Fertilizer nitrogen (N) accounts for the majority of the greenhouse gas (GHG) emissions associated with intensive wheat production, and the form of fertilizer N affects these emissions. Differences in manufacturing emissions (as represented in the current carbon accounting methodologies) tend to favour urea, even when using the best available manufacturing technologies (BAT), whereas differences in fertilizer N efficiency and emissions of ammonia tend to favour ammonium nitrate (AN). To resolve these differences, data from 47 experiments in two large UK studies conducted from 1982 to 1987 and from 2003 to 2005 were reanalysed, showing that on average urea efficiency was 0·9 of AN (although mean ammonia emissions in 10 subsidiary experiments indicated an efficiency difference of 0·2); treating urea with a urease inhibitor (TU; AGROTAIN®, active ingredient N-(n-butyl) thiophosphoric triamide (n-BTPT)) brought its efficiency almost in line with AN; however, a significantly greater mean optimum N amount for TU (+0·1 of AN) was not fully explained. A standard response function relating wheat yield to applied AN was modified for degrees of relative inefficiency, thus enabling yields and GHG intensities (kg CO2e/tonne (t) grain) to be calculated using a PAS2050 compatible model for GHG emissions for any N amount of any N form. With AN manufactured by average European technology (AET), the estimated GHG intensity of wheat producing 8 t/ha was 451 kg/t; whereas with urea or TU made by AET it was 0.87–0.99 or 0.84–0.86 of this respectively. Using BAT for fertilizer manufacture, the grain's GHG intensity with AN and TU was 368 kg/t, but was 1·03–1·17 of this with untreated urea. The range of effects on GHG intensities arose mainly from remaining uncertainties in the inefficiencies of the N forms. Generally, economic margins and GHG intensities were not much affected by adjustments in N use for relative inefficiencies or different prices of urea-based fertilizers compared with AN. Overall, TU appeared to provide the best combination of economic performance and GHG intensity, unless the price for N as TU exceeded that for N as AN.

Nitrogen (N) is an essential element for plants and animals. Due to large inputs of mineral fertilizer, crop yields and livestock production in Europe have increased markedly over the last century, but as a consequence losses of reactive N to air, soil and water have intensified as well. Two different models (CAPRI and MITERRA) were used to quantify the N flows in agriculture in the European Union (EU27), at country-level and for EU27 agriculture as a whole, differentiated into 12 main food categories. The results showed that the N footprint, defined as the total N losses to the environment per unit of product, varies widely between different food categories, with substantially higher values for livestock products and the highest values for beef (c. 500 g N/kg beef), as compared to vegetable products. The lowest N footprint of c. 2 g N/kg product was calculated for sugar beet, fruits and vegetables, and potatoes. The losses of reactive N were dominated by N leaching and run-off, and ammonia volatilization, with 0·83 and 0·88 due to consumption of livestock products. The N investment factors, defined as the quantity of new reactive N required to produce one unit of N in the product varied between 1·2 kg N/kg N in product for pulses to 15–20 kg N for beef.

Combustion of biogas containing hydrogen sulphide (H2S) yields highly corrosive sulphur oxides, thereby limiting the use of biogas for heat and power generation. The current study developed and tested a pilot-scale biogas bio-filter system (BBS) to replace conventional water scrubbing systems at a commercial pig farm in Miaoli County, Taiwan. A 62·8-litre pilot-scale BBS, packed with dried aerial roots from the common tree fern (Sphaeropteris lepifera) and a mixture of dried aerial roots and plastic rings as bio-carriers and inoculated with sulphur oxidizing bacteria, was installed at a commercial pig farm. H2S concentration was 5600 mg/m3 and the biogas flow rate was 4 litres/min. The pilot-scale BBS could remove 26·9 g H2S/m3/h using a bio-filter that operated at a 7% (v/v) O2 level continuously for >200 days. It was found that most H2S was oxidized to elemental sulphur (S0) and accumulated on the surface of the dried aerial roots (0·084 g S0/g aerial root) in the BBS. The dried aerial roots and plastic Raschig ring mixture was more efficent at sulphur dioxide removal than the dried aerial roots on their own. The pH and sulphate (SO42−) concentrations of water dropping from the BBS were 1·6 ± 1·0 and 28 680 ± 8253 mg/l, respectively. However, sulphur is the dominant product of sulphur oxidizers at the 7% O2 level. Periodical flushing of the bio-filter with the effluent from the wastewater treatment system on the farm can maintain high efficiency of H2S removal.

Incorporation of rice straw into soil has traditionally been an important method of recycling nutrients and improving soil productivity. Currently, although the effects of straw incorporation on disease severity have been documented, the dynamics of the pathogen in soil after straw incorporation are poorly understood. In the present study, rice straw with various proportions of diseased straw was incorporated at three separate locations (SuPu town, SuSong County and FengYang County) in Anhui province, China. The pathogen dynamics in paddy soil and disease severity of sheath blight during two continuous years from April 2010 to April 2012 were investigated. For all three locations, the amount of pathogen inoculum that persisted in the soil increased with increases in the proportion of diseased straw incorporated. Incorporation of 0·3 and 0·5 diseased straw into soil increased the amount of pathogen inoculum in the soil significantly, whereas incorporation of 0·1 diseased straw into soil had no significant effect on the pathogen inoculum compared with the control (no straw incorporated) or disease severity. Incorporation of healthy rice straw (no disease) resulted in a significant decrease in disease severity, whereas proportions of 0·3 and 0·5 diseased straw resulted in a significant increase of disease severity compared with the control. These results suggested that incorporation of diseased straw enhanced pathogen numbers in soil during the whole decomposition period and increased disease severity. To avoid soil-borne disease accumulation, severely diseased straw should be removed from the field or pre-treated before incorporation.

Stripe rust, caused by Puccinia striiformis f. sp. tritici (Pst), is a major wheat disease that can inflict yield losses of up to 70% on susceptible varieties under favourable environmental conditions. The timely identification of plant genetic resources likely to possess novel resistance to this disease would facilitate the rapid development of resistant wheat varieties. The focused identification of germplasm strategy (FIGS) approach was used to predict stripe rust resistance in a collection of wheat landraces conserved at ICARDA genebank. Long-term climate data for the collection sites, from which these accessions originated and stripe rust evaluation scores for one group of accessions were presented to three different non-linear models to explore the trait×collection site environment interactions. Patterns in the data detected by the models were used to predict stripe rust resistance in a second and different set of accessions. The results of the prediction were then tested against actual evaluation scores of the disease in the field. The study mimics the real scenario where requests are made to plant genetic resources curators to provide accessions that are likely to possess variation for specific traits such as disease resistance.

The models used were able to identify stripe rust-resistant accessions with a high degree of accuracy. Values as high as 0·75 for area under the curve and 0·45 for Kappa statistics, which quantify the agreement between the models’ predictions and the curator's disease scores, were achieved. This demonstrates a strong environmental component in the geographic distribution of resistance genes and therefore supports the theoretical basis for FIGS. It is argued that FIGS will improve the rate of gene discovery and efficiency of mining genetic resource collections for adaptive traits by reducing the number of accessions that are normally required for evaluation to identify such variation.

The agricultural land classification (ALC) of England and Wales is a formal method of assessing the quality of agricultural land and guiding future land use. It assesses several soil, site and climate criteria and classifies land according to whichever is the most limiting. A common approach is required for calculating the necessary agroclimatic parameters over time in order to determine the effects of changes in the climate on land grading. In the present paper, climatic parameters required by the ALC classification have been re-calculated from a range of primary climate data, available from the Meteorological Office's UKCP09 historical dataset, provided as 5 km rasters for every month from 1914 to 2000. Thirty-year averages of the various agroclimatic properties were created for 1921–50, 1931–60, 1941–70, 1951–80, 1961–90 and 1971–2000. Soil records from the National Soil Inventory on a 5 km grid across England and Wales were used to determine the required soil and site parameters for determining ALC grade. Over the 80-year period it was shown that the overall climate was coolest during 1951–80. However, the area of land estimated in retrospect as ‘best and most versatile (BMV) land’ (Grades 1, 2 and 3a) probably peaked in the 1951–80 period as the cooler climate resulted in fewer droughty soils, more than offsetting the land which was downgraded by the climate being too cold. Overall there has been little change in the proportions of ALC grades among the six periods once all 10 factors (climate, gradient, flooding, texture, depth, stoniness, chemical, soil wetness, droughtiness and erosion) are taken into account. This is because it is rare for changes in climate variables all to point in the same direction in terms of ALC. Thus, a reduction in rainfall could result in higher grades in wetter areas but lead to lower classification in drier areas.

The water driven crop growth model AquaCrop was evaluated for predicting the yield of kharif maize (i.e. maize sown in the monsoon season) under future water availability scenarios. Future climatic data were generated using the climate data generator ClimGen, which was parameterized using 37 years (1972–2008) of historical data relating to the study area. The climatic data generated were used first in the CROPWAT model to estimate the irrigation schedule, which was then used in the validated AquaCrop model to predict grain yield for future years. Rainfall estimates generated by ClimGen for 2012 (739 mm) and 2014 (625 mm) resulted in yields of 1600 and 5670 kg/ha, respectively, under rainfed situation during these 2 years with full fertilization levels. This variation may be attributed to the depths of rainfall events and their distribution during the entire growing season in general and sensitive growth stages in particular pertaining to the same sowing date (22 July) in both years. Nonetheless, the use of ClimGen, CROPWAT and AquaCrop models can be standardized as a model-linking protocol to estimate future maize yield and irrigation water requirements for sustainable production and as an adaptation measure to climate change.

The benefits of using white clover (Trifolium repens L.) as a source of nitrogen (N) and nutritious feed in pasture grazed by ruminant livestock have been widely recognized. However, clover is considered inadequate and unreliable as the main source of N input, since its abundance in pasture is patchy, low (typically <0·20) and shows great year-to-year variation. This is thought to be due to the metabolic costs of N fixation, competition with grass, the preference for clover by grazing animals and patchy dung and urine deposition. One solution suggested by a number of authors is to increase the heterogeneity within the pasture by spatially separating clover from grass. This method of pasture management, in order to sustain higher clover content in both the sward and diet of grazing animals, would remove inter-specific competition and equalize grazing pressure, allowing clover to grow unimpeded in greater abundance than previously observed. An existing spatially explicit grass–clover simulation model, developed to investigate the intrinsic spatial and temporal variability within mixed grass–clover swards, was modified and then used to examine the impact of spatial separation on the content, variability and patchiness of clover in pasture. The results show that spatial separation increases both the content and spatial aggregation of clover and reduces year-to-year variation compared with a mixed pasture that fluctuates around a lower mean. The same model was also used to examine the impact of spatial separation across a range of spatial scales, from narrow strips to complete separation, as a means of managing the concerns over disruption to the N cycle within the pasture. The present study shows the importance of the initial sowing arrangement of plant species in sustaining a high content of clover within a pasture in the short term, to at least 20 years depending on the scale of separation, and demonstrates that the spatial separation of clover from grass within a grazed pasture may overcome some of the limitations associated with the use of clover in conventional grass–clover pastures. Results are discussed in terms of benefits to both herbage dry matter production and animal performance.

Identification of climate-smart nutrient management practices will overcome the ill effects of extreme climate variability on agricultural production under projected climate change scenarios. The rice–wheat cropping system is the major system used in India: using long-term yield data from Integrated Nutrient Management experiments on this system, the present study analysed trends in weather parameters and grain yield under different nutrient management practices. Twelve treatments with different combinations of inorganic (chemical fertilizer) and organic (farmyard manure (FYM), green manure (GM) and crop residue) sources of nutrients were compared with farmers’ conventional practices. A significant increasing trend was noticed for rainfall during the rice season at Kalyani and Navsari, of the order of 137·7 and 154·2 mm/decade, respectively. The highest increase in maximum temperature was seen at Palampur (1·62 °C/decade) followed by Ludhiana (1·14 °C/decade). At all the sites except Ludhiana and Kanpur, the yield of the rice–wheat system showed an increasing trend ranging from 0·08 t/ha/year in Jabalpur to 0·011 t/ha/year in Navsari, under the recommended dose of inorganic fertilizer application. A significant decreasing trend of 0·055 t/ha was found in Ludhiana. For most of the sites, a combination of half the recommended dose of inorganic fertilizer and either FYM or GM to provide the remainder of the N required was sufficient to maintain productivity. The top three climate-resilient integrated nutrient management practices were identified for all the study sites. Thus, the present study highlights the adaptive capacity of different integrated nutrient management practices to rainfall and temperature extremes under rice–wheat cropping system in distinctive agro-ecological zones of India.

Data sets were accumulated of annual average maximum, minimum and mean air temperature from a range of sites worldwide, specifically from non-urban locations such as agricultural research institutes, universities and other rural or island locations for the period 1975–2011 or longer where data were available. The data sets were then analysed using linear regression to determine the rate and direction of change in temperature over the reference periods. This analysis was performed to provide vegetable scientists with likely future temperature change scenarios up to 2025 and 2050 (on the assumption that recent trends are maintained) so that breeding, agronomic and other related research programmes may better respond to potential challenges from abiotic and biotic stresses to vegetable production. Substantial variation was evident between sites and between time runs at specific sites. At some locations rapid increases in air temperature are projected, such as for sites in East Asia, but at other locations little change is evident; in rare cases, local cooling is shown. The implications of variability and change in air temperature in the context of constraints to vegetable production and the opportunities to exploit the range of genetic diversity available in climatically uncertain environments are discussed. It is believed that modern agricultural science can address successfully the problems raised by climate uncertainty, yet the lack of sufficient, immediate investment in horticultural disciplines worldwide places the world at severe risk of failing to attain effective food and nutritional security.

Annual medics and clovers have distinct properties in terms of usage as cover crops in Mediterranean orchards, but little is known of their capacity to adapt to the level of shading encountered on an orchard floor. A 2-year field experiment was conducted in South–Eastern Sicily to investigate the effects of withholding 0·50 of sunlight on the phenology and growth pattern of four medic and five clover accessions, focusing on traits known to be important for cover cropping. Shading delayed both seedling emergence and the onset of flowering (by up to 5 and 9 days, respectively), while it extended both the growth period and the overall life-cycle duration (by up to 5 and 11 days, respectively). It also induced an increase in cover crop height (from 34 to 38 cm) and crop light use (from 0·60 to 0·94 g DW/m2/MJ), but a reduction in soil coverage, above-ground dry biomass, maximum growth rate and maximum relative growth rate (by up to 13, 18, 21 and 7%, respectively), so compromising the competitiveness of cover crops against weeds. The responses to shading varied between genotypes. Medicago polymorpha ecotype S. Rosalia, Medicago rugosa ecotype Piano Lauro and ecotype Zappulla were the strongest competitors against weeds, whereas Trifolium tomentosum ecotype Bucampello was interesting in terms of its biomass yield and crop light use. The performance was unstable over seasons, so any future attempt to improve the species’ performances under shade by breeding will need to focus on reseeding capacity.

The present paper studied the performance of the stable isotope signatures of carbon (δ13C), nitrogen (δ15N) and oxygen (δ18O) in plants when used to assess early vigour and grain yield (GY) in durum wheat growing under mild and moderate Mediterranean stress conditions. A collection of 114 recombinant inbred lines was grown under rainfed (RF) and supplementary irrigation (IR) conditions. Broad sense heritabilities (H2) for GY and harvest index (HI) were higher under RF conditions than under IR. Broad sense heritabilities for δ13C were always above 0·60, regardless of the plant part studied, with similar values for IR and RF trials. Some of the largest genetic correlations with GY were those shown by the δ13C content of the flag leaf blade and mature grains. Under both water treatments, mature grains showed the highest negative correlations between δ13C and GY across genotypes. Flag leaf δ13C was negatively correlated with GY only under RF conditions. The δ13C in seedlings was negatively correlated, under IR conditions only, with GY but also with early vigour. The sources of variation in early vigour were studied by stepwise analysis using the stable isotope signatures measured in seedlings. The δ13C was able to explain almost 0·20 of this variation under RF, but up to 0·30 under IR. In addition, nitrogen concentration in seedlings accounted for another 0·05 of variation, increasing the amount explained to 0·35. The sources of variation in GY were also studied through stable isotope signatures and biomass of different plant parts: δ13C was always the first parameter to appear in the models for both water conditions, explaining c. 0·20 of the variation. The second parameter (δ15N or N concentration of grain, or biomass at maturity) depended on the water conditions and the plant tissue being analysed. Oxygen isotope composition (δ18O) was only able to explain a small amount of the variation in GY. In this regard, despite the known and previously described value of δ13C as a tool in breeding, δ15N is confirmed as an additional tool in the present study. Oxygen isotope composition does not seem to offer any potential, at least under the conditions of the present study.

The nitrogen (N) cycle is one of the best studied elemental cycles. However, the N flows and transformations, in particular in aggregated soils, at small scales and in plant–soil systems are not yet fully understood. Analytical and molecular techniques are now available to address N dynamics at small scales. The methodological advances should go hand in hand with the development of suitable mathematical models addressing the small scale and the full complexity of the many interacting effects. The importance of denitrification within the N cycle is highlighted and used as an example of the progress achieved in recent times. Research gaps and possible research pathways are outlined.

Cultivated lentil (Lens culinaris L.) landraces offer a challenge to exploiting their genetic variability and deriving new pure-line varieties. For insect-transmitted viruses, low densities favour increased virus spread. The objective of the present work was to evaluate a selection procedure applied within a landrace under ultra-low plant density and low-input conditions toward the isolation of high-performing genotypes that escape virus infection. Field trials were conducted through four growing seasons (2006–2011) in the Democritus University of Thrace research farm in Orestiada, Greece. Selection of individual plants for high grain yield was applied for three generations, while virus presence was tested by enzyme-linked immunosorbent assay in the seeds used or the plants selected in each selection cycle. Early high plant-to-plant phenotypic variability, reflected by high coefficient of variation (CV) values, was partly attributed to virus infection. However, sister lines were consistently higher yielding and of lower CV than the mother population (MP). Second generation lines yielded up to 136 and 23% more than the source landrace at the ultra-low density and dense stand, respectively. Pea seed-borne mosaic virus was detected in the seeds of the MP, whereas bean yellow mosaic virus and bean leafroll virus were mainly involved in the subsequent selection rounds. In general, the highest-yielding plants were free of the viruses detected during experimentation. It was concluded that selection at ultra-low density of the highest-yielding plants from the sister lines with the lowest CV constitute an effective way to improve the health status of the seeds produced and result in high yielding and potentially virus-tolerant pure-line varieties.

The present study investigated the historical occurrence of the European corn borer (Ostrinia nubilalis), the European grape vine moth (Lobesia botrana) and the Codling moth (Cydia pomonella) in southern Moravia and northern Austria from 1803–2008 by using climate and pest models. The pest model used, CLIMEX, indicates areas that are climatically favourable for the pest's development and long-term survival, considering the climatic parameters, especially daily air temperature, as determining factors for pest development. For model input parameters, two sets of meteorological data were prepared: (i) a generated meteorological series for 1803–2008 and (ii) a measured reference meteorological series for 1976–2008. In addition to estimating the historical climatic suitability for the persistence of a given pest, a second aim of the present study was to specify the core of the climatic niche during the continued presence of the pest and evaluate the applicability of the meteorological data generated for climate, based on pest mapping. This evaluation resulted in a partial overestimation of pest occurrence for L. botrana when using the generated meteorological data set. This species, native to warmer areas, has proved to be a sensitive indicator of increased temperatures.

The present study found that a protein lysis buffer, used for the extraction of proteins from cells, showed efficacy in reducing the disease severity of cucumber anthracnose, which is caused by the anthracnose fungus. The lysis buffer and its individual components were examined for their function in reducing disease development of cucumber anthracnose on cucumber plants. Nonidet P-40, a nonionic detergent commonly used to isolate cell membrane complexes, was the most effective component of the lysis buffer for disease control. The treatment of cucumber plants with Nonidet P-40 at a concentration of 50 μl/l suppressed development of cucumber anthracnose, but it did not inhibit spore germination of the fungus. Cucumber plants were inoculated with the pathogen 30 min after treatment with Nonidet P-40, and a reduction in disease severity was observed. Expression of genes related to disease resistance (acidic class III chitinase, phenylalanine ammonialyase 1, peroxidase and pathogenesis-related protein 1-1a) were also examined after plants were treated with Nonidet P-40 and inoculated with the pathogen. The results indicate that Nonidet P-40 functions as a trigger for a stereotypic defence response in cucumber plants, including an increase in the expression levels of genes related to disease resistance.

The need for nitrogen (N) efficiency measures for dairy systems is as great as ever if we are to meet the challenge of increasing global production of animal-based protein while reducing N losses to the environment. The present paper provides an overview of current N efficiency and mitigation options for pastoral dairy farm systems and assesses the impact of integrating a range of these options on reactive N loss to the environment from dairy farms located in five regions of New Zealand with contrasting soil, climate and farm management attributes. Specific options evaluated were: (i) eliminating winter applications of fertilizer N, (ii) optimal reuse of farm dairy effluent, (iii) improving animal performance through better feeding and using cows with higher genetic merit, (iv) lowering dietary N concentration, (v) applying the nitrification inhibitor dicyandiamide (DCD) and (vi) restricting the duration of pasture grazing during autumn and winter. The Overseer® Nutrient Budgeting model was used to estimate N losses from representative farms that were characterized based on information obtained from detailed farmer surveys conducted in 2001 and 2009. The analysis suggests that (i) milk production increases of 7–30% were associated with increased N leaching and nitrous oxide (N2O) emission losses of 3–30 and 0–25%, respectively; and (ii) integrating a range of strategic and tactical management and mitigation options could offset these increased N losses. The modelling analysis also suggested that the restricted autumn and winter grazing strategy resulted in some degree of pollution swapping, with reductions in N leaching loss being associated with increases in N loss via ammonia volatilization and N2O emissions from effluents captured and stored in the confinement systems. Future research efforts need to include farm systems level experimentation to validate and assess the impacts of region-specific dairy systems redesign on productivity, profit, environmental losses, practical feasibility and un-intended consequences.

Ethiopia is one of the countries most vulnerable to the impacts of climate variability and change on agriculture. The present study aims to understand and characterize agro-climatic variability and changes and associated risks with respect to implications for rainfed crop production in the Central Rift Valley (CRV). Temporal variability and extreme values of selected rainfall and temperature indices were analysed and trends were evaluated using Sen's slope estimator and Mann–Kendall trend test methods. Projected future changes in rainfall and temperature for the 2080s relative to the 1971–90 baseline period were determined based on four General Circulation Models (GCMs) and two emission scenarios (SRES, A2 and B1). The analysis for current climate showed that in the short rainy season (March–May), total mean rainfall varies spatially from 178 to 358 mm with a coefficient of variation (CV) of 32–50%. In the main (long) rainy season (June–September), total mean rainfall ranges between 420 and 680 mm with a CV of 15–40%. During the period 1977–2007, total rainfall decreased but not significantly. Also, there was a decrease in the number of rainy days associated with an increase (statistically not significant) in the intensity per rainfall event for the main rainy season, which can have implications for soil and nutrient losses through erosion and run-off. The reduced number of rainy days increased the length of intermediate dry spells by 0·8 days per decade, leading to crop moisture stress during the growing season. There was also a large inter-annual variability in the length of growing season, ranging from 76 to 239 days. The mean annual temperature exhibited a significant warming trend of 0·12–0·54 °C per decade. Projections from GCMs suggest that future annual rainfall will change by +10 to −40% by 2080. Rainfall will increase during November–December (outside the growing season), but will decline during the growing seasons. Also, the length of the growing season is expected to be reduced by 12–35%. The annual mean temperature is expected to increase in the range of 1·4–4·1 °C by 2080. The past and future climate trends, especially in terms of rainfall and its variability, pose major risks to rainfed agriculture. Specific adaptation strategies are needed for the CRV to cope with the risks, sustain farming and improve food security.

A field experiment was conducted to investigate the effects of powdery mildew (Blumeria graminis f. sp. Tritici, Bgt) on wheat grain at varying levels of disease severity and at different growth stages. Methods used to determine these effects included Kjeldahl determination, unidimensional polyacrylamide gel electrophoresis, dielectrophoresis combined with mass spectrometric analysis. The specific influences explored were those on prolamins and protein composition at the molecular level. Concentrations of both grain protein and prolamin in wheat increased as disease indices (DIs) of powdery mildew rose from 20 days after anthesis (DAA) to maturity. Globulin concentrations changed dynamically and significantly, especially at 25 DAA when DI was the highest. This was verified by proteomic analysis which showed globulins (such as globulin 3, globulin 3B, globulin 3C, gliadin/avenin-like protein and triticin) being up-regulated significantly under powdery mildew stress. It was proposed that powdery mildew might indirectly affect protein accumulation in grain by influencing the regulative enzymes (including peptidylprolyl isomerase, cyclophilin A-2 and GTPase ObgE) and metabolic processes. It was speculated that the indirect increase caused by yield reduction was not the only factor causing the increase in prolamin concentration. Another factor may be the rise of expression level of molecular chaperones and enzymes relating to protein synthesis, which led to the rise in protein synthesis.