Improved simulation of winter wheat yield in North China Plain by using PRYM-Wheat integrated dry matter distribution coefficient

The accurate simulation of regional-scale winter wheat yield is important for national food security and the balance of grain supply and demand in China.Presently,most remote sensing process models use the“biomass×harvest index(HI)”method to simulate regional-scale winter wheat yield.However,spatiotemporal differences in HI contribute to inaccuracies in yield simulation at the regional scale.Time-series dry matter partition coefficients(Fr)can dynamically reflect the dry matter partition of winter wheat.In this study,Fr equations were fitted for each organ of winter wheat using site-scale data.These equations were then coupled into a process-based and remote sensingdriven crop yield model for wheat(PRYM-Wheat)to improve the regional simulation of winter wheat yield over the North China Plain(NCP).The improved PRYM-Wheat model integrated with the fitted Fr equations(PRYM-Wheat-Fr)was validated using data obtained from provincial yearbooks.A 3-year(2000-2002)averaged validation showed that PRYM-Wheat-Fr had a higher coefficient of determination(R^(2)=0.55)and lower root mean square error(RMSE=0.94 t ha^(-1))than PRYM-Wheat with a stable HI(abbreviated as PRYM-Wheat-HI),which had R^(2) and RMSE values of 0.30 and 1.62 t ha^(-1),respectively.The PRYM-Wheat-Fr model also performed better than PRYM-Wheat-HI for simulating yield in verification years(2013-2015).In conclusion,the PRYM-Wheat-Fr model exhibited a better accuracy than the original PRYM-Wheat model,making it a useful tool for the simulation of regional winter wheat yield.

Winter Wheat Yield Estimation Based on Sparrow Search Algorithm Combined with Random Forest:A Case Study in Henan Province,China

Precise and timely prediction of crop yields is crucial for food security and the development of agricultural policies.However,crop yield is influenced by multiple factors within complex growth environments.Previous research has paid relatively little attention to the interference of environmental factors and drought on the growth of winter wheat.Therefore,there is an urgent need for more effective methods to explore the inherent relationship between these factors and crop yield,making precise yield prediction increasingly important.This study was based on four type of indicators including meteorological,crop growth status,environmental,and drought index,from October 2003 to June 2019 in Henan Province as the basic data for predicting winter wheat yield.Using the sparrow search al-gorithm combined with random forest(SSA-RF)under different input indicators,accuracy of winter wheat yield estimation was calcu-lated.The estimation accuracy of SSA-RF was compared with partial least squares regression(PLSR),extreme gradient boosting(XG-Boost),and random forest(RF)models.Finally,the determined optimal yield estimation method was used to predict winter wheat yield in three typical years.Following are the findings:1)the SSA-RF demonstrates superior performance in estimating winter wheat yield compared to other algorithms.The best yield estimation method is achieved by four types indicators’composition with SSA-RF)(R^(2)=0.805,RRMSE=9.9%.2)Crops growth status and environmental indicators play significant roles in wheat yield estimation,accounting for 46%and 22%of the yield importance among all indicators,respectively.3)Selecting indicators from October to April of the follow-ing year yielded the highest accuracy in winter wheat yield estimation,with an R^(2)of 0.826 and an RMSE of 9.0%.Yield estimates can be completed two months before the winter wheat harvest in June.4)The predicted performance will be slightly affected by severe drought.Compared with severe drought year(2011)(R^(2)=0.680)and normal year(2017)(R^(2)=0.790),the SSA-RF model has higher prediction accuracy for wet year(2018)(R^(2)=0.820).This study could provide an innovative approach for remote sensing estimation of winter wheat yield.yield.

Integrating a novel irrigation approximation method with a process-based remote sensing model to estimate multi-years'winter wheat yield over the North China Plain

Accurate estimation of regional winter wheat yields is essential for understanding the food production status and ensuring national food security.However,using the existing remote sensing-based crop yield models to accurately reproduce the inter-annual and spatial variations in winter wheat yields remains challenging due to the limited ability to acquire irrigation information in water-limited regions.Thus,we proposed a new approach to approximating irrigations of winter wheat over the North China Plain(NCP),where irrigation occurs extensively during the winter wheat growing season.This approach used irrigation pattern parameters(IPPs)to define the irrigation frequency and timing.Then,they were incorporated into a newly-developed process-based and remote sensing-driven crop yield model for winter wheat(PRYM–Wheat),to improve the regional estimates of winter wheat over the NCP.The IPPs were determined using statistical yield data of reference years(2010–2015)over the NCP.Our findings showed that PRYM–Wheat with the optimal IPPs could improve the regional estimate of winter wheat yield,with an increase and decrease in the correlation coefficient(R)and root mean square error(RMSE)of 0.15(about 37%)and 0.90 t ha–1(about 41%),respectively.The data in validation years(2001–2009 and 2016–2019)were used to validate PRYM–Wheat.In addition,our findings also showed R(RMSE)of 0.80(0.62 t ha–1)on a site level,0.61(0.91 t ha–1)for Hebei Province on a county level,0.73(0.97 t ha–1)for Henan Province on a county level,and 0.55(0.75 t ha–1)for Shandong Province on a city level.Overall,PRYM–Wheat can offer a stable and robust approach to estimating regional winter wheat yield across multiple years,providing a scientific basis for ensuring regional food security.

Assimilation of temporal-spatial leaf area index into the CERES-Wheat model with ensemble Kalman filter and uncertainty assessment for improving winter wheat yield estimation

To accurately estimate winter wheat yields and analyze the uncertainty in crop model data assimilations, winter wheat yield estimates were obtained by assimilating measured or remotely sensed leaf area index （LAI） values. The performances of the calibrated crop environment resource synthesis for wheat （CERES-Wheat） model for two different assimilation scenarios were compared by employing ensemble Kalman filter （EnKF）-based strategies. The uncertainty factors of the crop model data assimilation was analyzed by considering the observation errors, assimilation stages and temporal-spatial scales. Overalll the results indicated a better yield estimate performance when the EnKF-based strategy was used to comprehen- sively consider several factors in the initial conditions and observations. When using this strategy, an adjusted coefficients of determination （R2） of 0.84, a root mean square error （RMSE） of 323 kg ha-1, and a relative errors （RE） of 4.15% were obtained at the field plot scale and an R2 of 0.81, an RMSE of 362 kg ha-1, and an RE of 4.52% were obtained at the pixel scale of 30 mx30 m. With increasing observation errors, the accuracy of the yield estimates obviously decreased, but an acceptable estimate was observed when the observation errors were within 20%. Winter wheat yield estimates could be improved significantly by assimilating observations from the middle to the end of the crop growing seasons. With decreasing assimilation frequency and pixel resolution, the accuracy of the crop yield estimates decreased; however, the computation time decreased. It is important to consider reasonable temporal-spatial scales and assimilation stages to obtain tradeoffs between accuracy and computation time, especially in operational systems used for regional crop yield estimates.

Integrating remotely sensed water stress factor with a crop growth model for winter wheat yield estimation in the North China Plain during 2008–2018

Accurate estimation of regional-scale crop yield under drought conditions allows farmers and agricultural agencies to make well-informed decisions and guide agronomic management. However, few studies have focused on using the crop model data assimilation(CMDA) method for regional-scale winter wheat yield estimation under drought stress and partial-irrigation conditions. In this study, we developed a CMDA framework to integrate remotely sensed water stress factor(MOD16 ET PET) with the WOFOST model using an ensemble Kalman filter(En KF) for winter wheat yield estimation at the regional scale in the North China Plain(NCP) during 2008–2018. According to our results, integration of MOD16 ET PETwith the WOFOST model produced more accurate estimates of regional winter wheat yield than open-loop simulation. The correlation coefficient of simulated yield with statistical yield increased for each year and error decreased in most years, with r ranging from 0.28 to 0.65 and RMSE ranging from 700.08 to1966.12 kg ha. Yield estimation using the CMDA method was more suitable in drought years(r = 0.47, RMSE = 919.04 kg ha) than in normal years(r = 0.30, RMSE = 1215.51 kg ha). Our approach performed better in yield estimation under drought conditions than the conventional empirical correlation method using vegetation condition index(VCI). This research highlighted the potential of assimilating remotely sensed water stress factor, which can account for irrigation benefit, into crop model for improving the accuracy of winter wheat yield estimation at the regional scale especially under drought conditions, and this approach can be easily adapted to other regions and crops.

Analysis on Relationship between Overcast and Rainy Weather, Drought, Flood and Wheat Yield

[Objective] The research aimed to study influence of meteorological factor in late growth stage of wheat. [Method] Based on precipitation, sunshine and yield per unit of wheat in Anyang City in May of 1979-2008, the positive and negative influences of meteorological condition in late growth stage of wheat (May) on wheat yield in Anyang City were analyzed by using agricultural climatic statistical method. Moreover, the reason and defense measure of green-dry hazard in late growth stage of wheat in the city were studied. [Result] When the sunshine percentage in May > 55%, and rainfall < 45 mm, the wheat yield generally increased. But when it was overcast and rainy, and the sunshine was less, especially monthly rainfall > 80 mm, and monthly sunshine percentage < 55%, the wheat yield generally reduced. The overcast and rainy weather, flood in late growth stage of wheat were easy to cause green-dry yield reduction. The rainless weather even drought weren’t obviously unfavorable for good harvest of wheat. In May, when precipitation was too more, or duration was too long, and the air humidity was too big, the normal water supply and inorganic nutrient transmission were affected. Meanwhile, when the overcast and rainy weather was longer, the sunshine was shorter, and the sunshine intensity weakened in late stage, it wasn’t favorable for accumulation of photosynthetic product, and the normal implementing of grouting process was affected. The measures should be used to prevent and control green-dry yield reduction of wheat, such as discharging water and preventing flood, breeding good seed, scientific planting and reasonable irrigation. [Conclusion] The research provided scientific basis for studying variety improvement, scientific plantation, reasonable irrigation, good quality and high yield of wheat.

Effect of Fertilization on Soil Fertility and Wheat Yield of Dryland in the Loess Plateau

Long-term fertility experiments have become an important tool for investigating the sustainability of cropping systems.Therefore, a long-term (18-year) fertilization experiment was conducted in Changwu County, Shaanxi Province, China,to ascertain the effect of the long-term application of chemical fertilizers and manure on wheat yield and soil fertility in the Loess Plateau, so as to provide a scientific basis for sustainable land management. The experiment consisted of nine fertilizer treatments with three replicates arranged in a completely randomized design: 1) CK (no fertilizer); 2) N (N 120 kg ha-i); 3) P (P 26.2 kg ha-1); 4) NP (N 120, P 26.2 kg ha-1); 5) M (manure 75 t ha-1); 6) NM (N 120 kg ha-1,manure 75 t ha-1); 7) PM (P 26.2 kg ha-1, manure 75 t ha-1); 8) NPM (N 120, P 26.2 kg ha-1, manure 75 t ha-1);and 9) fallow (no fertilizer, no crop). N fertilizer was applied in the form of urea and P was applied as calcium super phosphate. The results showed that precipitation had a large effect on the response of wheat yield to fertilization. Manure (M), NP, PM, NM, and NPM treatments significantly increased (P ＜ 0.05) average yield. In the NP, PM, NM and NPM treatments, the percentage increases in yield due to fertilization were highest in normal years, and lowest in the drought years. Long-term P application enhanced soil available P markedly, and manure applications contributed more to soil fertility than chemical fertilizers alone. Chemical fertilizers applied together with manure distinctly improved soil fertility.The results also showed that the soil nutrient concentration changed mainly in the 0-60 cm layers and fertilization and planting only slightly affected soil nutrients below the 100 cm layers.

Optimization of sowing date and seeding rate for high winter wheat yield based on pre-winter plant development and soil water usage in the Loess Plateau,China

Sowing date and seeding rate are critical for productivity of winter wheat(Triticum aestivum L.).A three-year field experiment was conducted with three sowing dates(20 September(SD1),1 October(SD2),and 10 October(SD3)) and three seeding rates(SR67.5,SR90,and SR112.5) to determine suitable sowing date and seeding rate for high wheat yield.A large seasonal variation in accumulated temperature from sowing to winter dormancy was observed among three growing seasons.Suitable sowing dates for strong seedlings before winter varied with the seasons,that was SD2 in 2012–2013,SD3 in 2013–2014,and SD2 as well as SD1 in 2014–2015.Seasonal variation in precipitation during summer fallow also had substantial effects on soil water storage,and consequently influenced grain yield through soil water consumption from winter dormancy to maturity stages.Lower consumption of soil water from winter dormancy to booting stages could make more water available for productive growth from anthesis to maturity stages,leading to higher grain yield.SD2 combined with SR90 had the lowest soil water consumption from winter dormancy to booting stages in 2012–2013 and 2014–2015; while in 2013–2014,it was close to that with SR67.5 or SR112.5.For productive growth from anthesis to maturity stages,SD2 with SR90 had the highest soil water consumption in all three seasons.The highest water consumption in the productive growth period resulted in the best grain yield in both low and high rainfall years.Ear number largely contributed to the seasonal variation in grain yield,while grain number per ear and 1 000-grain weight also contributed to grain yield,especially when soil water storage was high.Our results indicate that sowing date and seeding rate affect grain yield through seedling development before winter and also affect soil water consumption in different growth periods.By selecting the suitable sowing date(1 October) in combination with the proper seeding rate of 90 kg ha–1,the best yield was achieved.Based on these results,we recommend that the current sowing date be delayed from 22 or 23 September to 1 October.

The impacts of climate change on wheat yield in the Huang-Huai-Hai Plain of China using DSSAT-CERES-Wheat model under different climate scenarios

Climate change has been documented as a major threat to current agricultural strategies.Progress in understanding the impact of climate change on crop yield is essential for agricultural climate adaptation,especially for the Huang-Huai-Hai Plain(3H Plain)of China which is an area known to be vulnerable to global warming.In this study,the impacts of climate change on winter wheat(Triticum aestivum L.)yield between the baseline period(1981–2010)and two Representative Concentration Pathways(RCP8.5 and RCP4.5)were simulated for the short-term(2010–2039),the medium-term(2040–2069)and the long-term(2070–2099)in the 3H Plain,by considering the relative contributions of changes in temperature,solar radiation and precipitation using the DSSAT-CERES-Wheat model.Results indicated that the maximum and minimum temperatures(TMAX and TMIN),solar radiation(SRAD),and precipitation(PREP)during the winter wheat season increased under these two RCPs.Yield analysis found that wheat yield increased with the increase in SRAD,PREP and CO2 concentration,but decreased with an increase in temperature.Increasing precipitation contributes the most to the total impact,increasing wheat yield by 9.53,6.62 and 23.73%for the three terms of future climate under RCP4.5 scenario,and 11.74,16.38 and 27.78%for the three terms of future climate under RCP8.5 scenario.However,as increases in temperature bring higher evapotranspiration,which further aggravated water deficits,the supposed negative effect of increasing thermal resources decreased wheat yield by 1.92,4.08 and 5.24%for the three terms of future climate under RCP4.5 scenario,and 3.64,5.87 and 5.81%for the three terms of future climate under RCP8.5 scenario with clearly larger decreases in RCP8.5.Counterintuitively,the impacts in southern sub-regions were positive,but they were all negative in the remaining sub-regions.Our analysis demonstrated that in the 3H Plain,which is a part of the mid-high latitude region,the effects of increasing thermal resources were counteracted by the aggravated water deficits caused by the increase in temperature.

Study on Rational Irrigation for Wheat Production in Fengqiu Region: Ⅰ. Analysis of the Relation Between Soil Water Supply and Wheat Yield

A 5--year experiment on water balance was conducted in a flat rainfed wheat field with an area of 66 m ×100 m in Fengqiu,Henan Province,China,Results of the experiment showed that the correlation between wheat yield and water consumption was not significant ,but that between wheat yield and the ratio of Water supply to Penman evaporation was significant ,foolowing a parabolic curve.The water consumption process, as well as the growing season of wheat plant,could be diveded inot three peridos.The first(154 days) was vegetative growth period ,during which the water consumption,accounted for 35% of the total;the second (65 days)reproductive growth period ,uring which the water consumption occupied 57%,indicating the importance of water consumption in this period;and the third(5-9 days) maturation period,during,which water supply was not important to yield formation.According to the statistics of meteorological data over the years in this region,the hydrological conditions of the five seasons covered a probability range of 74.8%. the results(3.46-5.63 t ha^-1)indicated taht the productivity of the wheat field under rainfed conditions in this region had a dergee of confidence of 74.8%.

Breaking wheat yield barriers requires integrated efforts in developing countries

Most yield progress obtained through the so called ＂Green Revolution＂, particularly in the irrigated areas of Asia, has reached a limit, and major resistance genes are quickly overcome by the appearance of new strains of disease causing organisms.New plant stresses due to a changing environment are difficult to breed for as quickly as the changes occur.There is consequently a continual need for new research programs and breeding strategies aimed at improving yield potential, abiotic stress tolerance and resistance to new, major pests and diseases.Recent advances in plant breeding encompass novel methods of expanding genetic variability and selecting for recombinants, including the development of synthetic hexaploid, hybrid and transgenic wheats.In addition, the use of molecular approaches such as quantitative trait locus（QTL） and association mapping may increase the possibility of directly selecting positive chromosomal regions linked with natural variation for grain yield and stress resistance.The present article reviews the potential contribution of these new approaches and tools to the improvement of wheat yield in farmer＇s fields, with a special emphasis on the Asian countries, which are major wheat producers, and contain the highest concentration of resource-poor wheat farmers.

Wheat yield scenarios for rainwater harvesting at Northern Sinjar Mountain, Iraq

Iraq is part of West Asia and North Africa (WANA) region. The area is known as dry land, famous with gap of crop yield as a result of the water shortage problem. Six basins with total catchment area of 614.19 km2 at rain-fed of Northern Sinjar District (Iraq) had been chosen to investigate both of the potential of rainwater harvesting (RWH) and three supplemental irrigation (SI) scenarios S1, S2, and S3 (100%, 75%, and 50% of full irrigation requirement) to support the wheat yield (bread and durum) under various rainfall conditions for the study period 1990-2009. The results indicated that, the total volume of harvested runoff can be considered for irrigation practices, that reached up to 42.4, 25.1, 0.6, 10.9 (× 106 m3) during 1995-1996, 1996-1997, 1998-1999, and 2001-2002, respectively. The total irrigated area ranged between 10.9 - 5163.7 and 8.8 - 3595.7 (ha) for bread and durum wheat crop for the four selected seasons respectively. The yield scenarios for supplemental irrigation condition Y1, Y2, and Y3 give 68 - 9712, 94 - 12,999, and 105 - 22,806 Ton for bread wheat, and for durum wheat give 56 - 8035, 87 - 10,906, and 103 - 17,396 Ton.

Alternate row mulching optimizes soil temperature and water conditions and improves wheat yield in dryland farming

Straw mulching allows for effective water storage in dryland wheat production. Finding a suitable straw mulching model that facilitates wheat growth was the objective of this study. A 2-year field experiment was conducted to investigate the effects of two straw mulching patterns （FM, full coverage within all the rows; HM, half coverage within alternate rows） and two mulching rates （4.5 and 9.0 t ha^-1） on soil moisture, soil temperature, grain yield, and water use efficiency （WUE） of winter wheat in northern China, with no mulching （M0） as the control. Results showed that mulching increased the soil water storage in all growth stages under high mulching rates, with a stronger effect in later growth stages. Water storage under the HM model was greater in later stages than under the FM model. Soil water content of HM groups was higher than that of FM groups, especially in surface soil layers. Evapotranspiration decreased in mulched groups and was higher under high mulching rates. Aboveground biomass during each growth stage under the HM model was higher than that under M0 and FM models with the same mulched rate, leading to a relatively higher grain yield under the HM model. Mulching increased WUE, a trend that was more obvious under HM9.0 treatment. Warming effect of soil temperature under the HM pattern persisted longer than under the FM model with the same mulching rates. Accumulated soil temperature under mulched treatments increased, and the period of negative soil temperature decreased by 9-12 days under FM and by 10-20 days under HM. Thus, the HM pattern with 9.0 t ha^-1 mulching rate is beneficial for both soil temperature and water content management and can contribute to high yields and high WUE for wheat production in China.

Analysis on Wheat Yield in China Based on the Prediction of Yield Potential

The maximum yield growth range of wheat yield per unit in China is analyzed from three aspects including photosynthesis production potential of wheat,the changing trend of per unit wheat in the previous years and potential of distribution area agricultural crops.In the paper,the potential of using light,the external potential of historical yield evolution tend and AEZ (agricultural ecological zone) are applied to calculate the per unit yield potential of Chinese wheat.The results assume that the maximum growth range of per unit yield in different stages was different:before 1991,the growth range was 10%;before 1996,the growth range was 9%;before 2000,the growth range was 8%.Any variety of wheat and planting technology higher than the above growth range can only be promoted in restricted area and has the statistical error.The results are of reference significance to Chinese wheat production.

Demonstrating Effect of Rainfall Characteristics on Wheat Yield: Case of Sinana District, South Eastern Ethiopia

Demonstrating Effects of Current and Projected Rainfall Characteristics on Wheat yield has been investigated in Sinana district for the period 1995-2016. Data on rainfall and crop yield for the period 1995-2016 were obtained from National Meteorological Agency and Sinana District Agricultural Offices, respectively. Following data quality checking, rainfall data (current and future), correlation and regression studies were analyzed using Statistical software like Instat V3.36 and SPSS V20. Downscaling the output of CSIRO-Mk3.6.0 GCM model (daily rainfall data) for RCP8.5 emission scenario using a web based software tool (Marksim GCM) for the period 2020-2049 were used to determine seasonal total rainfall and ascertain its impact on yield. This study used mean, coefficient of variation, correlation and regression analysis to ascertain the relation, cause and effect relationship between rainfall characteristics and wheat yields. The results indicated that the mean onset date of the main rainy season (JJAS) for Robe and Sinana station was June 30 and July 3. Furthermore, the results of Pearson Correlation Coefficients indicated that kiremt rainfall total (JJAS) had moderate positive relationship (r = 0.499) with wheat yield in the study area. It was also observed that nearly fifty percent of total variance of crop yield is explained jointly by kiremt rainfall total and rainy day (R2 value was 47.9%). The result of projected wheat yield indicated that there will be a slight decrease in wheat yield (qt/ha) after 2030 years due to the impact of expected weakening of kiremt rainfall total. Taking in to account the above findings, it could be suggested that the farmers’ community will be encouraged encouraged to utilize timely climate information issued from National Meteorological Agency of Ethiopia (NMA) and other centers for farm level decision to enhance their crop production.

Agrometeorological wheat yield prediction in rainfed Potohar region of Pakistan

The reliable early estimates of production had always been the prime concerns of growers on one hand and planners as well as policy makers for import/export on the other hand. This study represents a linear regression model making use of meteorological parameters at critical stages of crop’s life cycle to predict the wheat yield about two months earlier than the harvesting. A statistical based software “Statistical Package for Social Sciences” (SPSS) and MS-excel were employed as working tools. Decadal (ten days) agrometeorological data for Rabi season (for the period 1993-2011) being observed at Regional Agromet Centre, Rawalpindi have been utilized. The parameters studied for correlation were mainly rainfall (amount and days), air temperature (minimum, maximum, mean), heat units (on phenological basis), relative humidity, wind speed, sunshine duration, reference crop evapotran-spiration etc. Finally, minimum temperature, sunshine duration and rainfall amount in January (tillering and stem extension phase) proved to be the reliable predictors for the final yield. The correlation coefficients for these parameters on individual basis resulted within the acceptable range where as in aggregate it remained 0.87, an optimistic value.

Assessment cultivated period and farm yard manure addition on some soil properties, nutrient content and wheat yield under sprinkler irrigation system

This study examined changes in some soil hydrophysical, chemical properties and wheat yield (grain;straw yield, N, P, K, Protein and carbohydrates contents) as trends under two cultivated period 10 and 25 year and Farm Yard manure (FYM) addition under sprinkler irrigation system on a newly reclaimed soils, Nubaria, Beheira Governorate, Egypt. Obtained results noticed that cultivation period has more pronounced effect than FYM addition on soil water content at field capacity, wilting point and available water with increase percent 15.1%, 9.3%;19.0% and 25.7%, 19.5% and 30.0% for FYM and cultivation period comparing with control one. Hydraulic conductivity values were strongly affected by cultivation period and FYM addition and significantly decreased values by about 18.9% and 12.1% in same sequences. Wheat straw content from protein had a superior effect under 25 than 10 years cultivated periods with values 61.9 and 6.7 comparing with control, respectively as affected by FYM addition, while FYM alone improved protein content in straw by about 31.9% comparing with untreated one. Slightly increase in straw protein content was attained relative to the increase of cultivated period by about 7.8%. Nutrients content in grain is more than FYM, where the increase percentage were 5.2%, 13.5%;3.8% and 26.5, 21.3;22.6 comparing cultivated periods 25 with 10 years and FYM addition with control, respectively. FYM individually under two studied cultivated periods is more effective under 10 years (28.0%, 25.2%;15.1%) than the 2nd one (25.1%, 25.2%;15.1%) comparing with untreated FYM plots. While N, P and K content in wheat straw had unclear trend and the increase were 6.8, 23.23;56.5% and 62.9, 6.0;29.8 as a result of FYM addition under 10 and 25 years cultivated periods, respectively. The highest values of protein and carbohydrates content in wheat grains as affected by studied factors were 12.86% and 67.43%) were obtained under cultivated period 25 years after FYM addition. Cultivated periods had a highly significant effect on the field water use efficiency values of grain more than the effect of FYM. The highest values of grain and straw yield were recorded at 10 years cultivated periods + treated FYM (2966.8 kg/fed) and 25 years cultivated periods treated with FYM (3835.6 kg/fed). Cultivated periods increased grain and straw yield of wheat crop by about 57.6% and 8.3%. Whereas, FYM increased grain and straw yield by about 39.8% and 58.8% relative to the control, respectively.