International Journal of Plant Production
Volume:13 Issue: 4, Dec 2019

Extreme high temperatures may drastically reduce crop yield, especially when occurring during critical growth stages. The risk of future high temperatures may increase under global warming, this raises concerns regarding crop production. China is one of the most important corn production and consumer countries. The main summer corn cultivation region in China was taken as a sample to study the effects of extreme temperature on corn yield at present and in the near future (2021–2050). The determination of extreme high temperature threshold for corn is critical for assessment result. Based on historical observation data, we built a nonlinear regression model between temperature and corn yield, the extreme high temperature threshold of corn was determined as 36.06 °C in the study area. Multi-year average extreme high temperature days of the entire region during 1986–2015 were  5.2 days, the highest values appearing in the Midwestern area. The multi-year average extreme high temperature days increased every additional day could resulted in a 226.62 kg/ha multi-year average corn yield reducing. And over half of the stations, corn yield fluctuations had significant correlations with the number of extreme high temperature days (Nehtd). Nehtd displayed an increasing trend and reached 7.4 days and 11.6 days during 2021–2050 under RCP4.5 and RCP8.5, which could result in corn yield decreased by 9.2% and 27.3%, respectively.

Conventional methods for assessing the impacts of climate change on crop production are often unable to account for the impacts of extreme weather events and therefore underestimate the impacts of climate change. Risk assessment allows for the inclusion of inconsistent impact assessment results in the risk assessment framework and thus provides a qualitative or quantitative assessment of possible risks suffered by crops amid climate change. Due to the subjective assumptions on prior distributions (e.g., emission scenarios and climate model performance) and the assumption that variables are independent of one another, conventional risk assessment methods for crop production amid climate change could produce relatively large errors. In this study, a probability function for future weather scenarios is established based on the principle of maximum entropy using future weather scenario data from the Intergovernmental Panel on Climate Change. In addition, by linking future weather scenarios and winter wheat yields, the risks of winter wheat yield reduction caused by high temperatures as well as the risks of a decrease in rainfall on the North China Plain (NCP) amid climate change are systematically investigated. The results show the following. The risks of winter wheat yield reduction caused by high temperatures will be higher in the north than in the south of the NCP in 2030, 2050 and 2080. In particular, the probabilities of winter wheat yield reduction will be relatively high in central Hebei and northwestern Shandong. In addition, the risks of a decrease in rainfall during the winter wheat season will be higher in the northern NCP than in the southern NCP in 2030, 2050 and 2080. The probabilities of a decrease in rainfall will be relatively high in northern Hebei, Beijing and Tianjin in 2030, and the risks of a decrease in rainfall are gradually increasing. In this study, the principle of maximum entropy is successfully introduced into the field of risk assessments for crop production amid climate change and used to assess the risks to winter wheat production. The method used in this study could enrich the theories and technical methods for assessing crop production risks amid climate change. The results could provide a theoretical basis for developing measures and techniques for adapting winter wheat production to climate change.

Barley cutting in the late winter season is a strategy to provide good amount of high quality forage in the Mediterranean region. A 2-year field study was conducted in Alexandria, Egypt, to explore the variations in forage and grain yields and their characteristics of barley seeded with 100, 125, and 150 kg ha−1 and cut at 45, 55, and 65 days after sowing (DAS). The highest significant forage and grain yields were obtained with highest seeding rate (150 kg ha−1), amounting to 18.91, and 4.38 t ha−1, respectively. Cutting barley at early growth stages (45 and 55 DAS) resulted in the production of higher forage yield with higher quality, in terms of high crude protein and low fiber content, compared to late forage cut at 65 DAS. Meanwhile, early forage cutting resulted in the least amount of reduction in the final grain yield and, thus, grain income. The percentage reduction in grain income associated with forage cutting at 45, 55, and 65 DAS, amounted to 5.7, 19.6, and 31.0%, respectively. However, the net returns obtained from the dual purpose system, when forage was cut at 45 and 55 DAS were $104.27 (11.4%), and $67.91 (7.4%), respectively, greater than that obtained in the grain-only system. Economic analysis showed that the extra income from early forage cutting was sufficient to compensate the grain yield reduction in the dual purpose system. Dual purpose barley production, thus, proved to be highly feasible in the region due to the good price of the barley forage.

Drought stress limits the oilseed crops productivity in semi-arid areas. To alleviate drought stress effects during seed-filling stage, the effect of foliar application of different Zn concentration (0, 0.6 and 1.2 kg ha−1) on five safflower genotypes was investigated in a 2-year (2015–2016 and 2016–2017) field experiments. The results showed that supplemental Zn (1.2 kg ha−1) significantly increased drought resistance by enhancement in proline (20%) and carbohydrate accumulation (4.3%), relative water content (2.4%) and chlorophyll content (3.8%) in all studied safflower genotypes. The induced improve in safflower’s physiological traits achieved in the Zn supplemented treatment resulted in a significant increase in genotypes yield and its components. Moreover, Zn foliar application significantly reduced the drought adverse effect on oil yield and improved the unsaturated fatty acids content. Finally, Zn foliar application can represent an effective means to mitigate the adverse effects of drought stress on growth and the yield of safflower genotypes in water shortage condition.

Peanut is one of the most important oilseed crop grown in China. Purple nutsedge (Cyperus rotundus L.) is a competitive perennial weed, which infests peanut fields in south China and causes considerable peanut yield losses. Information on the interference of purple nutsedge on peanut and its economic threshold (ET) in field is an integral component of integrated weed management system. This will help growers use herbicides more legitimately and reduce the amount of herbicide that is discharged into the environment. 2-year experiments were conducted to assess the infestation effects of purple nutsedge on peanut in pure stands (nutsedge density 0, 5, 10, 20, 40, 80, 120 and 160 plants m−2) and in natural weed infestation, respectively. Furthermore, the ET of purple nutsedge in peanut was determined according the quadratic equation reported by Cousens. The biomass of purple nutsedge with a density of 160 plants m−2 in pure stand was less than that of natural weed infestation treatment. Compared with natural weed infestation treatments, lower yield loss in treatment of nutsedge 160 plants m−2 indicated weaker interference on peanut. But the ET of purple nutsedge in peanut came down to 4–5 plants m−2. The higher price of peanut than the cost of weed control and very high efficiency (90%) of imazapic could be the probable reasons.

Soil salinity and nutrient imbalances are two important limiting factors for plant production in arid and semiarid regions. Quantification of such limiting factors is pivotal for any management in these areas. In this investigation novel deterministic linear and nonlinear models were derived for predicting plant response to interactive effects of salinity and phosphorus through integration of a non-linear salinity model with two basic soil fertility models. To examine and evaluate performances of newly proposed models, several experiments were conducted under separate and combined salinity and phosphorus levels in field conditions. Treatments were consisted of five natural salinity (0.3, 3, 6, 9 and 12 dS m−1) and four phosphorus levels (0, 20, 40 and 80 mg kg−1 soil as KH2PO4), each with three replicates. The obtained results indicated that the proposed nonlinear model (Eq. 7) with R2 of 0.92 provides better estimations than other proposed models for canola yield under different levels of salinity, different levels of soil phosphorus and under combination of different levels of salinity and phosphorus. All proposed models accounting for simultaneous salinity and phosphorus showed that applying 20 and 40 mg P kg−1 soil, or even no use of phosphorus in soil had no significant impact on performance of salinity threshold value, while adding 80 mg P kg−1 soil would lead to increase the salinity threshold value.

In order to contend with decreasing gross amounts and soaring costs, viable rice production in Japan requires high yield levels. This study assessed the effects of nitrogen fertilizer and soil chemical properties on rice yield. Data were recorded in 2014 and 2015 from 93 paddy fields at a farm larger than 30 ha in Hokuriku Region, Japan. Koshihikari, the most widely planted rice variety in Japan, was cultivated in the sampled fields. Soil chemical properties were quantified using 12 variables, namely pH, cation exchange capacity, phosphoric acid content, silicic acid content, content and saturation of the three exchangeable bases, and the equivalent ratios of calcium to magnesium and magnesium to potassium. Three principal components (PCs) were extracted explaining 76% of the total variation and comprised mainly the magnesium (PC1), potassium (PC2), and acidity–basicity (PC3) variables. The multivariate regression model retained significant determinants, with the standardized principal components (SPCs) and the time trend explaining 66.6% of the total variation. The results showed that higher squared values of SPC1 positively related to rice yield, while SPC2 and SPC3 increased rice yield up to a threshold, at which point increases plateaued. These findings were then confirmed through correlation analyses between each soil chemical property and both the PCs and rice yield. The effect of nitrogen fertilizer was insignificant, due to low variation among the paddy fields in which the special cultivation regime was adopted. Further investigations were conducted into countermeasures to improve soil chemical properties, especially those highly related to SPC2 and SPC3.

Crop yields usually respond to crop rotation, but they may interact with tillage system and year (as an integration of variables, mainly in terms of temperature and precipitation). The objective of this study was to evaluate the determinants of the irrigated durum wheat yield under long-term tillage system × crop rotation (2000–2008). Tillage factor considered two levels: moldboard plow plus disk harrow (CT) and no-till (NT) and crop rotations factor had three levels: wheat–fallow–canola (W–F–C), wheat–maize (W–M) and wheat–fallow (W–F). Last year, we evaluate a maize crop as a physical soil quality indicator. The tillage system × crop rotation interaction was not significant, and the lowest durum wheat yield and biomass were observed in the W–M rotation experimental year (reduction of 18.7%). Tillage system × year interaction was significant for wheat yield. Partial least squares analysis indicated that precipitation was high between sowing and 3rd leaf was determinant for yield, and a negative correlation between these variables was observed. Despite the above, no differences were observed in the maize yield directly attributable to physical soil properties. Our study shows that rainfall distribution appears to cause of the tillage system × year interaction for durum wheat yield. When the precipitation was higher (160 mm) between sowing and 3rd leaf, yield decreased in NT by 37% compared to CT possible due to a hypoxia condition and/or low plant-available soil nitrogen, with a negative effect over tillering, affecting in the long-term spike number per square meter.

Crop straw retention to field (CSRF) is a technology to impact the crop yield, soil properties and greenhouse gas (GHG) emission and plays a critical role in sustainable agriculture system. Based on the literatures published, a meta-analysis was performed to evaluate actual impact of CSRF on crop yield, soil properties and GHG emission compared with straw no-retention (NSR). The results indicated that compared with NSR, yield of wheat, maize and rice under CSRF was significantly higher by 4.11, 7.22 and 7.62% respectively; CSRF enhanced the water use efficiency (WUE) and soil organic carbon (SOC) by 14.60 and 7.59%, respectively, reduced the bulk density of 0–20 cm soil layer by 3.06%., while it had no significant effect on the SOC of 20–40 cm; For GHG emissions, the soil emissions of CO2, N2O and CH4 were significantly improved under CSRF by 23.64, 12.21 and 27.34% respectively. Categorically, results on meta-analysis and regression indicated that large variation in crop yield, SOC content and bulk density in 0–20 cm soil layer, WUE and GHG emission under CSRF compared with NSR because of different straw retention mass, retention regions, and crop species. For example, the increased rate of large straw retention mass (LA) on crop yield was the highest. Adoption of CSRF under appropriate site-specific conditions can safeguard China’s food security, alleviate soil-related constraints and slightly increase GHG emissions.

Information is lacking on sulfur (S) nutrition characteristics of contemporary cotton (Gossypium hirsutum L.) cultivars and their responses to S fertilization in the United States. The objective of this study was to develop S fertilizer recommendations and S sufficiency ranges for contemporary cotton cultivars with high yielding potentials. Sixteen field trials were conducted on cotton across west Tennessee during 2014–2016. Five S application rates of 0, 11.2, 22.4, 33.6, 44.8 kg ha−1 were examined in a randomized complete block design with four replicates at each location-year. Lint yield was significantly increased by 8.5–9.8% with S applications of 11.2, 22.4, 33.6, 44.8 kg ha−1 in the soils with low S. Soil residual S level after harvest was significantly enhanced only at the highest rate of 44.8 kg S ha−1. However, lint yield or soil residual S did not respond to S application in the medium S soils. Leaf S concentrations of 3.9–8.2 g kg−1 at late bloom were needed for 95–100% of the highest yield in the low S soils, which were different from the current S sufficiency range of 3.0–9.0 g kg−1 being used in diagnosing cotton S nutrition. In conclusion, application of 11.2 kg S ha−1 is beneficial and adequate for cotton grown on low S soils. The S sufficiency range at late bloom was narrower for contemporary cotton cultivars than conventional cotton varieties. Sulfur management needs to be more accurate for contemporary cotton cultivars due to their narrower S sufficiency range.