scholarly journals Evaluating InfoCrop model for growth, development and yield of spring wheat at farmers' field in semi-arid environment

2021 ◽  
Vol 21 (3) ◽  
pp. 254-261 ◽  
Author(s):  
RAJKUMAR DHAKAR ◽  
VINAY KUMAR SEHGAL ◽  
DEBASISH CHAKRABORTY ◽  
JOYDEEP MUKHERJEE ◽  
S. NARESH KUMAR
Keyword(s):  
Management Practices ◽  
Sowing Date ◽  
Arid Environment ◽  
Application Rate ◽  
Wheat Crop ◽  
Area Index ◽  
Large Variability ◽  
Acceptable Error ◽  
Agricultural Applications ◽  
Growth Development

Evaluation of crop simulation model for growth and development of crops at farmers' eld is uncommon, as large variability exists in management practices at farmers' elds. Present study was attempted to evaluate the suitability of InfoCrop v2.1 model for prediction of growth, development and yield of wheat crop at farmers' elds using two years data i.e. 2015-16 & 2016-17. A total of 42 farmers'elds were selected in Pataudi block of Haryana state. The large variability in wheat sowing date (1-Nov to 25-Dec), seed rate (87 to 150 kgha-1), N application rate (70 to 195 kgha-1) and number of irrigations (5-8) were observed in farmers' eld. InfoCrop model could able to predict well days to anthesis and physiological maturity within an acceptable error of 5% (RMSE~3 days). Measured leaf area index (LAI) matched well with simulated LAI (RMSE ~ 0.5). The agreement between observed and model simulated wheat grain yield was found to be satisfactory (nRMSE ~ 6-8%). We conclude that InfoCrop-wheat model satisfactorily simulate the growth, development and yield of wheat crop under varied management practices at farmers' elds, and hence can be applied for agricultural applications for farmers 

scholarly journals Assessment of Greenhouse Gases Emission in Maize-Wheat Cropping System Under Varied N Fertilizer Application Using Cool Farm Tool

2021 ◽  
Vol 9 ◽  
Author(s):  
Rakesh Kumar ◽  
S. Karmakar ◽  
Asisan Minz ◽  
Jitendra Singh ◽  
Abhay Kumar ◽  
...  
Keyword(s):  
Management Practices ◽  
Greenhouse Gas Emission ◽  
Cropping System ◽  
Fertilizer Application ◽  
Application Rate ◽  
N Fertilizer ◽  
Wheat Crop ◽  
Land Preparation ◽  
Direct Emission ◽  
Indirect Emission

In recent decades, climate change induced by enhanced global warming is one of the biggest challenges at the global level. Agriculture sectors significantly contribute to total anthropogenic greenhouse gas emission to the atmosphere. Wheat and maize, cultivated globally, and consumed in different forms, are considered as crucial staple cereal for ensuring food security to global population. The management practices involving land preparation, sowing, fertilizer application, irrigation, pest management, etc. significantly influence the emission of carbon dioxide (CO2) and nitrous oxide (N2O) from agricultural soil. In this study, CO2 and N2O emission were assessed from maize and wheat crops at four different levels of N fertilizer using cool farm tool model. Emissions of CO2 per hectare varied from 331.4 to 1,088.3 kgCO2 in maize and ranged from 292.3 to 765.3 kgCO2 in wheat on application of different doses of N. The total GHG emission in maize crops ranged from 859.5 to 3,003.4 kgCO2 eq per hectare with the application of nitrogen at varying levels (0–240 kg N per hectare). The highest N2O efflux (0.368 kg per ton) was observed at 240 kg N per hectare under wheat crop. The total on-farm emissions, through fertilizer production, account for about 33.7%, and emission of N2O contributes only 65.9%, whereas pesticides account merely 0.4% under maize-wheat cropping. This study confirms that the direct emission of N2O was totally dependent on N fertilizers application rate; however, the indirect emission was controlled by the fuels and energy consumption.

scholarly journals Use of PNUTGRO model for optimization of sowing date and plant spacing to maximize yield of groundnut (Arachis hypogaea L.)

MAUSAM ◽  
2021 ◽  
Vol 57 (2) ◽  
pp. 307-314
Author(s):  
R. P. SAMUI ◽  
R. BALASUBRAMANIAN ◽  
P. S. KULKARNI ◽  
A. M. SHEKH ◽  
PIARA SINGH
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Field Experiments ◽  
Sowing Date ◽  
Area Index ◽  
Pod Yield ◽  
Arachis Hypogaea L ◽  
Growth Development ◽  
Normal Spacing ◽  
Satisfactory Prediction

Lkkj & ihuVxzks ¼ih- ,u- ;w- Vh- th- vkj- vks-½ ekWMy dh izkekf.kdrk fl) djus ds fy, 1987 - 90 ds nkSjku vkuan] xqtjkr esa {ks=h; iz;ksx fd, x, gSaA bl ekWMy dk mi;ksx ew¡xQyh dh QhuksykWth] c<+ksrjh] fodkl vkSj iSnkokj dk iwokZuqeku yxkus ds fy, fd;k x;k gSSA ew¡xQyh ds izfr:fir iq"iu] isfxax] Qyh cuus vkSj Qyh idus dh frfFk;ksa] i.khZ {ks=Qy lwpdkad  ¼,y- ,- vkbZ-½ tSoHkkj] 'kSfyax dk izfr’kr rFkk iSnkokj dh rqyuk rhu i)fr;ksa uker% th- ,- ;w- th- 10] th- ,- ;w- th- 2 vkSj vkj- vk-sa - 33 - 1 ls izkIr gq, iszf{kr ekuksa ds lkFk dh xbZ gSA izfr:fir ?kVukØe ls iq"iu  ds fy, ,d fnu deh rFkk ik¡p fnu dh c<+r dk] isfxxa ds fy, 2 ls 6 fnuksa dh c<+r] Qyh cuus ds fy, 3 fnu dh deh rFkk 6   fnuksa dh c<+r dk vkSj Qyh idus ds fy, 6 fnu dh deh rFkk 5 fnu rd dh c<+r dk varj ik;k x;k gSA okLrfod ekuksa dh rqyuk esa bl ekWMy ls i.khZ {ks=Qy lwpdkad 91-8 ls 105-8 izfr’kr vkSj 'kSfyax dk izfr’kr 81-5 ls 109-8 ik;k x;k gSA bl ekWMy ls ew¡xQyh dh iSnkokj izsf{kr ekuksa dh rqyuk esa 88-5 ls 112-7 izfr’kr rd ikbZ xbZ gSA bl ekWMy ls izkIr ifj.kkeksa ds vk/kkj ij ij yxkrkj  pkj Qlyksa vkSj _rqvksa ds laca/k esa ew¡xQyh  dh QhuksYkWkth] c<+ksrjh] fodkl vkSj iSnkokj ds ckjs  esa iwokZuqeku larks"ktud ik;k x;k gSA ew¡xQyh dh izsf{kr vkSj izfr:fir iSnkokj ds chp 11 izfr’kr dh ?kVc<+ ikbZ xbZ gS ftlls irk pyrk gS fd ekWMy ds vk/kkj ij fd;k x;k iwokZuqeku larks"ktud gSA ,y- ,- vkbZ- dks NksMdj okLrfod ekuksa vkSj izsf{kr ekuksa esa varj ¼Mh-½ 0-03 vkSj 1-77 ds chp jgk gS ftlls ekWMy ds larks"ktud dk;Z djus dk irk pyrk gSA izfr:i.k v/;;uksa ds ifj.kkeksa ls irk pyrk gS fd tc vf/kd o"kkZ gksus dhs laHkkouk gks rks ew¡xQyh ds chtksa dh lkekU; nwjh rFkk cqokbZ ds lkekU; le; dh vis{kk chtksa dks vf/kd ikl&ikl cksdj rFkk cqokbZ yxHkx ,d lIrkg igys djds ew¡xQyh dh vf/kd iSnkokj  izkIr dh tk ldrh gSA  Field experiments were conducted at Anand, Gujarat during 1987-90 to validate the PNUTGRO model. The model was used to predict phenology, growth, development and yield of groundnut. The simulated flowering, pegging, pod formation and pod maturity dates, leaf area index (LAI), biomass, shelling % and pod yield of groundnut were compared with the observed values for three cultivars viz., GAUG 10, GAUG 2 and Ro-33-1. The simulated phenological events showed a deviation of –1 to +5 days for flowering, +2 to +6 days for peg formation, -3 to +6 days for pod formation and –6 to +5 days for pod maturity of the crop. The model estimated leaf area index within 91.8 to 105.8% and shelling percentage within 81.5 to 109.8% of the actual values. The model simulated the pod yields within 88.5 to 112.7% of the observed values. The results obtained with the model for the four consecutive crops and seasons revealed satisfactory prediction of phenology, growth, development and yield of groundnut. The percent error between observed and simulated pod yield was 11% which indicated satisfactory prediction by the model. The degree of agreement (d) ranged between 0.03 and 1.77 except for LAI indicating satisfactory performance of the model. Results of simulation studies indicated that when there is a possibility of high rainfall higher pod yield can be achieved by adopting closer spacing and early sowing (one week earlier than normal date of sowing) compared to normal spacing and date of sowing.

Weed Management in Peanuts

EDIS ◽  
2020 ◽  
Vol 2020 (3) ◽  
Author(s):  
Pratap Devkota
Keyword(s):  
Weed Control ◽  
Weed Management ◽  
Management Practices ◽  
Application Rate ◽  
Good Management ◽  
Peanut Production

Successful weed control in peanuts involves use of good management practices in all phases of peanut production. This 11-page document lists herbicide products registered for use in Florida peanut production, their mode of actions group, application rate per acre and per season, and reentry interval. It also discusses the performance of these herbicides on several weeds under Florida conditions. Written by J. A. Ferrell, G. E. MacDonald, and P. Devkota, and published by the UF/IFAS Agronomy Department, revised May 2020.

Assessment of sowing dates and plant densities using CSM-CROPGRO-Soybean for soybean maturity groups in low latitude

2021 ◽  
pp. 1-14
Author(s):  
L. S. Sampaio ◽  
R. Battisti ◽  
M. A. Lana ◽  
K. J. Boote
Keyword(s):  
Management Practices ◽  
Field Experiments ◽  
Plant Density ◽  
Crop Model ◽  
Management Scenarios ◽  
Low Latitude ◽  
Area Index ◽  
Sowing Dates ◽  
Plant Densities ◽  
Maturity Groups

Abstract Crop models can be used to explain yield variations associated with management practices, environment and genotype. This study aimed to assess the effect of plant densities using CSM-CROPGRO-Soybean for low latitudes. The crop model was calibrated and evaluated using data from field experiments, including plant densities (10, 20, 30 and 40 plants per m2), maturity groups (MG 7.7 and 8.8) and sowing dates (calibration: 06 Jan., 19 Jan., 16 Feb. 2018; and evaluation: 19 Jan. 2019). The model simulated phenology with a bias lower than 2 days for calibration and 7 days for evaluation. Relative root mean square error for the maximum leaf area index varied from 12.2 to 31.3%; while that for grain yield varied between 3 and 32%. The calibrated model was used to simulate different management scenarios across six sites located in the low latitude, considering 33 growing seasons. Simulations showed a higher yield for 40 pl per m2, as expected, but with greater yield gain increments occurring at low plant density going from 10 to 20 pl per m2. In Santarém, Brazil, MG 8.8 sown on 21 Feb. had a median yield of 2658, 3197, 3442 and 3583 kg/ha, respectively, for 10, 20, 30 and 40 pl per m2, resulting in a relative increase of 20, 8 and 4% for each additional 10 pl per m2. Overall, the crop model had adequate performance, indicating a minimum recommended plant density of 20 pl per m2, while sowing dates and maturity groups showed different yield level and pattern across sites in function of the local climate.

scholarly journals Agro-Economic Evaluation of Alternative Crop Management Options for Teff Production in Midland Agro-Ecology, Ethiopia

Agriculture ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 298
Author(s):  
Fekremariam Asargew Mihretie ◽  
Atsushi Tsunekawa ◽  
Nigussie Haregeweyn ◽  
Enyew Adgo ◽  
Mitsuru Tsubo ◽  
...  
Keyword(s):  
Management Practices ◽  
Smallholder Farmers ◽  
Early Stage ◽  
Crop Management ◽  
Production Costs ◽  
Agronomic Performance ◽  
Labor Costs ◽  
Management Options ◽  
Area Index ◽  
Weed Population

Teff is an important crop for smallholder farmers in Ethiopia. Improved crop management practices are needed to increase teff productivity and decrease production costs. Here, we used a split–split plot design to evaluate the impacts of different tillage, sowing, and soil compaction practices, and their combinations, on agronomic performance, weed population, lodging, and cost in teff production at the Aba Gerima watershed in northwestern Ethiopia in 2018–2020. Reduced tillage (RT) improved soil moisture, resulting in increased agronomic performance and decreased production costs compared with conventional tillage (CT); however, the weed population was substantially larger with RT than with CT. Row planting (RP) reduced seed cost and lodging but increased sowing and weeding costs compared with broadcast planting (BP). Plant population and leaf area index were substantially greater with BP than with RP during early-stage growth, but this reversed during late-stage growth. Despite labor costs being significantly greater with (WC) compaction than without (NC), little to no differences were observed in the weed population or in agronomic performance. Partial cost–benefit analysis revealed that RT–RP–WC followed by RT–RP–NC was the most economical treatment combination, suggesting that RT–RP–NC could be a labor-effective means of increasing teff production by smallholder farms in Ethiopia.

Assessment of groundwater contamination by chlorpyrifos using the PWC model in Valencia Region (Spain)

2021 ◽  
Author(s):  
Ricardo Pérez Indoval ◽  
Javier Rodrigo-Ilarri ◽  
Eduardo Cassiraga
Keyword(s):  
Reactive Transport ◽  
Management Practices ◽  
Fate And Transport ◽  
Environmental Modeling ◽  
Transport Processes ◽  
Negative Effects ◽  
Advection Dispersion ◽  
Agricultural Applications ◽  
Transformation Processes ◽  
Mass Transport Equation

&lt;p&gt;Chlorpyrifos is commoly used as an pesticide to control weeds and prevent nondesirable grow of algae, fungi and bacteria in many agricultural applications. Despite its highly negative effects on human health, environmental modeling of this kind of pesticide in the groundwater is not commonly done in real situations. Predicting the fate of pesticides released into the natural environment is necessary to anticipate and minimize adverse effects both at close and long distances from the contamination source. A number of models have been developed to predict the behavior, mobility, and persistence of pesticides. These models should account for key hydrological and agricultural processes, such as crop growth, pesticide application patterns, transformation processes and field management practices.&lt;/p&gt;&lt;p&gt;This work shows results obtained by the Pesticide Water Calculator (PWC) model to simulate the behavior of chlorpyrifos. PWC model is used as a standard pesticide simulation model in USA and in this work it has been used to&amp;#160; simulate the fate and transport of chlorpyrifos in the unsaturated zone of the aquifer. The model uses a whole set of parameters to solve a modified version of the mass transport equation considering the combined effect of advection, dispersion and reactive transport processes. PWC is used to estimate the daily concentrations of chlorpyrifos in the Bu&amp;#241;ol-Cheste aquifer in Valencia Region(Spain).&lt;/p&gt;&lt;p&gt;A whole set of simulation scenarios have been designed to perform a parameter sensitivity analysis. Results of the PWC model obtained in this study represents a crucial first step towards the development of a pesticide risk assessment in Valencia Region. Results show that numerical simulation is a valid tool for the analysis and prediction of the fate&amp;#160; and transport of pesticides in the groundwater.&lt;/p&gt;

scholarly journals Genotype selection and addition of fertilizer increases grain yield in upland rice in Suriname

2017 ◽  
Vol 47 (3) ◽  
pp. 185-194 ◽  
Author(s):  
Adriano Stephan NASCENTE ◽  
Ruby KROMOCARDI
Keyword(s):  
Grain Yield ◽  
Management Practices ◽  
Upland Rice ◽  
Block Design ◽  
Field Trials ◽  
Application Rate ◽  
Rice Grain ◽  
Rice Varieties ◽  
Local Conditions ◽  
Randomized Block Design

ABSTRACT The upland rice farmers in Suriname use local varieties and low level technologies in the field. As a result, the upland rice grain yield is low, at about 1 000 kg ha-1. Our objective was to evaluate the use of upland rice cultivars from Suriname and Brazil, and the effect of nitrogen, N, phosphorus, P, and potassium, K, fertilizers on cultivation variables. We undertook four field trials in the Victoria Area, in the Brokopondo District, using a randomized block design each with four replications. The most productive rice varieties were BRS Esmeralda (grain yield 2 903 kg ha-1) and BRS Sertaneja (2 802 kg ha-1). The highest grain yield of 2 620 kg ha-1 was achieved with a top dressing application of 76.41 kg N ha-1 20 days after sowing. For P, the highest grain yield of 3 085 kg ha-1 was achieved with application of 98.06 kg ha-1 P2O5 applied at sowing. An application rate of 31.45 kg ha-1 of K2O at sowing achieved the highest grain yield of 2 952 kg ha-1. Together, these application rates of N, P and K resulted in rice grain yield of about 3 000 kg ha-1, which is three times greater than the national average for upland rice. We demonstrate that the use of improved rice varieties matched to the local conditions, and application of appropriate fertilizers, are management practices that can result in significant increases in rice grain yield in Suriname.

scholarly journals Evapotranspiration simulated by CRITERIA and AquaCrop models in stony soils

2015 ◽  
Vol 10 (2) ◽  
pp. 67 ◽  
Author(s):  
Pasquale Campi ◽  
Francesca Modugno ◽  
Alejandra Navarro ◽  
Fausto Tomei ◽  
Giulia Villani ◽  
...  
Keyword(s):  
Statistical Tests ◽  
Efficiency Index ◽  
Balance Model ◽  
Coefficient Of Determination ◽  
Wheat Crop ◽  
Area Index ◽  
Aquacrop Model ◽  
Daily Evapotranspiration ◽  
Daily Scale ◽  
The Impact

The performance of a water balance model is also based on the ability to correctly perform simulations in heterogeneous soils. The objective of this paper is to test CRITERIA and AquaCrop models in order to evaluate their suitability in estimating evapotranspiration at the field scale in two types of soil in the Mediterranean region: non-stony and stony soil. The first step of the work was to calibrate both models under the non-stony conditions. The models were calibrated by using observations on wheat crop (leaf area index or canopy cover, and phenological stages as a function of degree days) and pedo-climatic measurements. The second step consisted in the analysing the impact of the soil type on the models performances by comparing simulated and measured values. The outputs retained in the analysis were soil water content (at the daily scale) and crop evapotranspiration (at two time scales: daily and crop season). The model performances were evaluated through four statistical tests: normalised difference (D%) at the seasonal time scale; and relative root mean square error (RRMSE), efficiency index (EF), coefficient of determination (r<sup>2</sup>) at the daily scale. At the seasonal scale, values of D% were less than 15% in stony and on-stony soils, indicating a good performance attained by both models. At the daily scale, the RRMSE values (2) indicate the inadequacy of AquaCrop to simulate correctly daily evapotranspiration. The higher performance of CRITERIA model to simulate daily evapotranspiration in stony soils, is due to the soil submodel, which requires the percentage skeleton as an input, while AquaCrop model takes into account the presence of skeleton by reducing the soil volume.

scholarly journals Selection of sowing date and biofertilization as alternatives to improve the yield and profitability of the F68 rice variety

2020 ◽  
Vol 38 (1) ◽  
pp. 61-72
Author(s):  
Yeison Mauricio Quevedo-Amaya ◽  
José Isidro Beltrán-Medina ◽  
José Álvaro Hoyos-Cartagena ◽  
John Edinson Calderón-Carvajal ◽  
Eduardo Barragán-Quijano
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Carbon Balance ◽  
Sowing Date ◽  
Dry Matter Accumulation ◽  
Phosphate Solubilizing Bacteria ◽  
Area Index ◽  
Use Of Resources ◽  
High Efficient ◽  
Selection Of

Multiple factors influence rice yield. Developing management practices that increase crop yield and an efficient use of resources are challenging to modern agriculture. Consequently, the aim of this study was to evaluate biological nitrogen fixation and bacterial phosphorous solubilization (biofertilization) practices with the selection of the sowing date. Three sowing dates (May, July and August) were evaluated when interacting with two mineral nutrition treatments using a randomized complete block design in a split-plot arrangement. Leaf carbon balance, leaf area index, interception and radiation use efficiency, harvest index, dry matter accumulation, nutritional status, and yield were quantified. Results showed that the maximum yield was obtained in the sowing date of August. Additionally, yield increased by 18.92% with the biofertilization treatment, reaching 35.18% of profitability compared to the local production practice. High yields were related to a higher carbon balance during flowering, which was 11.56% and 54.04% higher in August than in July and May, respectively, due to a lower night temperature. In addition, a high efficient use of radiation, which in August was 17.56% and 41.23% higher than in July and May, respectively, contributed to obtain higher yields and this behavior is related to the selection of the sowing date. Likewise, a rapid development of the leaf area index and an optimum foliar nitrogen concentration (>3%) were observed. This allowed for greater efficient use of radiation and is attributed to the activity of nitrogen-fixing and phosphate solubilizing bacteria that also act as plant growth promoters.

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