Effects of date of planting on plant emergence, leaf growth, and yield in contrasting potato varieties

1983 ◽  
Vol 101 (1) ◽  
pp. 81-95 ◽  
Author(s):  
J. L. Jones ◽  
E. J. Allen
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Leaf Growth ◽  
Growth And Yield ◽  
Soil Conditions ◽  
Area Index ◽  
Potato Varieties ◽  
Wide Range ◽  
Emerging Treatments ◽  
Soil Temperatures

SUMMARYFive experiments which studied the effects of a wide range of dates of planting on contrasting potato varieties in Pembrokeshire are reported. In three experiments (1976–7) four early varieties (Home Guard, Arran Comet, Irish Peace and Ulster Sceptre) were sprouted from the end of dormancy and compared at four dates of planting, which began as soon as soil conditions allowed (February in 1975 and 1976 and March in 1977). In these experiments all early-emerging treatments were damaged by frost and in 1975 and 1976 date of planting had little effect on leaf area index or yield. In 1977 planting in late April delayed and increased peak leaf area index but reduced yields throughout harvesting. In all experiments the emergence of varieties was affected by date of planting. The varieties with the longest sprouts emerged first only from the earliest plantings; at late plantings all varieties emerged together, which suggests that rate of post-planting sprout elongation decreased in this old seed as planting was delayed despite increasing soil temperatures. The implications for testing of early varieties are discussed.In two further experiments two early varieties (Home Guard in both years and Red Craigs Royal and Arran Comet in 1 year) were compared with three maincrop varieties (Désirée, Maris Piper, Stormont Enterprise) using seed which did not begin to sprout until January at dates of planting beginning in March. Sprout length was again poorly related to earliness of emergence. Delaying planting delayed and increased peak leaf area index in all varieties but only increased yields in the early varieties which had the smallest leaf areas. In maincrop varieties date of planting had little effect on final yields. In these years there were long periods without rain and in 1976 yields were limited by the amount of water available from the soil, for as each treatment exhausted this supply bulking ceased.

scholarly journals Analogy-Based Crop Yield Forecasts Based on Temporal Similarity of Leaf Area Index

2021 ◽  
Vol 13 (16) ◽  
pp. 3069
Author(s):  
Yadong Liu ◽  
Junhwan Kim ◽  
David H. Fleisher ◽  
Kwang Soo Kim
Keyword(s):  
Time Series ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Crop Yield ◽  
Satellite Data ◽  
Growing Season ◽  
Environmental Data ◽  
Area Index ◽  
Current Season ◽  
Wide Range

Seasonal forecasts of crop yield are important components for agricultural policy decisions and farmer planning. A wide range of input data are often needed to forecast crop yield in a region where sophisticated approaches such as machine learning and process-based models are used. This requires considerable effort for data preparation in addition to identifying data sources. Here, we propose a simpler approach called the Analogy Based Crop-yield (ABC) forecast scheme to make timely and accurate prediction of regional crop yield using a minimum set of inputs. In the ABC method, a growing season from a prior long-term period, e.g., 10 years, is first identified as analogous to the current season by the use of a similarity index based on the time series leaf area index (LAI) patterns. Crop yield in the given growing season is then forecasted using the weighted yield average reported in the analogous seasons for the area of interest. The ABC approach was used to predict corn and soybean yields in the Midwestern U.S. at the county level for the period of 2017–2019. The MOD15A2H, which is a satellite data product for LAI, was used to compile inputs. The mean absolute percentage error (MAPE) of crop yield forecasts was <10% for corn and soybean in each growing season when the time series of LAI from the day of year 89 to 209 was used as inputs to the ABC approach. The prediction error for the ABC approach was comparable to results from a deep neural network model that relied on soil and weather data as well as satellite data in a previous study. These results indicate that the ABC approach allowed for crop yield forecast with a lead-time of at least two months before harvest. In particular, the ABC scheme would be useful for regions where crop yield forecasts are limited by availability of reliable environmental data.

scholarly journals Growth and yield of wheat at different dates of sowing under chrland ecosystem of Bangladesh

2017 ◽  
Vol 14 (2) ◽  
pp. 147-154 ◽  
Author(s):  
MM Kamrozzaman ◽  
MAH Khan ◽  
S Ahmed ◽  
N Sultana
Keyword(s):  
Growth Rate ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Matter ◽  
Block Design ◽  
Grain Filling ◽  
Crop Growth ◽  
Growth And Yield ◽  
Area Index ◽  
Crop Growth Rate

An experiment was conducted at Sadipur charland under Farming System Research and Development Site, Hatgobindapur, Faridpur, during rabi season of 2012-13 and 2013-14 to study the growth and yield performance of cv. BARI Gom-24 as affected by different dates of sowing under Agro-ecological Zone-12 (AEZ-12) of Bangladesh. The experiment was laid out in randomized complete block design with six replications, comprising five different dates of sowing viz. November 5, November 15, November 25, December 5 and December 15. Results reveal that the tallest plant, leaf area index, total dry matter, and crop growth rate were observed in November 25 sown crop and leaf area index, total dry matter and crop growth rate were higher at booting, grain filling, and tillering stages of the crop. Maximum effective tillers hill-1 (3.49), spikes m-2, (311), number of grains spike-1 (42.20) and 1000-grain weight (52.10 g) were produced by November 25 sown crop exhibited the highest grain (4.30 t ha-1) and straw yield (4.94 t ha-1) as well as harvest index (46.88%) of the crop. Lowest performance was observed both in early (November 5) and late sown crop (December 15). The overall results indicated that November 25 sown crop showed better performance in respect of growth and yield of wheat under charland ecosystem of Bangladesh.J. Bangladesh Agril. Univ. 14(2): 147-154, December 2016

scholarly journals Extracting Leaf Area Index Using Viewing Geometry Effects - A New Perspective on High-Resolution Unmanned Aerial System Photography.

2020 ◽  
Author(s):  
Lukas Roth ◽  
Helge Aasen ◽  
Achim Walter ◽  
Frank Liebisch
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Plant Ecology ◽  
Growth And Yield ◽  
Unmanned Aerial System ◽  
Area Index ◽  
Handheld Device ◽  
Gap Fraction ◽  
Rgb Images ◽  
New Perspective

Abstract Extraction of leaf area index (LAI) is an important prerequisite in numerous studies related to plant ecology, physiology and breeding. LAI is indicative for the performance of a plant canopy and of its potential for growth and yield. In this study, a novel method to estimate LAI based on RGB images taken by an unmanned aerial system (UAS) is introduced. Soybean was taken as the model crop of investigation. The method integrates viewing geometry information in an approach related to gap fraction theory. A 3-D simulation of virtual canopies helped developing and verifying the underlying model. In addition, the method includes techniques to extract plot based data from individual oblique images using image projection, as well as image segmentation applying an active learning approach. Data from a soybean field experiment were used to validate the method. The thereby measured LAI 14 prediction accuracy was comparable with the one of a gap fraction-based handheld device (R2 of 0.92, RMSE of 0.42 m2 m2) and correlated well with destructive LAI measurements (R2 of 0.89, RMSE of 0.41 m2 m2). These results indicate that, if respecting the range (LAI ≤3) the method was tested for, extracting LAI from UAS derived RGB images using viewing geometry information represents a valid alternative to destructive and optical handheld device LAI measurements in soybean. Thereby, we open the door for automated, high-throughput assessment of LAI in plant and crop science.

Integrating remote sensing and climate data with process-based models to map forest productivity within west-central Alberta's boreal forest: Ecoleap-West

2006 ◽  
Vol 82 (2) ◽  
pp. 159-176 ◽  
Author(s):  
R J Hall ◽  
F. Raulier ◽  
D T Price ◽  
E. Arsenault ◽  
P Y Bernier ◽  
...  
Keyword(s):  
Climate Change ◽  
Remote Sensing ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Management Practices ◽  
Forest Productivity ◽  
Process Models ◽  
Growth And Yield ◽  
Area Index ◽  
Study Region

Forest yield forecasting typically employs statistically derived growth and yield (G&Y) functions that will yield biased growth estimates if changes in climate seriously influence future site conditions. Significant climate warming anticipated for the Prairie Provinces may result in increased moisture deficits, reductions in average site productivity and changes to natural species composition. Process-based stand growth models that respond realistically to simulated changes in climate can be used to assess the potential impacts of climate change on forest productivity, and hence can provide information for adapting forest management practices. We present an application of such a model, StandLEAP, to estimate stand-level net primary productivity (NPP) within a 2700 km2 study region in western Alberta. StandLEAP requires satellite remote-sensing derived estimates of canopy light absorption or leaf area index, in addition to spatial data on climate, topography and soil physical characteristics. The model was applied to some 80 000 stand-level inventory polygons across the study region. The resulting estimates of NPP correlate well with timber productivity values based on stand-level site index (height in metres at 50 years). This agreement demonstrates the potential to make site-based G&Y estimates using process models and to further investigate possible effects of climate change on future timber supply. Key words: forest productivity, NPP, climate change, process-based model, StandLEAP, leaf area index, above-ground biomass

scholarly journals LaiPen LP 100 – a new device for estimating forest ecosystem leaf area index compared to the etalon: A methodologic case study

2018 ◽  
Vol 64 (No. 11) ◽  
pp. 455-468
Author(s):  
Jakub Černý ◽  
Jan Krejza ◽  
Radek Pokorný ◽  
Pavel Bednář
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Optical Methods ◽  
Ecological Studies ◽  
Area Index ◽  
New Device ◽  
Area Efficiency ◽  
Wide Range ◽  
World Standard

Fast and precise leaf area index (LAI) estimation of a forest stand is frequently needed for a wide range of ecological studies. In the presented study, we compared side-by-side two instruments for performing LAI estimation (i.e. LaiPen LP 100 as a “newly developed device” and LAI-2200 PCA as the “world standard”), both based on indirect optical methods for performing LAI estimation in pure Norway spruce (Picea abies (Linnaeus) H. Karsten) stands under different thinning treatments. LAI values estimated by LaiPen LP 100 were approximate 5.8% lower compared to those measured by LAI-2200 PCA when averaging all collected data regardless of the thinning type. Nevertheless, when we considered the differences among LAI values at each measurement point within a regular grid, LaiPen LP 100 overestimated LAI values compared to those from LAI-2200 PCA on average by 1.4%. Therefore, both instruments are comparable. Similar LAI values between thinning from above (A) and thinning from below (B) approaches were indirectly detected by both instruments. The highest values of canopy production index and leaf area efficiency were observed within the stand thinned from above (plot A).

Field Competition between Ivyleaf Morningglory (Ipomea hederacea) and Soybeans (Glycine max)

Weed Science ◽  
1984 ◽  
Vol 32 (3) ◽  
pp. 364-370 ◽  
Author(s):  
Ronald C. Cordes ◽  
Thomas T. Bauman
Keyword(s):  
Soil Moisture ◽  
Glycine Max ◽  
Leaf Area Index ◽  
Leaf Area ◽  
Dry Weight ◽  
Growth And Yield ◽  
Yield Reduction ◽  
Area Index ◽  
Soybean Yield ◽  
Competition Effects

Detrimental effects on growth and yield of soybeans [Glycine max(L.) Merr. ‘Amsoy 77′] from density and duration of competition by ivyleaf morningglory [Ipomea hederacea(L.) Jacq. ♯3IPOHE] was evaluated in 1981 and 1982 near West Lafayette, IN. Ivyleaf morningglory was planted at densities of 1 plant per 90, 60, 30, and 15 cm of row in 1981 and 1 plant per 60, 30, 15, and 7.5 cm of row in 1982. Each density of ivyleaf morningglory competed for 22 to 46 days after emergence and the full season in 1981, and for 29 to 60 days after emergence and the full season in 1982. The best indicators of competition effects were leaf area index, plant dry weight, and yield of soybeans. Ivyleaf morningglory was more competitive during the reproductive stage of soybean growth. Photosynthetic irradiance and soil moisture measurements indicated that ivyleaf morningglory does not effectively compete for light or soil moisture. All densities of ivyleaf morningglory could compete with soybeans for 46 and 60 days after emergence in 1981 and 1982, respectively, without reducing soybean yield. Full-season competition from densities of 1 ivyleaf morningglory plant per 15 cm of row significantly reduced soybean yield by 36% in 1981 and 13% in 1982. The magnitude of soybean growth and yield reduction caused by a given density of ivyleaf morningglory was greater when warm, early season temperatures favored rapid weed development.

A simulation model of kenaf for assisting fibre industry planning in northern Australia. III. Model description and validation

1992 ◽  
Vol 43 (7) ◽  
pp. 1527 ◽  
Author(s):  
PS Carberry ◽  
RC Muchow
Keyword(s):  
Leaf Area Index ◽  
Soil Water ◽  
Leaf Area ◽  
Leaf Growth ◽  
Biomass Accumulation ◽  
Fibre Industry ◽  
Model Description ◽  
Northern Australia ◽  
Area Index ◽  
Extractable Soil

NTKENAF (Version 1.1) is a computer model which simulates the growth of kenaf (Hibiscus cannabinus L.) under rainfed conditions in tropical Australia. In daily time-steps, the model simulates the phenology, leaf area development, biomass accumulation and partitioning, soil water balance and dry matter yields of kenaf plants based on climatic and management inputs. The model assumes adequate nutrition and no effect of pests and diseases. The model uses daily maximum and minimum temperature, solar radiation and rainfall. The duration from sowing to flowering is predicted using temperature and photoperiod. Leaf growth is described as a function of node production (as determined by temperature), leaf area per node and leaf area senescence. Potential daily biomass is predicted from leaf area index, the light extinction coefficient and radiation use efficiency, and partitioned to the economic stem yield. Soil evaporation is predicted using a two-stage evaporation model, and plant transpiration is predicted from the daily biomass accumulation, a transpiration efficiency coefficient and predicted daily vapour pressure deficit. Plant extractable soil water is dependent on the available soil water range for each depth increment, the extraction front velocity, and the extent of water extraction at each depth. Daily transpiration and leaf growth are decreased below potential values once the fraction of available soil water declines below a threshold value. NTKENAF V1.1 has been validated against observed data from kenaf experiments conducted at two sites (lat. 13�48'S. and 14�28'S.) in northern Australia. The predictive accuracy of the model was good over a range in above-ground biomass up to 25 000 kg ha-1 (n = 40, r2 = 0.94, root mean square deviation = 1716 kg ha-1). Validations were also undertaken for predictions of the core and bark stem components, leaf area index and plant extractable soil water contents. The development of NTKENAF has provided a tool which can greatly aid assessment of the feasibility of a fibre industry based on kenaf in northern Australia.

scholarly journals Impact of Vermicompost, Poultry Manure and Jeevaamrit on Growth Parameters of Kiwifruit (Actinidia deliciosa) cv. Allison

2020 ◽  
pp. 31-40
Author(s):  
Ashok K. Garg ◽  
Rajesh Kaushal ◽  
Vishal S. Rana
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Photosynthetically Active Radiation ◽  
Poultry Manure ◽  
Growth And Yield ◽  
Recommended Dose ◽  
Inorganic Fertilizers ◽  
Area Index ◽  
Active Radiation ◽  
Chlorophyll Index

The present investigation was conducted on 6 years old kiwifruit vines cultivar ‘Allison’ at a spacing of 4.0 m × 6.0 m for two consecutive years 2018-19 and 2019-20 at experimental block of Department of Fruit Science, Dr YS Parmar University of Horticulture and Forestry, Nauni, Solan (HP). The experiment was laid out in triplicate in Randomized Block Design with 8 treatments under three farming systems viz., Inorganic Fertilizer Based System (IFBS), Organic Farming Based System (OFBS) and Subhash Palekar’s Natural Farming System (SPNFS). The maximum leaf area (158.1 cm2), leaf area index (4.36), chlorophyll index (51.2), comparative photosynthetically active radiation (612 µ mol quanta m-2 s-1) was found in the treatment (T8) receiving 30 liters of jeevaamrit (JM) + 3 kg ghana jeevaamrit and 40 kg FYM per vine under SPNFS. Among OFBS, the treatment T2 (100% recommended dose of nitrogen (RDN) through vermicompost and poultry manure on 50:50 basis) observed maximum leaf area (151.8 cm2), leaf area index (4.35), comparative photosynthetically active radiation (642 µ mol quanta m-2 s-1) but lower significantly lower chlorophyll index (51.2) over T1 (Recommended dose of inorganic fertilizers + FYM) treatment of IFBS. Hence application of 30 litres jeevaamrit and 3 kg ghana jeevaamrit (both in 3 equal splits first in end of January, second in February and third in the month of April) along with 40 kg FYM per vine or alternatively substitution of 100% RDN through vermicompost and poultry manure on 50:50 basis along with 40 kg FYM were found to be best and alternate different option in place of inorganic fertilizers to ‘Allison’ cultivar of kiwifruit under mid-hill conditions of Himachal Pradesh, India. Furthermore, the research emphases mainly on improving soil health without compromising growth and yield of kiwifruits in the region. By using alternative sources of nutrients, farmers can obtain the comparable growth and yield of kiwifruits.

scholarly journals Influence of Date of Sowing on Growth and Yield Performance of Field Pea (Pisum sativum L.) Genotypes

2020 ◽  
pp. 26-34
Author(s):  
Bulbul Ahmed ◽  
Ahmed Khairul Hasan ◽  
Biswajit Karmakar ◽  
Md. Sahed Hasan ◽  
Fahamida Akter ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Seed Yield ◽  
Growth Parameters ◽  
Field Pea ◽  
Growth And Yield ◽  
Yield Performance ◽  
Area Index ◽  
Stover Yield ◽  
Growth Characters

An experiment was carried out at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh during October 2014 to March 2015 to study the growth and yield performance of field pea varieties as influenced by date of sowing. The experiment comprised of two factors namely, date of sowing and variety. Date of sowing comprised of 29 October, 13 November and 28 November and the variety comprised of BARI motor-1, BADC motor-1, Natore local and Narail local. The experiment was laid out in a split plot design with three replications. The results indicate that all the growth characters were varied significantly at different days after. Those growth characters except leaf area index were highest for the crop sown on 28 November. The growth characters were highest in variety Natore local and lowest in Narail local except dry matter it was lowest in BADC motor-1. The interaction effect of 28 November sowing, Natore local was highest for all of the growth parameters except leaf area index it was highest on 13 November sowing and the interaction on 29 October sowing BARI motor-1 gave the lowest value. Most of the yield contributing parameters significantly affected by sowing date. The highest seed yield (827.7 kg ha-1) and other yield contributing characters were found on early sowing (13 November) and the lowest seed yield (534 kg ha-1) and other yield contributing characters was at 28 November sowing. Variety had significant effect on yield and yield contributing parameters. The highest seed yield (1032.2 kg ha-1) and Stover yield (3221.35 kg ha-1) was obtained from Natore local while Narail local gave lowest (469.1 kg ha-1) seed yield and lowest Stover yield. The interaction of 13 November with Natore local gave the highest seed yield (1319.3 kg ha-1) and lowest seed yield was produced by Narail local (330.35 kg ha-1) by late sowing (28 November). It can be concluded that, vegetative growth were highest at 28 November sowing and yield components gave highest value on 13 November sowing. Highest yield was produced by Natore local at 13 November sowing but yield was reduced drastically when the crop sown on 28 November. So, it is clear that the optimum date of sowing for field pea is at 13 November.

scholarly journals PERTUMBUHAN DAN PRODUKSI TANAMAN JAGUNG PROLIFIK PADA BERBAGAI JARAK TANAM DALAM BARIS DENGAN SISTEM TANAM JAJAR LEGOWO

2020 ◽  
Vol 4 (1) ◽  
pp. 13-23
Author(s):  
Intan Dwi Lestari
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Block Design ◽  
Stem Diameter ◽  
Growth And Yield ◽  
Area Index ◽  
Plant Weight ◽  
South Sulawesi ◽  
Randomized Block Design ◽  
Number Of Leaves

This research aimed to determine the effect of spacing on the growth and yield of corn. It was conducted from July to November 2019 at the Experimental Plantation of Cereal Crops Research Institute (BalitSereal), Maros, South Sulawesi. The experimental method used was a randomized block design consisting of 4 treatments: J1= (100 cm x 50 cm) x 20 cm, one seed per hole; J2= (100 cm x 50 cm) x 30 cm, alternating between one seed per hole and two seeds per hole; J3= (100 cm x 50 cm) x 40 cm, two seeds per hole; J4= (100 cm x 50 cm) x 15 cm, one seed per hole. The observed variables were plant height, number of leaves, stem diameter, leaf area index, Anthesis Silking Interval (ASI), length of cob 1 and cob 2, diameter of cob 1 and cob 2, weight of shelled seeds/plant, weight of 100 seeds on cob 1 and cob 2, and production of shelled seeds/hectare. The experimental results showed that plant spacing affected the growth and production of maize. The J3 spacing (100 cm x 50 cm) x 40 cm with two seeds per hole significantly affected the leaf area index and gave the highest average stem diameter. The J2 spacing with (100 cm x 50 cm) x 30 cm with alternating between one seed per hole and two seeds per hole produced the highest production in terms of weight of shelled seeds/plant, weight of 100 seeds and yield of shelled seeds/hectare.

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