International Journal of Plant Production
Volume:14 Issue: 1, Mar 2020

This experiment aimed at evaluating the yield and weed infestation of winter durum wheat grown in a multi-year cereal monoculture (CM) and crop rotation (CR) as well as in three tillage systems: (1) conventional tillage—CT, (2) reduced tillage—RT, and (3) no-tillage—NT. Shallow ploughing and pre-sowing ploughing were performed in the CT system; a cultivator and a cultivating set were used in the RT system, whereas glyphosate and a cultivating set were applied in the NT system. Grain yield was lower in CM than in CR (1.43 t ha−1 vs. 3.91 t ha−1) as well as in NT than in RT and CT systems. Grain yield and its components were determined to a greater extent by cropping systems (CS) than by tillage systems (TS). The number and air-dry weight of weeds per m2 were higher in CM than in CR, and also in RT than in NT and CT, and were found to be more afected by TS than by CS. At the tillering stage of wheat, more weed species occurred in CM than in CR, whereas at the stage of waxy maturity of wheat—in CR than in CM. Likewise, a higher number of weed species was identifed in RT than in CT and NT systems.

Accurate quantification of biological processes (e.g. germination) response to temperature was and still is of particular interest to many disciplines. Our objective was to develop and compare a new function (modified segmented function) with existing non-linear functions in fitting experimental data that cover both sub- and supra-optimum temperature ranges. We utilized diverse experimental and literature data on various crops such as safflower, maize, sorghum to test the functions which were: a modified segmented (derived in this paper), segmented and beta growth function. The datasets covered different plant biological processes, such as seed germination, leaf elongation. The new function fitted various experimental data with a root mean square deviation (RMSD) from 0.011 to 0.082. In 6 out of the 11 datasets, the new function performed better than the beta and segmented function according to various statistics. However, the performance of the segmented and beta function was better that our function in 4 and 1 out of the 11 datasets, respectively. The new function is interesting because all parameters have biological interpretation, it offers advanced flexibility in fitting complex datasets as compared to the two other functions and its response curve parts can be varied from linear to nonlinear based on thermal sensitivity parameter. We concluded that the new function is a good alternative to beta and segmented functions. Lastly our study confirms that there is no best function that can fit different data of temperature response.

The water extracts of allelopathic crops have potential to stimulate the plant growth when applied at low concentration. Most of the previous studies have evaluated the role of exogenous application of allelopathic water extracts at low fertilizer inputs. In this 2-year study, comprised of three independent field experiments, we evaluated the role of exogenous application of allelopathic water extracts of sorghum/sunflower and benzyl aminopurine, applied alone or in combination, in improving the productivity and profitability of bread wheat grown at optimum and high levels of inorganic fertilizers. In first two studies, the sorghum or the sunflower water extracts (5% each) and benzyl aminopurine were applied alone or in combination with benzyl amino purine under optimal (N:P = 125:90 kg ha−1) and high (N:P = 225:150 kg ha−1) fertilizer; no extract application and water spray were taken as control. In the third study, the sorghum water extracts and benzyl aminopurine were used alone or in combination, under optimal (N:P = 125:90 kg ha−1), high (N:P = 225:150 kg ha−1) and very high (N:P = 325:210 kg ha−1) fertilizer keeping water spray as control. The foliage sprays were done at 40 and 75 days after sowing in all experiments. The results indicated that stay green character, grain yield and yield components, and the profitability of wheat were improved with the exogenous application of sorghum/sunflower water extracts and benzyl aminopurine as compared with the control treatments in all experiments. This improvement can be attributed to enhanced physiological functioning and hermetic response of the crop plants to potential allelochemicals present in crop water extracts. The combine application of water extracts and benzyl aminopurine was most useful in terms of yield increment regardless of any fertility status, possibly due to synergistic action of the allelochemicals and the commercial growth regulator. In nutshell, combine use of allelopathic crop water extracts and benzyl aminopurine can be used to improve wheat yield under any fertility status. However, the application of allelopathic crop water extracts and benzyl aminopurine, either alone or in combination was not profitable when applied at high or very high fertilizer level.

The bioeconomic models developed in Weed Science consider the effect of a species on the crop. Bioeconomic models accounting for species interactions within the weed community might represent more realistic approximation to the economic outcome of weed control options in Mediterranean cereal crops. A bioeconomic model, based in community dynamics, competition and economic submodels, was developed and used to investigate the long-term agronomic, economic and environmental consequences of using herbicide-based strategies for the control of winter wild oats (Avena sterilis) and rigid ryegrass (Lolium rigidum) in winter wheat. The results of simulations indicated that different winner strategies can be postulated depending on selection criterion. Based on purely economic outcome, the best strategy was the application of half-dose herbicide to both species whereas if the goal is to achieve a long-term economically viable and environmental friendly decision making, then the strategy chosen would be the one based on a full-dose herbicide application for the control of L. rigidum and half-dose for control of A. sterilis. The sensitivity of the model to variation in economic and competition parameters was checked. The most sensitive model parameters were the potential yield and the wheat price. Bioeconomic models offer practical guidance regarding the possibilities and limitations of various strategic approaches for weed control.

Changes in phenology, growth, biomass production and photosynthetic parameters in Trifolium repens L. were studied under Free Air CO2 Enrichment (FACE; 550 ± 50 µmol mol−1 [CO2]) and Free Air Temperature Increment FATI for 2 years during 2010–11 and 2011–12 in temperate Himalaya. Plant height, root volume, leaf area and dry biomass of T. repens increased from 8.8 to 33.5% under elevated [CO2] but decreased from 4.6 to 58.1% under elevated temperature compared to ambient environment. Leaf area increased by 24.1 and 29.5% under elevated [CO2], however, elevated temperature reduced leaf area by 78.1 and 38.6% compared to ambient conditions during 2010–11 and 2011–12, respectively. Leaf net photosynthetic rates (PN) and stomatal conductance (gS) measured at 390 ± 10 µmol m−2 s−1 CO2, declined under FACE and FATI environment as compared to control conditions, with greater reduction during year 2011–12 than 2010–11. The values of PN in year 2011–2012 during spring and autumn were lower by 13% and 7% under FACE and 24% and 18% under FATI, respectively, compared to ambient (control) conditions, when measured at 400 µmol m−2 s−1. For year 2012, gS showed a decrease by 26% and 39% under FACE and by 21% under FATI during spring and autumn months, respectively, compared to ambient conditions. All phenological stages were significantly advanced under elevated temperature but showed a delayed response under elevated [CO2] as compared to ambient conditions.

Stability of maize (Zea mays L.) hybrids has been major research topics. So far, more emphasis has been placed on the per area grain yield variation, rather than on the plant-to-plant variability within the crop stand, i.e. intra-crop variation. The acquired intra-crop variation of different hybrids was recorded across five environments via the coefficient of variation (CV) of plant-to-plant variability for seven agronomic traits. Hybrids were less variable for plant height (PH) with CVs ranging up to 23%, and most variable for grain yield (GY) with a CV ceiling of 96%. A general negative association of plant-to-plant variability with GY pinpointed hybrids prone to intra-crop variation to be less efficient to capture the available inputs. An adverse affection of intra-crop variation on aboveground biomass (AB) was relatively moderate, while on harvest index (HI) occasional (albeit consistent in one environment). A test established to search whether variance and CV were systematically dependent on mean reflecting a meaningless CV ~ mean negative relationship, was occasionally positive only for AB but not for GY and HI, strengthening thus the value of CV for plant-to-plant variability as a measure of stability. There was also a tendency relationship of AB, GY or HI with interplant variation to follow the exponential than the linear declining pattern, i.e. the Taylor power law (TPL) model. The adverse effect of the interplant variation was more pronounced on GY compared to AB and HI. Consequently, crop stand uniformity seems imperative for optimal use of resources. The findings brought into the forefront the single-plant performance as a crucial breeding goal to moderate the intra-specific competition and acquired interplant variation.

Rapid non-destructive estimation of the plant nitrogen (N) status is needed for the precise management of N in small-scale farms. Our objectives were to describe the responses of the soil–plant analyses development (SPAD) measurements to the plant N status of winter wheat, and to evaluate whether the SPAD index is more precise than SPAD readings in estimating the plant N status. During 2009–2011, a field experiment with winter wheat was conducted in the North China Plain. There were eight N supply levels ranging from 0 to 420 kg N ha−1 to create gradients of leaf greenness. The SPAD readings were measured on the topmost fully expanded leaf; the SPAD index was expressed relative to the SPAD readings of sufficiently fertilized plants. Combing over years, significant quadratic responses of SPAD reading to the plant N concentration (PNC) occurred at each/similar Zadoks growth stage (ZGS) but differed largely from ZGS 39/43 to ZGS 58/59, the r2 varied between 0.88 and 0.97; the SPAD readings exhibited a high logarithmic correlation to plant N accumulation (PNA, r2 = 0.94) irrespective of growth stages. Compared with SPAD readings, the SPAD index showed the same precision in response to PNC and PNA at each growth stage in each year, but presented less precision for the combined datasets across years, indicating that the SPAD index is not a more preferable tool in estimating plant N status. In addition, both the SPAD readings and SPAD index demonstrated poor to moderate responses to basal stem nitrate content (BSNC) with large differences among ZGS 39–59 and between the 2 years, indicating that the SPAD measurements could not be effectively used to estimate the BSNC.Rapid non-destructive estimation of the plant nitrogen (N) status is needed for the precise management of N in small-scale farms. Our objectives were to describe the responses of the soil–plant analyses development (SPAD) measurements to the plant N status of winter wheat, and to evaluate whether the SPAD index is more precise than SPAD readings in estimating the plant N status. During 2009–2011, a field experiment with winter wheat was conducted in the North China Plain. There were eight N supply levels ranging from 0 to 420 kg N ha−1 to create gradients of leaf greenness. The SPAD readings were measured on the topmost fully expanded leaf; the SPAD index was expressed relative to the SPAD readings of sufficiently fertilized plants. Combing over years, significant quadratic responses of SPAD reading to the plant N concentration (PNC) occurred at each/similar Zadoks growth stage (ZGS) but differed largely from ZGS 39/43 to ZGS 58/59, the r2 varied between 0.88 and 0.97; the SPAD readings exhibited a high logarithmic correlation to plant N accumulation (PNA, r2 = 0.94) irrespective of growth stages. Compared with SPAD readings, the SPAD index showed the same precision in response to PNC and PNA at each growth stage in each year, but presented less precision for the combined datasets across years, indicating that the SPAD index is not a more preferable tool in estimating plant N status. In addition, both the SPAD readings and SPAD index demonstrated poor to moderate responses to basal stem nitrate content (BSNC) with large differences among ZGS 39–59 and between the 2 years, indicating that the SPAD measurements could not be effectively used to estimate the BSNC.

Both transplanting and direct-sowing are the dominated methods for establishing winter oilseed rape in China. It is important to understand crop performances and responses to nutrient deficiency between transplanted oilseed rape (TOR) and direct sown oilseed rape (DOR). We estimated the effects of establishment methods (transplanting and direct-sowing) and nutrient deficiency (N, P, and K) on rapeseed yield, yield components, and nutrient uptake from 32 site-years field experiments. We found that DOR plants produced lower seed yield, dry matter, and harvest index than TOR plants. The population density in DOR was higher with poor individual growth as reflected by significantly reduced branches, pods, and seeds pod−1. Thus, DOR plants were more sensitive to nutrient deficiency and would lose more yield under nutrient omission conditions. TOR and DOR yields significantly correlated with all yield components except for 1000-seed weight. Pod number plant−1 showed the strongest direct effect on TOR yield. However, population density and pod number plant−1 exhibited highest direct effect on DOR yield. The uptakes and harvest indexes of N and P were higher for TOR, while the DOR plots received higher K uptake and harvest index of K. DOR was more sensitive to nutrient deficiency and its nutrient management should be paid more attention.

To evaluate the yield potential of 96 ecotypes including 48 proso millet (Panicum miliaceum) and 48 foxtail millet ecotypes (Setaria italica) along with four check cultivars under well-watered and water stress conditions, a field experiment was carried out in the Agricultural Research Institute, Meybod, Yazd, Iran, during 2013–2014 using an incomplete block design with two replications. Based on the grain and forage yield, tolerance (TOL), stress susceptibility index (SSI), mean productivity (MP), harmonic mean (HM), geometric mean productivity (GMP) and stress tolerance index (STI) as drought tolerance indices were calculated and tolerant genotype selection index (TGSI) was conducted along with factor analysis. Among all the ecotypes and according to all indices, ecotypes S100, P10, S52, P97, S108, P20, S55, S104 and S18 were selected as the most drought-tolerant and grain yield potential. In addition, ecotypes P34, S104, P97, S39, S53, P102, P23, P5, S18, S13, S12, P92, and S3 were tolerant ecotypes with high potential forage yield. The results indicated that the ranking by TGSI was almost similar to the results obtained through the factor analysis. In addition, TGSI has had easier calculations than factor analysis and other methods. Therefore, it is suggested to explore the stress tolerant ecotypes in practical plant breeding.

Regulating plant density is an important practice to improve winter wheat productivity under limited irrigation in North China Plain. Field experiments were carried out over two seasons (2014–15 and 2015–16) under three plant densities (Dh: 480–570, Dm: 360–390, Dl: 240–270 104 plants hm−2) and three irrigation levels (W0: no irrigation; W1: irrigated 80.0 mm only at the jointing stage, which also means limited irrigation; W2: irrigated 60.0 mm each at the jointing and the flowering stages). Results showed that higher numbers of spikes and higher yield were obtained at high density than that at low density under limited irrigation. Under the same irrigation, wheat culms at ripening stage and the proportion of main stem spikes increased with plant density increasing, along with the increasing of transportation amount, transportation rate, and contribution rate of pre-anthesis storage material to grain. But accumulation amount and contribution rate of post-anthesis dry matter, which was influenced by irrigation level, showed a declining trend with increasing plant density under W2 and W1. Therefore, (1) under limited water condition, yield loss could be compensated by increasing contribution rate of pre-anthesis storage material to grain with increasing plant density. (2) Meantime, under the same limited water condition, higher plant densities could promote nitrogen accumulation in grain and plant of wheat, which was significantly correlation to wheat yield. (3) Considering water and nitrogen use efficiency, medium plant density (Dm) is recommended in wet years, high plant density (Dh) may be considered to increase wheat yield in dry years.

Despite tropical grasses being the main feed source for major part of ruminant livestock, information about nutritional quality changes under climate changes scenario are still scarce. The novelty of this work was to determine the effects of season and elevated CO2 under field conditions upon biomass production and nutritional value of Brachiaria decumbens during 2 years. The Free-Air Carbon Dioxide Enrichment was established in twelve rings: six of them being the control (current atmosphere) and others six fumigated with pure CO2 to achieve a higher concentration (e[CO2]). In each ring, two 0.25 m2 plots have been established with B. decumbens and after standardization cut, green forage yield was evaluated frequently. Plant samples were collected at 20 cm height and evaluated for determining the biomass production, nutritive value and in vitro enteric methane (CH4) production. Season and year had significant effect (P < 0.01) upon all the studied variables. Biomass production, acid detergent fibre and cellulose contents of samples from e[CO2] were statistically greater (P < 0.05). Carbon, nitrogen and crude protein content were within the normal range and as well as CH4 production were not altered by e[CO2] (P > 0.05). Overall, e[CO2] and rainfall seasons significantly increased forage production, contributing to sequester carbon in plant biomass, but this C4 tropical grass must be grazed at its best protein and fermentable carbohydrate ratio for advantages in the rumen microbial synthesis and lowering CH4 production intensity of the production system.

Maize yield prediction is of extreme importance for both identifying those locations with high potential for this crop and determining the yield gaps of the crop where it is currently produced. The most feasible way to estimate crop yields is with the use of crop simulation models, since well calibrated and evaluated. Even though, these estimations have uncertainties once the crop models are not complete. Recent studies have shown that crop models´ uncertainties can be reduced when several models are used together, in an ensemble. Considering that, this study aimed to calibrate and evaluate three crop simulation models (AEZ-FAO; DSSAT-CERES-Maize and APSIM-Maize) to estimate maize potential and attainable yields and to assess the performance of different ensemble strategies to reduce their uncertainties for maize yield prediction. Weather, soil and maize yield data from 79 experimental sites in Brazil were used for calibrating and evaluating these models. After that, the models showed only a good performance, with mean absolute errors (MAE) between 727 and 1376 kg ha−1, R2 between 0.49 and 0.79, d index between 0.78 and 0.94, and C index from 0.54 to 0.84. When the ensemble was applied, using the combination of two models (DSSAT-CERES-Maize and APSIM-Maize), the results showed a better performance than each single model or even the average of them, with MAE = 799 kg ha−1, R2 = 0.79, d = 0.94 and C = 0.84, allowing us to conclude that the ensemble of simulated maize yields is a good strategy to reduce uncertainties on simulations.

To incorporate canopy vertical structure in a process-based model over a temperate meadow, a multilayered model estimated canopy carbon flux (Fc) and water flux (LE) was applied by comparing with eddy covariance measurements in Inner Mongolia, China. Simulations of diurnal, seasonal CO2 and H2O fluxes and model sensitivity to parameters and variables were analyzed. The results showed that the model underestimated Fc and LE by about 0.6% and 5.0%, respectively. It was able to simulate the diurnal and seasonal variation of Fc and LE and performed well during the day and in the growing season, but poorly at night and early in the growing season. Fc was more sensitive to the leaf nitrogen content distribution coefficient and maximum catalytic activity of Rubisco, whereas LE showed greater sensitivity to the stomatal conductance parameter a1, empirical coefficient of stomatal response to saturated vapor pressure difference Vpds0, and minimum stomatal conductance of CO2gsc0. The response of Fc to environmental factors was ranked as air CO2 concentration (Ca) > air temperature (Ta) > photosynthetically active radiation (PAR) > soil water content (θsm) > vapor pressure deficit (VPD) > wind speed (u0). The response of LE to environmental factors was ranked as Ta > VPD > θsm> PAR> Ca> u0. The response of LE to vegetation characteristic parameters was greater than that of Fc.

Water deficit is the most limiting factor for seed yield of crop species in the arid and semi-arid regions. Due to increasing limitation of fresh water resources and importance of safflower (Carthamus tinctorius L.) as a significant oilseed crop in Iran, it is necessary to evaluate physiological responses of drought tolerance and its association with seed yield of this crop in water stress condition. In this study, 21 safflower genotypes were planted by hand in the field under water stress and non-stress conditions in a randomized complete block design with two replications during 2 years (2016–17). The results indicated that water deficit stress significantly reduced relative water content (RWC), chlorophyll a (Chl-a) and chlorophyll b (Chl-b) concentrations and seed yield, but increased ascorbate peroxidase (APX) and peroxidase (POX) activities and leaf proline concentration. Significant differences were observed among the genotypes for all studied traits except Chl-b concentration. Genotypes were discriminated according to their response to drought using stress tolerance index (STI). Drought tolerant genotypes displayed a higher capability for accumulation of proline in association with maintaining RWC, antioxidant enzymes activity and higher seed yield, compared to the drought sensitive genotypes. Presented results suggested that safflower genotypes with higher levels of antioxidant enzymes activity, RWC and proline accumulation are characterized by a higher STI. Therefore, these physiological traits can be employed as effective criteria for selecting safflower genotypes with more tolerance to water deficit stress.

Critical nitrogen (Nc) dilution curve and its extended N nutrient index (NNI) in previous study was only be applied to wheat for N status diagnosis. This research improved this model and further established the N topdressing model which can be quantify the N topdressing rate when NNI < 1. To facilitate the estimate of the Nc concentration, the determination of basal stem tissue sap nitrate (Nit) concentration as a rapid and operational way was used to characterize N status in this study. The results revealed that N dilution curve in this study specific to winter wheat could be used to establish the N nutrition status. There was significantly positive relationship between the Nit concentration and whole plant N concentration at each growth stage. Moreover, the Nit concentration linearly and positively correlated to the N fertilizer application rate, then deducing the N fertilizer topdressing rate per 100 Nit unit, which finally established the N fertilizer topdressing model: N topdressing rate = (critical Nit − actual Nit) × N topdressing rate per 100 Nit unit. The N dilution curve-based model will offer technical support for managing the precise application of N during the growth period of wheat crops.