two natural photoperiod regimes (from different transplanting dates) and vernalization pre-treatments. Relative responses to vernalization (RRV_GDD) and photoperiod (RRP_GDD) were quantified using the reciprocal of thermal time to end of ear emergence, whereas earliness per se was estimated by calculating thermal time from seedling emergence until end of ear emergence for fully vernalized and lately planted material. An additional index based on final leaf numbers was also calculated to characterize response to vernalization (RRV_FLN). To test whether the obtained indices have predictive power, results were compared with cultivar parameters estimated for the CSM-Cropsim-CERES-Wheat model Version 4.0.2.0. For vernalization requirement, RRV_GDD was compared with the vernalization parameter P1V, for photoperiod (RRP_GDD), with P1D, and for earliness per se, EPS was compared with the sum of the component phase durations. Allowing for variation in EPS in the calibration improved the relation between observed versus simulated data substantially: correlations of RRP_GDD with P1D increased from r² = .34 (p < .01), to .82 (p < .001), and of RRV_GDD with P1V, from r² = .88 (p < .001), to .94 (p < .001). In comparisons of observed versus simulated anthesis dates for independent field experiments, the estimated model coefficients resulted in an r² of .98 (p < .001) and root mean square error of 1d. Overall, the results indicated that combining planting dates with vernalization pre-treatments can permit reliable, quantitative characterization of vernalization requirement, photoperiod response and EPS of wheat cultivars. Furthermore, emphasize the need for further study to clarify aspects that determine EPS, including whether measured EPS varies with temperature or other factors.     

Uptake and use efficiency of N, P, K, Ca and Al by Al-sensitive and Al-tolerant cultivars of wheat under a wide range of soil Al concentrations

The impacts of acidic soils and Al toxicity on wheat nutrient economy have been scarcely researched under field conditions even though these soils are widely spread in wheat production areas around the world. The main objective of this study was to quantitatively evaluate the element (N, P, K, Ca and Al) economy of an Al-sensitive and an Al-tolerant wheat cultivar growing under different soil Al concentrations at field conditions. To reach this objective, two field experiments were conducted in an Andisol in Valdivia (39°47′18″S, 73°14′05″W), Chile. Treatments were a factorial arrangement of: (i) two spring wheat cultivars (Al-sensitive, Domo.INIA and Al-tolerant, Dalcahue.INIA) and (ii) five exchangeable Al levels (0-2.7 cmol₍₊₎ kg⁻¹) with three replicates. At harvest, plant biomass was sampled and divided into 5 organ categories: ears, grains, blade leaves, stems plus sheath leaves and roots. The element content (N, P, K, Ca and Al) in each organ was measured to quantify element uptake and concentration, nutrient uptake efficiency (UPE) and nutrient utilization efficiency (UTE). Element uptake (N, P, K, Ca, and Al) was negatively affected by the increased soil Al concentration in above-ground and root biomass in both cultivars (R² = 0.61-0.98, p < 0.01), although clear differences were found between cultivars. On the contrary, the impact of soil exchangeable Al on the plant element concentration was minor, showing weak associations with soil Al levels. However, the Al concentration in above-ground tissues of the Al-sensitive cultivar was an exception because it increased exponentially with the Al soil concentration (R² = 0.96-0.99, p < 0.001). Nutrient uptake efficiencies, UPEs (N, P, K and Ca), were negatively affected by soil Al concentrations and were well described by linear equations in both cultivars (R² = 0.58-0.98, p < 0.05), with notable differences between them. Both nutrient uptake (capture) and UPE were the traits that best explained above-ground biomass production (R² = 0.82-0.99, p < 0.001, n = 20). Nutrient utilization efficiency, UTEs (N, P, K and Ca) responded more conservatively to the soil Al concentration, except for the Al sensitive cultivar under very high soil Al levels.     

Heritability of,and genotypic correlations between,aflatoxin traits and physiological traits for drought tolerance under end of season drought in peanut (Arachis hypogaea L.)

More rapid progress in breeding peanut for reduced aflatoxin contamination should be achievable with a better understanding of the inheritance of, aflatoxin trait and physiological traits that are associated with reduced contamination. The objectives of this study were to estimate the heritability of aflatoxin traits and genotypic (r_G) and phenotypic (r_P) correlations between drought resistance traits and aflatoxin traits in peanut. One hundred-forty peanut lines in the F_4:6 and F_4:7 generations were generated from four crosses, and tested under well-watered and terminal drought conditions. Field experiments were conducted under the dry seasons 2006/2007 and 2007/2008. Data were recorded for biomass (BIO), pod yield (PY), drought tolerance traits [harvest index (HI), drought tolerance index (DTI) of BIO and PY, specific leaf area (SLA), and SPAD chlorophyll meter reading (SCMR)], and aflatoxin traits [seed infection and aflatoxin contamination]. Heritabilities of A. flavus infection and aflatoxin contamination in this study were low to moderate. The heritabilities for seed infection and aflatoxin contamination ranged from 0.48 to 0.58 and 0.24 to 0.68, respectively. Significant correlations between aflatoxin traits and DTI (PY), DTI (BIO), HI, biomass and pod yield under terminal drought conditions were found (r_P = −0.25** to 0.32**, r_G = −0.57** to 0.53**). Strong correlations between SLA and SCMR with A. flavus infection and aflatoxin contamination were also found. Positive correlations between SLA at 80, 90, and 100 DAP and aflatoxin traits were significant (r_P = 0.13** to 0.46**, r_G = 0.26** to 0.81**). SCMR was negatively correlated with aflatoxin traits (r_P = −0.10** to −0.40**, r_G = −0.11** to −0.66**). These results indicated that physiological-based selection approaches using SLA and SCMR might be effective for improving aflatoxin resistance in peanut.