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

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.

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Effect of Sowing Date on Groundnuts in Sudan Gezira

Experimental Agriculture ◽

10.1017/s0014479700008279 ◽

1978 ◽

Vol 14 (1) ◽

pp. 13-16 ◽

Cited By ~ 1

Author(s):

Idris M. Nur ◽

Ali A. E. Gasim

Keyword(s):

Leaf Area Index ◽

Iodine Number ◽

Leaf Area ◽

Oil Content ◽

Sowing Date ◽

Area Index ◽

Pod Yield ◽

Sudan Gezira

SUMMARYA 4-year investigation of the effects of sowing date on three types of groundnut showed that the earlier the sowing date, the later was kernel initiation and kernel maturity. Early sowing resulted in a high pod yield, oil content and iodine number, but reduced the shelling percentage. The leaf area index ranged from 3·0 to 5·0, the highest value being obtained with early sowing and with non-upright bunch varieties.

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

Agronomía Colombiana ◽

10.15446/agron.colomb.v38n1.79803 ◽

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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Estimation of Peanut Leaf Area Index from Unmanned Aerial Vehicle Multispectral Images

Sensors ◽

10.3390/s20236732 ◽

2020 ◽

Vol 20 (23) ◽

pp. 6732

Author(s):

Haixia Qi ◽

Bingyu Zhu ◽

Zeyu Wu ◽

Yu Liang ◽

Jianwen Li ◽

...

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Vegetation Index ◽

Field Experiments ◽

Predictive Accuracy ◽

Vegetation Indices ◽

Planting Density ◽

Coefficient Of Determination ◽

Multispectral Images ◽

Area Index

Leaf area index (LAI) is used to predict crop yield, and unmanned aerial vehicles (UAVs) provide new ways to monitor LAI. In this study, we used a fixed-wing UAV with multispectral cameras for remote sensing monitoring. We conducted field experiments with two peanut varieties at different planting densities to estimate LAI from multispectral images and establish a high-precision LAI prediction model. We used eight vegetation indices (VIs) and developed simple regression and artificial neural network (BPN) models for LAI and spectral VIs. The empirical model was calibrated to estimate peanut LAI, and the best model was selected from the coefficient of determination and root mean square error. The red (660 nm) and near-infrared (790 nm) bands effectively predicted peanut LAI, and LAI increased with planting density. The predictive accuracy of the multiple regression model was higher than that of the single linear regression models, and the correlations between Modified Red-Edge Simple Ratio Index (MSR), Ratio Vegetation Index (RVI), Normalized Difference Vegetation Index (NDVI), and LAI were higher than the other indices. The combined VI BPN model was more accurate than the single VI BPN model, and the BPN model accuracy was higher. Planting density affects peanut LAI, and reflectance-based vegetation indices can help predict LAI.

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Influence of seed priming and water stress on selected physiological traits of borage

Folia Horticulturae ◽

10.1515/fhort-2015-0025 ◽

2015 ◽

Vol 27 (2) ◽

pp. 151-159 ◽

Cited By ~ 3

Author(s):

Soheila Dastborhan ◽

Kazem Ghassemi-Golezani

Keyword(s):

Medicinal Plant ◽

Grain Yield ◽

Leaf Area Index ◽

Leaf Area ◽

Field Experiments ◽

Seedling Emergence ◽

Field Performance ◽

Stability Index ◽

Seed Priming ◽

Area Index

Abstract Borage is a valuable medicinal plant with various constituents in leaves, flowers and seeds. Hence, it is important to improve the performance of this medicinal plant under different environmental conditions. Thus, two field experiments were arranged as split-plots based on a RCB design with three replications in 2012 and 2013, to evaluate the effects of seed priming and different irrigation intervals on selected physiological properties of borage leaves. Irrigation intervals (irrigation after 60, 90, 120, 150 mm evaporation from Class A pans, respectively) and priming treatments (control, water, KNO3 and KH2PO4) were allocated to the main and sub plots, respectively. The chlorophyll content index was enhanced under limited irrigation treatments, mainly due to a decrease in leaf area index and intercepting more radiation. However, the membrane stability index was stable under different irrigation intervals. Decreased relative water content and leaf area index and increased leaf temperature under lower water availability led to some reductions in the grain yield of borage. All of the priming techniques, particularly hydro-priming, enhanced the seedling emergence rate, leaf area index and consequently grain yield per unit area. Therefore, seed hydro-priming can be used to improve the field performance of borage, particularly when sufficient water is available.

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Comparison of an Antitranspirant Spray, a Polyacrylamide Gel, and Wind Protection on Early Growth of Muskmelon

HortScience ◽

10.21273/hortsci.41.2.361 ◽

2006 ◽

Vol 41 (2) ◽

pp. 361-366 ◽

Cited By ~ 2

Author(s):

Laurie Hodges ◽

Entin Daningsih ◽

James R. Brandle

Keyword(s):

Plant Growth ◽

Leaf Area Index ◽

Leaf Area ◽

Field Experiments ◽

Block Design ◽

Dry Weight ◽

Early Growth ◽

Polyacrylamide Gel ◽

Fresh Weight ◽

Area Index

Field experiments were conducted over 4 years to evaluate the effects of antitranspirant (Folicote, Aquatrol Inc., Paulsboro, N.J.) and polyacrylamide gel (SuperSorb, Aquatrol Inc., Paulsboro, N.J.) on early growth of transplanted muskmelon grown either protected by tree windbreaks or exposed to seasonal winds. A randomized complete block design (RCBD) with split plot arrangement was used with wind protection (sheltered and exposed) areas as the main treatment and use of an antitranspirant spray or gel dip as subtreatments. Based on destructive harvests in the field, treatments and subtreatments did not affect dry weight or leaf area index in the first 2 years. Specific contrasts, however, showed that gel application significantly increased fresh weight, dry weight, and leaf area index over that of the untreated transplants whereas the spray application tended to reduce these factors during the first 3 weeks after transplanting. Significant differences between gel and spray subtreatments disappeared by 5 weeks after transplanting. Shelterbelts ameliorated crop microclimate thereby enhancing plant growth. Significantly, wind velocity at canopy height was reduced 40% on average and soil temperatures were about 4% warmer in the sheltered plots compared to the exposed plots during the first 5 weeks post-transplant. Muskmelon plants in the sheltered areas grew significantly faster than the plants in the exposed areas in 2 of the 3 years reported, with the 3-year average fresh weight increased by 168% due to wind protection. Overall transplanting success and early growth were enhanced the most by wind protection, followed by the polyacrylamide gel root dip, and least by the antitranspirant foliar spray. We conclude that microclimate modification by wind speed reduction can increase early muskmelon plant growth more consistently than the use of polyacrylamide gel as a root dip at transplanting or the use of an antitranspirant spray. A polyacrylamide gel root dip generally will provide more benefit during early muskmelon growth than the use of an antitranspirant spray.

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Study of plant physiological parameters in winter oilseed rape (Brassica napus var. napus f. biennis L.) production on chernozem soil

Acta Agraria Debreceniensis ◽

10.34101/actaagrar/68/1779 ◽

2016 ◽

pp. 111-115

Author(s):

Éva Vincze ◽

Péter Pepó

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

Chlorophyll Content ◽

Oilseed Rape ◽

Plant Density ◽

Sowing Date ◽

Winter Oilseed Rape ◽

Sowing Time ◽

Area Index ◽

Relative Chlorophyll Content

We made plant physiology examinations in Arkaso winter oilseed rape hybrid substance: relative chlorophyll content (SPAD) and leaf area index (LAI) measurements. The experiment was set in University of Debrecen Agricultural Sciences Center at Látóképi Experimental Station in four replications, in two different sowing times (I. sowing date on 08/22/2014 and II. sowing date on 09/09/2014 sowing againhappened because of the incomplete germination in the second subtance 01/10/2014) Three different plant density 200, 350 and 500 thousand ha-1, under the same nutrient supply, 45 cm row spacing. The experiment was green crop of winter wheat. The relative chlorophyll content (SPAD) and leaf area index (LAI) measurements were made in seven different times. We measured the maximum value of chlorophyll content in the first sowing time at 500, and the second sowing time at 350 thousand ha-1 plant density. The measurement results proved that there was a linear relationship between the number of plants and the LAI. The maximum leaf area index values we measured in both the sowing time at 500 thousand ha-1 reached.

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The role of leaf area and photosynthesis in optimising the sowing date of maize

Acta Agraria Debreceniensis ◽

10.34101/actaagrar/64/1854 ◽

2015 ◽

pp. 5-10

Author(s):

Enikő Bene ◽

Mihály Sárvári

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

High Performance ◽

Photosynthetic Capacity ◽

Linear Regression Analysis ◽

Sowing Date ◽

Area Index ◽

The Third ◽

Growing Seasons ◽

Plant Sciences

Our sowing date experiment took place in the Demonstration Garden of Institution of Plant Sciences, Agricultural Center of University of Debrecen, in 2012–2014. The thesis contains data of test year 2014. Our purpose, besides several other examinations, was to observe how sowing date influences leaf area index and activity of photosynthesis of maize hybrids, and how those factors affect fruiting. In the experiment we monitored the change of the leaf area index and the photosynthesis of hybrids with four different growing seasons. Based on the results, it can be concluded that most of the examined hybrids reached their smallest leaf area with the third sowing date and with the highest yield results. Hybrid Da Sonka had the largest leaf area (4.10 m2 m-2), and hybrid DKC 4590 produced the highest yield (13.16 t ha-1) with the third sowing date. During testing the photosynthetic capacity, the extremely high performance of the youngest plants with the third sowing date is outstanding, which can be explained by the different ripening periods. Examination of the correlation between the photosynthetic capacity and the yield, by linear regression analysis, also proves that photosynthesis has a determinative role in fruiting. The results obtained confirm that not only the environmental and agricultural factors in the growing season have effect on the yield, but also other factors like the leaf area index and the photosynthesis are determinative parameters, and all those factors together, modifying effects of each other, develop average yields.

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A quantitative comparison of the growth, development and yield of different varieties of oilseed rape

The Journal of Agricultural Science ◽

10.1017/s0021859600053533 ◽

1975 ◽

Vol 85 (1) ◽

pp. 159-174 ◽

Cited By ~ 38

Author(s):

E. J. Allen ◽

D. G. Morgan

Keyword(s):

Field Experiment ◽

Leaf Area Index ◽

Leaf Area ◽

Oilseed Rape ◽

Quantitative Comparison ◽

Area Index ◽

The Mean ◽

Growth Development ◽

The Individual ◽

Pod Growth

SUMMARYA field experiment to compare the growth, development and yields of four varieties of oilseed rape, Cresus, Guile, Rigo and Nilla, is described and the results discussed. Cressus was the highest-yielding variety largely because it produced more pods and more seeds per pod. The numbers of pods and seeds per pod were positively correlated with the leaf area index at the onset of flowering. This suggests that the rate of supply of carbon assimilates to the inflorescences around the time of anthesis is an important yield-determining character. The mean weight of the individual seeds was greater in Cresus than Guile and this difference, which developed late on in pod growth, also contributed to the higher yields in Cresus.

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Determination of Principal Yield Attributing Traits of Hybrid Maize (Zea mays L.) Using Multivariate Analysis

International Journal of Bio-resource and Stress Management ◽

10.23910/1.2021.2366 ◽

2021 ◽

Vol 12 (5) ◽

pp. 594-602

Author(s):

L. Rana ◽

◽

H. Banerjee ◽

D. Mazumdar ◽

S. Sarkar ◽

...

Keyword(s):

Grain Yield ◽

Leaf Area Index ◽

Leaf Area ◽

Field Experiments ◽

Growth And Yield ◽

Planting Density ◽

Direct Effects ◽

Area Index ◽

Positive Direct ◽

Hybrid Maize

The field experiments were conducted at farmer’s field, Madandanga village under Chakdaha Block of Nadia district in West Bengal during rabi season 2014-15 and 2015-16. Treatments were distributed in split-factorial design, with three varieties (P ‘3533’, P ‘3396’, P ‘30V92’) in the main plot and three planting density (55,555, 66,666, 83,333 plants ha-1) × three sowing dates (November 20, November 30, December 10) combinations in the sub-plots, replicated thrice. Irrespective of planting density and sowing date, the variety ‘P30V92’ produced the highest yield, followed by ‘P3396’ and ‘P3533’. The significantly highest grain and stover yield was obtained in high density planting (83,333 plants ha-1), accounting 44.2 and 39.6% more than low planting density (55,555 plants ha-1), respectively. The maximum grain and stover yields were obtained from Nov. 20 sown plants; being 7.71 and 11.95% more than the grain yield derived from late sown (Dec. 10) plants. A correlation study showed that among the growth and yield components, leaf area index (0.96) and shelling percentage (0.91) exhibited highly positive direct effects on the grain yield of hybrid maize. However, other growth attributes, namely P uptake (0.88), K uptake (0.86) and plant height (0.81) exerted comparatively low positive direct effects on the grain yield of hybrid maize. Further, the standard regression equation revealed a significant relationship of shelling percentage (p≤0.01), leaf area index (p≤0.01) and uptake of P (p≤0.05) with grain yield.

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Aerial high-throughput phenotyping of peanut leaf area index and lateral growth

Scientific Reports ◽

10.1038/s41598-021-00936-w ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Sayantan Sarkar ◽

Alexandre-Brice Cazenave ◽

Joseph Oakes ◽

David McCall ◽

Wade Thomason ◽

...

Keyword(s):

Leaf Area Index ◽

Leaf Area ◽

High Throughput ◽

Lateral Growth ◽

Area Index ◽

Pigment Ratio ◽

Leaf Reflectance ◽

Pod Yield ◽

Plant Pigment ◽

High Throughput Phenotyping

AbstractLeaf area index (LAI) is the ratio of the total one-sided leaf area to the ground area, whereas lateral growth (LG) is the measure of canopy expansion. They are indicators for light capture, plant growth, and yield. Although LAI and LG can be directly measured, this is time consuming. Healthy leaves absorb in the blue and red, and reflect in the green regions of the electromagnetic spectrum. Aerial high-throughput phenotyping (HTP) may enable rapid acquisition of LAI and LG from leaf reflectance in these regions. In this paper, we report novel models to estimate peanut (Arachis hypogaea L.) LAI and LG from vegetation indices (VIs) derived relatively fast and inexpensively from the red, green, and blue (RGB) leaf reflectance collected with an unmanned aerial vehicle (UAV). In addition, we evaluate the models’ suitability to identify phenotypic variation for LAI and LG and predict pod yield from early season estimated LAI and LG. The study included 18 peanut genotypes for model training in 2017, and 8 genotypes for model validation in 2019. The VIs included the blue green index (BGI), red-green ratio (RGR), normalized plant pigment ratio (NPPR), normalized green red difference index (NGRDI), normalized chlorophyll pigment index (NCPI), and plant pigment ratio (PPR). The models used multiple linear and artificial neural network (ANN) regression, and their predictive accuracy ranged from 84 to 97%, depending on the VIs combinations used in the models. The results concluded that the new models were time- and cost-effective for estimation of LAI and LG, and accessible for use in phenotypic selection of peanuts with desirable LAI, LG and pod yield.

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