Validation of CERES-Rice v3.5 under the climate of Andhra Pradesh state, India

Crop growth simulation models, properly validated against experimental data have the potential for tactical and strategic decision making in agriculture. Such validated models can also take the information generated through site specific experiments and trials to other sites and years. For proper calibration and evaluation of crop simulation models, there is a need for collection of a comprehensive minimum set of data on soil, weather and crop management in all agronomic experiments. Keeping this in view, field experiments were conducted at Rajendranagar (17°19' N, 78°23' E; 542.3 m amsl) during 1994-97 for three popular varieties of rice viz. Sambamasuri, Rajavadlu and Tellahamsa under irrigated conditions and data collected. Genetic coefficients required for running the CERES-Rice v3.5 model were calculated and the performance of the model under the climate of the area was evaluated. The results of the study show that the model simulations of date of flowering for Sambamasuri, Rajavadlu and Tellahamsa were within an average error of 6.2, 5.7 and 6.7 days respectively. Similar errors in predictions of physiological maturity dates were 7.6, 6.7 and 7.2 days. The error in grain yield predictions by the model averaged at 7.9%, 8.3%, and 5.7% respectively for the three crop varieties. These results indicate that the CERES Rice v3.5 model is capable of prediction of grain yield and phenological development of the crop in the climatic conditions of Andhra Pradesh with reasonable accuracy and hence, the model have the potential for its use as a tool in making various strategic and tactical decisions related to agricultural planning in the state.

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Rice phenology and growth simulation using CERES-Rice model under the agro-climate of upper Brahmaputra valley of Assam

MAUSAM ◽

10.54302/mausam.v67i3.1374 ◽

2021 ◽

Vol 67 (3) ◽

pp. 591-598

Author(s):

R. L. DEKA ◽

R. HUSSAIN ◽

K. K. SINGH ◽

A. K. BAXLA ◽

V. U. M. RAO ◽

...

Keyword(s):

Field Experiments ◽

Simulation Models ◽

Rice Cultivar ◽

Climatic Conditions ◽

Strategic Decision ◽

Growth Stages ◽

Growth Simulation ◽

Brahmaputra Valley ◽

Agricultural Planning ◽

Tactical Decisions

Crop growth simulation models, properly validated against experimental data have the potential for facilitating strategic decision making in agriculture. Such validated models can also make use of the information generated for site specific experiments and trials to other sites and for different time durations. For proper calibration and evaluation of crop simulation models, there is a need for collection of a comprehensive minimum set of data on soil, weather and crop management in all agronomic experiments. Keeping this in view, data from seven field experiments conducted at Jorhat (26° 47' N, 94°12' E; 87 m amsl) during 1998-2005 for long duration rice cultivar Ranjit grown under rainfed conditions were collected. Genetic coefficients required for running the CERES-Rice v4.5 model were derived and the performance of the model under the climate of upper Brahmaputra valley was evaluated. These results indicate that the CERES Rice v4.5 model is capable of estimating growth stages and grain yield of rice cultivar Ranjit in the climatic conditions of upper Brahmaputra valley with reasonable accuracy. Hence, the model have the potential for its use as a tool in making various strategic and tactical decisions related to agricultural planning in the state.

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Effect of Temperature on Sowing Dates of Wheat under Arid and Semi-Arid Climatic Regions and Impact Quantification of Climate Change through Mechanistic Modeling with Evidence from Field

Atmosphere ◽

10.3390/atmos12070927 ◽

2021 ◽

Vol 12 (7) ◽

pp. 927

Author(s):

Jamshad Hussain ◽

Tasneem Khaliq ◽

Muhammad Habib ur Rahman ◽

Asmat Ullah ◽

Ishfaq Ahmed ◽

...

Keyword(s):

Climate Change ◽

Grain Yield ◽

Arid Region ◽

Field Experiments ◽

Climatic Conditions ◽

Seasonal Temperature ◽

Sowing Dates ◽

Rcp 8.5 ◽

Semi Arid Region ◽

Semi Arid

Rising temperature from climate change is the most threatening factor worldwide for crop production. Sustainable wheat production is a challenge due to climate change and variability, which is ultimately a serious threat to food security in Pakistan. A series of field experiments were conducted during seasons 2013–2014 and 2014–2015 in the semi-arid (Faisalabad) and arid (Layyah) regions of Punjab-Pakistan. Three spring wheat genotypes were evaluated under eleven sowing dates from 16 October to 16 March, with an interval of 14–16 days in the two regions. Data for the model calibration and evaluation were collected from field experiments following the standard procedures and protocols. The grain yield under future climate scenarios was simulated by using a well-calibrated CERES-wheat model included in DSSAT v4.7. Future (2051–2100) and baseline (1980–2015) climatic data were simulated using 29 global circulation models (GCMs) under representative concentration pathway (RCP) 8.5. These GCMs were distributed among five quadrants of climatic conditions (Hot/Wet, Hot/Dry, Cool/Dry, Cool/Wet, and Middle) by a stretched distribution approach based on temperature and rainfall change. A maximum of ten GCMs predicted the chances of Middle climatic conditions during the second half of the century (2051–2100). The average temperature during the wheat season in a semi-arid region and arid region would increase by 3.52 °C and 3.84 °C, respectively, under Middle climatic conditions using the RCP 8.5 scenario during the second half-century. The simulated grain yield was reduced by 23.5% in the semi-arid region and 35.45% in the arid region under Middle climatic conditions (scenario). Mean seasonal temperature (MST) of sowing dates ranged from 16 to 27.3 °C, while the mean temperature from the heading to maturity (MTHM) stage was varying between 12.9 to 30.4 °C. Coefficients of determination (R2) between wheat morphology parameters and temperature were highly significant, with a range of 0.84–0.96. Impacts of temperature on wheat sown on 15 March were found to be as severe as to exterminate the crop before heading. The spikes and spikelets were not formed under a mean seasonal temperature higher than 25.5 °C. In a nutshell, elevated temperature (3–4 °C) till the end-century can reduce grain yield by about 30% in semi-arid and arid regions of Pakistan. These findings are crucial for growers and especially for policymakers to decide on sustainable wheat production for food security in the region.

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Change in Maize Final Leaf Numbers and Its Effects on Biomass and Grain Yield across China

Agriculture ◽

10.3390/agriculture10090411 ◽

2020 ◽

Vol 10 (9) ◽

pp. 411

Author(s):

Wanmao Liu ◽

Bo Ming ◽

Ruizhi Xie ◽

Guangzhou Liu ◽

Keru Wang ◽

...

Keyword(s):

Grain Yield ◽

Field Experiments ◽

Climatic Factors ◽

Input Parameter ◽

Climatic Conditions ◽

Leaf Number ◽

Maize Crop ◽

Area Index ◽

Distribution Ranges ◽

The Mean

The final leaf number is an important morphological characteristic of maize (Zea mays L.) and is therefore an important input parameter in some maize crop models. In this study, field experiments were conducted from 2013 to 2016 at 23 sites across China, which were located between latitudes of 26°30′ and 46°45′ N, focusing on five modern maize cultivars, in order to determine the amplitude of variation in mean leaf numbers between each cultivar, identify differences between the mean leaf numbers of cultivars under different climatic conditions, and clarify the effects of the differences in final leaf numbers on aboveground dry matter (DM) and grain yield. The results showed that the mean final leaf numbers increased in the order of XY335 < NH101 < ZD909 < ZD958 < DH11 among the five cultivars, with the wide distribution ranges of final leaf numbers being 17.0–23.3 (DH11), 16.7–22.3 (ZD958), 16.7–22.0 (ZD909), 16.7–22.3 (NH101), and 17.0–22.0 (XY335) across all locations. In addition, leaf numbers above and below the primary ear showed the same trends with the mean final leaf numbers for the same cultivars. Many climatic factors were found to significantly affect the final leaf numbers across four maize-growing regions in China, and the result of stepwise regression indicated that the influences of photoperiod and temperature, in particular, were greater than other climatic factors for these cultivars. Finally, there were found to be significant and positive relationships between the final leaf number and (1) the maximum leaf area index (LAImax), (2) DM at both silking and physiological maturity, and (3) grain yield for the same cultivars across all locations. The results of this study are of great importance for guiding future trans-regional maize cultivation and further model calibration.

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Biometric Analyses of Yield, Oil and Protein Contents of Wheat (Triticum aestivum L.) Genotypes in Different Environments

Agronomy ◽

10.3390/agronomy9060270 ◽

2019 ◽

Vol 9 (6) ◽

pp. 270 ◽

Cited By ~ 4

Author(s):

Ankica Kondić-Špika ◽

Novica Mladenov ◽

Nada Grahovac ◽

Miroslav Zorić ◽

Sanja Mikić ◽

...

Keyword(s):

Grain Yield ◽

Protein Content ◽

Oil Content ◽

Significant Positive Correlation ◽

Field Experiments ◽

Triticum Aestivum L ◽

Climatic Conditions ◽

Partial Least Square ◽

Least Square ◽

Partial Least Square Regression

The objectives of this study were to investigate: (1) the effects of genotype, environment, and their interactions on the oil content (OC), protein content (PC) and grain yield (GY) of 25 varieties of winter wheat, (2) the correlations among these traits in different environments, and (3) the effects of different climatic variables and their interactions with wheat genotypes for the examined traits. The field experiments were performed on three experimental sites in Serbia in 2009/10 and 2010/11. The most variable traits were GY and PC, while the variations of OC were lower. A significant positive correlation between wheat bran OC and GY was found in one, while highly significant negative correlations between PC and GY were found in three out of six environments. The partial least square regression (PLSR) triplots for protein content, oil content and grain yield enabled us to identify favorable and limiting climatic conditions for each trait and explained 31.9%, 32.6%, and 30.4% of the total variance, respectively. Cvs. Renesansa and Zvezdana were identified as genotypes with high average values for all traits, while cvs. Bankuty 1205 and Banatka were identified as potential sources of high protein content.

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Agrophysical properties of soil and yield of spring barley for various predecessors and mineral fertilizers in the Central Black Earth Region

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/845/1/012053 ◽

2021 ◽

Vol 845 (1) ◽

pp. 012053

Author(s):

S N Ermolaev ◽

S I Smurov ◽

O V Grigorov ◽

V N Naumkin ◽

L A Naumkina ◽

...

Keyword(s):

Grain Yield ◽

Field Experiments ◽

Elevated Temperatures ◽

Spring Barley ◽

Barley Grain ◽

Climatic Conditions ◽

Mineral Fertilizers ◽

Typical Chernozem ◽

Critical Phases ◽

Aggregate Composition

Abstract The research is devoted to the study of the influence of precursors and mineral fertilizers, applied in various doses, on the agrophysical properties of the soil, the value of the grain yield of spring barley in the soil and climatic conditions of the Central Black Earth region. The field experiment was based on the long-term hospital of Belgorod State Agrarian University named after V. Ya. Gorin. As an object, the variety of spring barley Knyazhich, recommended for the region, was chosen. The soil of the experimental plot is typical chernozem, medium loamy granulometric composition on loess-like loam. The experiment scheme (4×4) provided for the study of four gradations of factor A (predecessors: corn for grain - control, sunflower, sugar beet, soybeans) and factor B (doses of mineral fertilizers: N10P10K10 - control, N30P30K30, N50P50K50, N70P70K70). Growth and development of spring barley plants in 2018-2020 took place in meteorological conditions characterized as arid with a predominance of elevated temperatures and insufficient precipitation during the critical phases of plant vegetation. The results of field experiments established that the water and agrophysical properties (density and structural-aggregate composition) of the soil under the influence of previous crops approached the optimal values and changed insignificantly. Increased doses of mineral fertilizers had a positive effect on the value of the yield of barley grain according to the studied predecessors. The highest grain yield over the years of research was obtained at high N50P50K50 and intensive N70P70K70 backgrounds for the predecessors of soybeans and sugar beets and amounted to 5.48 and 5.03 t/ha and 5.33 and 5.32 t/ha, respectively. This was higher than the control of corn for grain 0.82 and 0.37 t/ha and 0.62 and 0.61 t/ha, while for sunflower it decreased to 4.06 and 4.71 t/ha and was at the level with the control.

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Contribution of phase durations to canola (Brassica napus L.) grain yields in the High Rainfall Zone of southern Australia

Crop and Pasture Science ◽

10.1071/cp15213 ◽

2016 ◽

Vol 67 (4) ◽

pp. 359 ◽

Cited By ~ 6

Author(s):

Penny Riffkin ◽

Brendan Christy ◽

Garry O'Leary ◽

Debra Partington

Keyword(s):

Grain Yield ◽

Environmental Conditions ◽

Field Experiments ◽

Positive Association ◽

Grain Filling ◽

Climatic Conditions ◽

Annual Rainfall ◽

Brassica Napus L ◽

Winter Canola ◽

High Rainfall

In the High Rainfall Zone (HRZ) of southern Australia, long-season winter canola types have been commercially available only since 2011. Experiments in this region show that these varieties can provide improvements in grain yield over spring types of >20% because of their ability to make better use of the longer growing season. However, within this longer crop duration, the optimum length and timings of the critical growth phases to maximise grain production are unknown. Data from eight field experiments conducted between 2010 and 2014 at Hamilton, in the HRZ of south-western Victoria, were analysed to determine whether different phases within the crop’s life cycle vary in their contribution to grain yield and, if so, how this is influenced by climatic conditions. The dataset provided 536 genotype–environment–management combinations including 60 varieties ranging in total crop duration from 186 to 236 days. Over the 5 years, seasons were highly variable with annual rainfall ranging between 479 and 981 mm and spring rainfall (September–November) between 84 and 199 mm. The range of crop maturity types (i.e. winter and spring types) and environmental conditions provided a wide spread in growth, development and grain yield. The analysis showed a positive association between longer duration from flowering to maturity and grain yield, and showed that the duration was influenced by both environmental and genetic factors. Pre-flowering reserves made an important contribution to grain yield, and remobilisation of reserves from the pre-flowering period was greatest for winter types, presumably due to less favourable conditions for growth during grain-filling. Optimising flowering to produce sufficient pre-flowering reserves for remobilisation while ensuring that environmental conditions post-flowering are such that the grain-filling duration is maximised may provide a strategy to increase yields in this environment.

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Calibration, validation and application of AquaCrop model in irrigation scheduling for rice under northwest India

Journal of Applied and Natural Science ◽

10.31018/jans.v7i2.668 ◽

2015 ◽

Vol 7 (2) ◽

pp. 691-699 ◽

Cited By ~ 1

Author(s):

S. S. Sandhu ◽

S. S. Mahal ◽

Prabhjyot Kaur

Keyword(s):

Grain Yield ◽

Field Experiments ◽

Water Productivity ◽

Irrigation Schedule ◽

Research Work ◽

Simulation Models ◽

Irrigation Scheduling ◽

Loamy Sand Soil ◽

Aquacrop Model ◽

Dry Biomass

A lot of research work regarding irrigation scheduling in rice has been carried out at global level with the objective of increasing irrigation water productivity (IWP) and sustaining grain yield. Under natural conditions rain disturb the planned irrigation treatments. One way to overcome this problem is to use rain shelters which is a costly affair, crop growth simulation models offer a good scope to conduct such studies by excluding the effect of rain. Very limited studies are available where FAO’s AquaCrop model has been used to develop irrigation schedule for crops. Therefore, a study was conducted using FAO AquaCrop model to develop irrigation schedule for rice having higher IWP. The model was calibrated and validated using the experimental data of field experiments conducting during 2009 and 2010, respectively. The model underestimated the above ground dry biomass at 30 days after transplanting (DAT) in the range of 21.60 to 24.85 %. At the time of harvest the model overestimated the above ground dry biomass within the range 11.58 to 14.34 %. At harvest the values of normalized root mean square error (15.54%) suggested a good fit for the above ground dry biomass and an excellent agreement (3.34%) between observed and model predicted grain yield. The model suggested to irrigate rice transplanted in puddled loamy sand soil on every 5th day to get higher IWP coupled with statistically similar grain yield as obtained with daily irrigation schedule.

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Genetic Yield Gains and Changes in Morphophysiological-Related Traits of Winter Wheat in Southern Chilean High-Yielding Environments

Frontiers in Plant Science ◽

10.3389/fpls.2021.732988 ◽

2022 ◽

Vol 12 ◽

Author(s):

Alejandro del Pozo ◽

Claudio Jobet ◽

Iván Matus ◽

Ana María Méndez-Espinoza ◽

Miguel Garriga ◽

...

Keyword(s):

Grain Yield ◽

Field Experiments ◽

Vegetation Indices ◽

Grain Filling ◽

Climatic Conditions ◽

Yield Potential ◽

Soil Conditions ◽

Genetic Progress ◽

Potential Yield ◽

Stay Green

Both the temperate-humid zone and the southern part of the Mediterranean climate region of Chile are characterized by high wheat productivity. Study objectives were to analyze the yield potential, yield progress, and genetic progress of the winter bread wheat (Triticum aestivum L.) cultivars and changes in agronomic and morphophysiological traits during the past 60 years. Thus, two field experiments: (a) yield potential and (b) yield genetic progress trials were conducted in high-yielding environments of central-southern Chile during the 2018/2019 and 2019/2020 seasons. In addition, yield progress was analyzed using yield historical data of a high-yielding environment from 1957 to 2017. Potential yield trials showed that, at the most favorable sites, grain yield reached ∼20.46 Mg ha–1. The prolonged growing and grain filling period, mild temperatures in December-January, ample water availability, and favorable soil conditions explain this high-potential yield. Yield progress analysis indicated that average grain yield increased from 2.70 Mg ha–1 in 1959 to 12.90 Mg ha–1 in 2017, with a 128.8 kg ha–1 per-year increase due to favorable soil and climatic conditions. For genetic progress trials, genetic gain in grain yield from 1965 to 2019 was 70.20 kg ha–1 (0.49%) per year, representing around 55% of the yield progress. Results revealed that the genetic gains in grain yield were related to increases in biomass partitioning toward reproductive organs, without significant increases in Shoot DW production. In addition, reducing trends in the NDVI, the fraction of intercepted PAR, the intercepted PAR (form emergence to heading), and the RGB-derived vegetation indices with the year of cultivar release were detected. These decreases could be due to the erectophile leaf habit, which enhanced photosynthetic activity, and thus grain yield increased. Also, senescence of bottom canopy leaves (starting from booting) could be involved by decreasing the ability of spectral and RGB-derived vegetation indices to capture the characteristics of green biomass after the booting stage. Contrary, a positive correlation was detected for intercepted PAR from heading to maturity, which could be due to a stay-green mechanism, supported by the trend of positive correlations of Chlorophyll content with the year of cultivar release.

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Analysis for grain yield and some quality traits in Bulgarian bread wheat (Triticum Aestivum L.)

Agricultural sciences ◽

10.22620/agrisci.2021.29.002 ◽

2021 ◽

Vol 13 (29) ◽

pp. 12-21

Author(s):

Galina Mihova ◽

Keyword(s):

Grain Yield ◽

Field Experiments ◽

Triticum Aestivum L ◽

Kernel Weight ◽

Climatic Conditions ◽

Environment Interaction ◽

Wheat Genotypes ◽

High Productivity ◽

Hybrid Plants ◽

Increased Strength

A major priority of the breeding programs is the development of varieties and hybrid plants combining high productivity and a level of qualitative parameters. Equally topical is the problem of achieving their stable level of expression under uncertain climatic environments. Within three vegetative growth periods (2018, 2019 and 2020) characterized with different levels of abiotic stress, 20 varieties of common winter wheat were investigated. The criteria for setting up of the working collection were the genotypes to be included in the Varietal List of Republic of Bulgaria and to cover the groups’ quality levels. The trials were carried out at two locations: the Institute of Agriculture – Karnobat and Dobrudzha Agricultural Institute – General Toshevo. These regions have specific soil and climatic conditions and are characterized with different risk factors for the development of the cereal crops. The variance analysis showed that the environmental conditions had a significant percent in the total variation of grain yield, the number of productive tillers, 1000 kernel weight and test weight. Concerning these traits, a genotype x environment interaction was also established. The cultivars with high mean yield from the two locations were Rada, Kristalina, Kalina, Katarzhina and Bozhana. The correlation between productivity and quality was successfully broken in Lazarka, Pchelina and Merilin, which belong to the group of strong wheat genotypes. Under the specific technology for conducting the field experiments we used, cultivars Pchelina and Merilin from group A were with expectedly high levels of wet gluten content and W index. The values determined for Lazarka were lower but less variable. In the group of medium wheat genotypes with increased strength, worth mentioning are Enola, Kristalina, Rada and Katarzhina.

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Relationship between Relative Maturity and Grain Yield of Maize (Zea mays L.) Hybrids in Northwest New Mexico for the 2003–2019 Period

Agriculture ◽

10.3390/agriculture10070290 ◽

2020 ◽

Vol 10 (7) ◽

pp. 290

Author(s):

Koffi Djaman ◽

Curtis Owen ◽

Margaret M. West ◽

Samuel Allen ◽

Komlan Koudahe ◽

...

Keyword(s):

New Mexico ◽

Grain Yield ◽

Sprinkler Irrigation ◽

Growing Season ◽

Climatic Conditions ◽

Agricultural Science ◽

Production Optimization ◽

Science Center ◽

Early Season ◽

Climate Conditions

The highly variable weather under changing climate conditions affects the establishment and the cutoff of crop growing season and exposes crops to failure if producers choose non-adapted relative maturity that matches the characteristics of the crop growing season. This study aimed to determine the relationship between maize hybrid relative maturity and the grain yield and determine the relative maturity range that will sustain maize production in northwest New Mexico (NM). Different relative maturity maize hybrids were grown at the Agricultural Science Center at Farmington ((Latitude 36.69° North, Longitude 108.31° West, elevation 1720 m) from 2003 to 2019 under sprinkler irrigation. A total of 343 hybrids were grouped as early and full season hybrids according to their relative maturity that ranged from 93 to 119 and 64 hybrids with unknown relative maturity. The crops were grown under optimal management condition with no stress of any kind. The results showed non-significant increase in grain yield in early season hybrids and non-significant decrease in grain yield with relative maturity in full season hybrids. The relative maturity range of 100–110 obtained reasonable high grain yields and could be considered under the northwestern New Mexico climatic conditions. However, more research should target the evaluation of different planting date coupled with plant population density to determine the planting window for the early season and full season hybrids for the production optimization and sustainability.

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