International Journal of Plant Production
Volume:9 Issue: 3, Jul 2015

Biochemical leaf photosynthesis models are evaluated by laboratory results and have been widely used at field scale for quantification of plant production, biochemical cycles and land surface processes. It is a key issue to search for appropriate model structure and parameterization, which determine model uncertainty. A leaf photosynthesis model that couples the Farquhar-von Caemmerer-Berry (FvCB) formulation to four different leaf temperature models is used to investigate the photosynthetic characteristics across a range of temperature gradients using both light (A-Q) and CO2 response curves (A-Ci). We used the Bayesian approach to fit the model to trial data of C3 crop plants (soybean, wheat) in the North China Plain and estimated key photosynthetic parameters, such as the maximum carboxylation rate of Rubisco (Vcmax25), the potential electron transport rate (Jmax25), leaf dark respiration in the light (Rd25), mesophyll conductance (gm25) and the kinetic parameter of Rubisco (Г*25) at a reference temperature of 25 °C. The results showed that 1) the model with moderate complexity showed the best goodness of fit, while conversely the simpler and more complex models were under and over fitting with their corresponding data, respectively; 2) the nonpeaked Arrhenius temperature response, which including both light and CO2 responses data gave the best estimates for the key parameters among the four models; and 3) the temperature gradient used to verify the model has greatly improved the estimation of six key parameters (Jmax25, Vcmax25, Rd25, Г*25, Kc25, g 25) with relatively more narrow confidence intervals (CIs) and showing regular variation on temperature gradient. Overall, this method offers an accurate basis for estimating leaf photosynthesis parameters and may enhance the accuracy of canopy, ecosystem and even global vegetation models.

This paper investigated the response of major food crop yields namely beans,cassava, Irish potatoes, maize and sweet potatoes to ongoing changes in climate inRwanda. The projected daily precipitation and temperature data for the period2000-2050 used in this study were generated by stochastic weather generator(LARS-WG) from daily raw data for the period 1961 -2000. These data werecollected from Rwandan Meteorological Center based in Kigali, while theagricultural records for the period 2000-2010 used to project yields of major foodcrops for 2011-2050 were obtained from the National Institute of Statistics ofRwanda and the Ministry of Agriculture and Animal Resources. A number ofstatistical techniques were applied in projecting the major food crops yields andattempting to quantify their magnitude trends in response to projected precipitationand temperature data. The climate and soil suitability analysis revealed that thecentral plateau and south-west regions of the country will be the most suitableregions for cultivation of major food crops except Irish potatoes which can begrown in the north-western highlands. The central plateau region is the only regionthat is expected to experience an increase in yields for most of the major food cropsunder investigation. The south-west region will have increased beans, cassava andsweet potatoes yields in season A (September-January). The eastern lowlands areexpected to register a decreasing trend in most of crops yields in season A,corresponding to the anticipated decline in mean rainfalls and number of rainydays. The envisaged yields increase in season B (February-June) for beans, maize and Irish potatoes will be in response to a rise in mean rainfall and number of rainydays. Heavy rainfall in the north-western region is likely to have a negative impacton crop yields. The rain might cause waterlogging, flooding events and landslideswhich may damage and destroy the crops.

SALTMED model has been developed to predict yield, soil salinity and water content under saline conditions. A two year field experiment was carried out during 2012-13 to calibrate and validate the model for sorghum. Plants were irrigated with salinity levels of 2, 6, 10 and 14 dS m-1. Results showed that there were significant differences between the observed and simulated sorghum dry matter (SDM) and yield. Absolute mean differences between the observed and simulated SDM values for 2, 6, 10 and 14 dS m-1 were 0.45, 1.53, 0.04 and 1.07 Mgha-1, respectively. Soil water contents (SWC) were overestimated at different soil depths. Mean differences between the simulated and observed SWC at 0.0-0.3, 0.3-0.6, 0.6-0.9 and 0.0-0.9 m soil depths were 0.02, 0.04, 0.02 and 0.03 m3m-3, respectively. As salinity increased the mean differences between the observed and simulated SWC were increased. There were no significant differences between the observed and simulated soil salinities at 0.0-0.3, 0.3-0.6, 0.6-0.9 and 0.0-0.9 m soil depths. The Willmott index of agreement value of the observed and simulated ECe at different soil depth were between 0.92-0.96. It is concluded that following successful calibration, the SALTMED model could predict soil salinity and SWC with reasonably good accuracy at different water salinity levels. Although, SALTMED model reasonably well predicted soil salinity at different soil depth, there was a weak agreement between the observed and simulated soil water content at different soil depths. There was a fair agreement between the observed and simulated dry matter and grain yield at different water salinity levels.

Quantitative information about the response of seedling emergence to temperature for safflower (Carthamus tinctorius L.) is rare. The main objective of the present study was to develop a model for predicting days to emergence for safflower as influenced by the temperature. In this regard, a field experiment with a range of sowing dates and four safflower cultivars were conducted to describe the response of seedling emergence to temperature and determine cardinal temperatures and biological days required for emergence (number of days to emergence under optimum temperatures). The segmented, dent-like and beta functions were used to describe the response of seedling emergence to temperature. Results showed that the segmented function described well the seedling emergence response to temperature with the cardinal temperatures of 3.4, 22 and 35 °C for base, optimum and ceiling temperatures, respectively. The biological days required for seedling emergence was estimated 8.6 days. Based on the findings, a seedling emergence model was conducted which can estimate time to 50% of emergence under variable temperature conditions. Model evaluation by using the some independent data showed that the model predicted time to 50% of emergence accurately (RMSD=1.3 days and R2=0.92).

A large body of research has documented the effect of seed priming on germination, emergence and crop yield. In such research, seed priming has been found to have a positive, negative or no effect. Meta-analysis can help to summarize and interpret a collection of experiments. The aim of this study was to conduct a meta-analysis to synthesize published data from studies addressing the effect of seed priming in Iran. Our results indicated that seed priming profoundly influences germination (rate or percentage), seedling emergence (rate or percentage) and crop yield. Among the studied traits, the crop yield increased the most (+28%), followed by the seedling emergence percentage (+19%), the germination rate (+17%), the seedling emergence rate (+15%) and the germination percentage (+4%). In general, hormonal priming was the best seed priming treatment. This was followed by hydropriming and osmopriming. The best priming durations were 12-24 h for the germination percentage (+14%), longer than 24 h for the germination rate (+16%), shorter than 24 h for the seedling emergence rate (+10 to + 14%) and the percentage (about +11%) and shorter than 12 h for the crop yield (+26%). Seed priming significantly increased in all of the traits of eudicots and monocots, except for the germination percentage in monocots. The differences were significant between the monocot and eudicot species in the germination stage. The differences became insignificant in the seedling emergence and crop yield. Finally, it was concluded that hydropriming is a practical treatment. This is due to its low cost and beneficial effects. We additionally concluded that durations shorter than 12 h are the most effective for this priming.

This research was conducted to study and classify the physico-chemical properties of soil, yield components of wheat and to determine the significance of these parameters on the grain yield formation. In this research, seven statistical methods consisting of simple correlation analysis (SCA), multiple linear regression (MLR), stepwise regression (SR), factor analysis (FA), principal component analysis (PCA), cluster analysis (CA) and path analysis (PA) have been investigated. The physico-chemical properties of soil, different morphological traits and wheat yield have been obtained from a field with 250×300 meter dimension located in Bajgah (with silty clay loam soil) that consisted of 30 samples. Among statistical analysis performed, MLR has provided more acceptable results. In this method, among the examined characteristics, five traits i.e., the number of stems without spikes per plant, biological yield, harvest index, soil soluble potassium and soil available phosphorus, examined 98.3% of the variations of the yield (P<0.05). Lack of soil nitrogen effect on yield is due to drought stress conditions in which the plant growth is less sensitive to nitrogen. Furthermore, the negative effect of phosphorus on the yield of plant may be due to the inverse relationship between the soil phosphorus and micronutrient elements on the plant growth. Generally, among the yield components, biological yield is the most important and effective trait on grain yield, that has presented a significant contribution in different statistical methods. For some of the used statistical methods, the measured traits, like length of spike, the number of spikes per square meter, the number of grains per spike and harvest index showed positive effects on the grain yield and other traits like 1000-grains weight, the weight of grain per spike and the number of tillers without spikes per plant showed negative effects on the grain yield with the highest correlation. Among different soil nutrition, soluble potassium, phosphorus, sulfate and available potassium with positive effects and the clay content with negative effects showed the most correlation with the grain yield.

Despite general effect of salicylic-acid (SA) in improving plant growth and productivity in saline conditions, there have not been unanimity about the best concentration. In this 2-yr field study the effect of different SA concentrations (0, 0.5, 1.0, 1.5 and 2.0 mM) was examined on growth, grain yield and yield components of barley under two non-saline (2 dS m-1) and saline (12 dS m-1) conditions. By using response curves and regression analyses the best concentration was also determined. The results showed that salt stress decreased barley plant height (22.7%), fertile tillers (19.0%), ear length (21.6%), grain number per ear (22.5%), thousand grain weight (19.9%), biological yield (29.6%) and grain yield (37.6%). Since salinity treatment when imposed the tillers were at their rapid growth phase; therefore, fertile tiller number per unit area was found to be the most sensitive trait to salt stress. Nonetheless, SA foliar application in different concentrations could ameliorate some of these negative impacts on growth, yield and yield components. Reduction percentage of grain yield due to salinity was the lowest at 1.5 mM in first and 1.0 mM SA concentration in second year corresponding to 27.3% and 33.8%, respectively; while those were highest at no-SA treatments (42.2% and 43.8% in first and second year, respectively). Modulating role of SA for adverse effect of salinity could be attributed to enhanced grain number. Based on the result of regression analysis, it can be concluded that SA foliar application at 2.0 mM under non-saline and at 1.41 mM under saline conditions could be considered as the best concentrations for improving barley performance.

A strict field experiment with crops sown in crop rotation and monoculture was carried out in the years 1988-2012 at the Experimental Station Uhrusk belonging to the University of Life Sciences in Lublin, south-eastern Poland. The study was aimed at evaluating the structure of weed communities occurring in crop rotation and monoculture of cereals. The highest weed density m-2 was determined in the second (1992-1996) and the third crop rotation (1997-2000), whereas the highest weight of weeds was noted in the third crop rotation. Weed community in cereals sown in crop rotation and monoculture was constituted by species belonging to 6 syntaxonomic classes: Stellarietea mediae, Artemisietea vulgaris, Molinio-Arrhenatheretea, Agropyretea intermedio-repentis, Koelerio glaucaeCorynephoretea canescentis and Bidentetea tripartiti.