scholarly journals Effects of Ridge Tillage and Straw Mulching on Cultivation the Fresh Faba Beans

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1054
Author(s):  
Bo Li ◽  
Xinyu Chen ◽  
Xiaoxu Shi ◽  
Jian Liu ◽  
Yafeng Wei ◽  
...  
Keyword(s):  
Rice Straw ◽  
Precision Agriculture ◽  
Field Experiments ◽  
Root Length Density ◽  
Root Surface ◽  
High Yield ◽  
Root Surface Area ◽  
Straw Mulching ◽  
Faba Beans ◽  
Ridge Tillage

Ridge tillage is an effective agronomic practice and a miniature precision agriculture; however, its effects on the growth of faba beans (Vicia faba L.) are poorly understood. This study aimed to determine the effect of ridge tillage and straw mulching on the root growth, nutrient accumulation and yield of faba beans. Field experiments were conducted during 2016 and 2017 cropping seasons and comprised four treatments: ridge tillage without any mulching (RT), flat tillage without any mulch (FT), flat tillage with rice straw mulched on the ridge tillage (FTRSM) and ridge tillage with rice straw mulched on the ridge tillage (RTRSM). The RT and RTRSM increased soil temperature and decreased soil humidity and improved soil total nitrogen, total phosphorus, available potassium and organic matter. RT and RTRSM increased the root length density, root surface area, root diameter and root activity of faba beans at flowering and harvest periods. The RT and RTRSM also increased the nitrogen, phosphorus, potassium absorption and the yield of faba beans. These results indicated that ridge tillage and straw mulching affect faba bean growth by improving soil moisture conditions and providing good air permeability and effective soil nutrition supply. This study provides a theoretical basis for the high yield cultivation improvement of faba beans.

scholarly journals Mowing Height, Nitrogen Rate, and Biostimulant Influence Root Development of Field-grown `TifEagle' Bermudagrass

HortScience ◽  
2006 ◽  
Vol 41 (3) ◽  
pp. 805-807 ◽  
Author(s):  
Brian J. Tucker ◽  
Lambert B. McCarty ◽  
Haibo Liu ◽  
Christina E. Wells ◽  
James R. Rieck
Keyword(s):  
Cynodon Dactylon ◽  
Root Length Density ◽  
Root Surface ◽  
Root Surface Area ◽  
First Year ◽  
Plant Responses ◽  
Turf Quality ◽  
N Rates ◽  
Positive Effect

As golfers demand higher quality golf green putting surfaces, researchers continue to seek improved turfgrass cultivars. One such improved cultivar is `TifEagle' bermudagrass [Cynodon dactylon (L.) Pers. × C. transvaalensis Burtt-Davy], which is an improvement over traditional bermudagrass cultivars such as `Tifgreen' and `Tifdwarf' due to its ability to tolerate mowing heights of ≤3.2 mm for extended periods. One observed disadvantage of `TifEagle' is its lack of a deep, dense root system compared to previous bermudagrass cultivars. This field study measured mowing height, N rate, and biostimulant product effects on `TifEagle' rooting. Three mowing heights (3.2, 4.0, and 4.8 mm), three N rates (12, 24, and 48 kg N/ha/week), and two cytokinin-containing commercial biostimulant products (BIO1 and BIO2) were examined. Plant responses measured were root length density (RLD), root surface area (RSA), thatch layer depth (TLD), and turf quality (TQ). Increasing mowing height from 3.2 to 4.0 mm increased RLD by >11%, RSA by >11%, and TQ by >17%. Increasing N rates from 12 to 24 kg N ha-1 week-1 increased RLD by >17%, RSA by >26% and TQ by >16%. No effect on RLD was observed after the first year of biostimulant use, however, after the second year, BIO1 increased RLD by >11% when applied with the lowest rate of N (12 kg N/ha/week). Higher mowing heights (4.8 and 4.0 mm) increased TLD >6% compared to the lowest mowing height (3.2 mm), and higher N rates (48 and 24 kg N/ha/week) increased TLD >3% compared to the lowest N rate (12 kg N/ha/week). Overall, a mowing heights ≥4.0 mm, N rates ≥24 kg N/ha/week, and long-term use of a cytokinins-containing biostimulant had a positive effect on `TifEagle' rooting.

Effect of Reed-Sedge Peat Moss on Hybrid Bermudagrass Injury with Indaziflam and Prodiamine in Sand-Based Root Zones

2013 ◽  
Vol 27 (3) ◽  
pp. 547-551 ◽  
Author(s):  
Patrick A. Jones ◽  
James T. Brosnan ◽  
Dean A. Kopsell ◽  
Greg K. Breeden
Keyword(s):  
Organic Carbon ◽  
Root Length ◽  
Root Length Density ◽  
Root Surface ◽  
Sand Culture ◽  
Peat Moss ◽  
Root Surface Area ◽  
Organic Carbon Content ◽  
Foliar Injury ◽  
Root Zones

PRE herbicides have been reported to injure both the foliage and roots of hybrid bermudagrass turf established in sand culture. Research was conducted to evaluate the influence of reed-sedge peat moss (RSPM) on hybrid bermudagrass injury following PRE herbicide applications to plants established in sand culture. Washed sod plugs were established in mini-rhizotrons constructed with sand root-zones varying in organic carbon content (0.000, 0.003, 0.007, and 0.012 kg kg−1). Herbicide treatments included indaziflam (35 and 52.5 g ai ha−1) and prodiamine (840 g ai ha−1). Significant foliar injury was only observed with indaziflam at 52.5 g ha−1. When applied to plants in sand with no detectable (0.000 kg kg−1) organic carbon, foliar injury measured 61% by 6 wk after treatment. Comparatively, injury with indaziflam at 52.5 g ha−1was reduced by 40% with applications to plants established in sand with 0.007 kg kg−1organic carbon. Root length, root length density, and root surface area were greatest in sand-based root zones with ≥ 0.007 kg kg−1organic carbon regardless of herbicide treatment; however, only indaziflam (52.5 g ha−1) and prodiamine-treated plants exhibited diminished root parameters relative to the nontreated check. Data in the current study illustrate that RSPM can affect above- and belowground injury following PRE herbicide applications to hybrid bermudagrass in sand root-zones.

Research on Regulating the Effect of Different Mulching Measures on Root Spatial Distribution and the Root-Shoot Ratio of Maize

2014 ◽  
Vol 1030-1032 ◽  
pp. 361-369
Author(s):  
Ke Xin Wang ◽  
Qiang Fu ◽  
Xin Jiang ◽  
Xiao Ping Zhang
Keyword(s):  
Spatial Distribution ◽  
Surface Area ◽  
Root Surface ◽  
Root Surface Area ◽  
Root Weight ◽  
No Tillage ◽  
Straw Mulching ◽  
Maize Growth ◽  
Shoot Ratio ◽  
Root Shoot Ratio

The effects of four types of mulching models (surface tillage with straw mulching, no-tillage with straw mulching on furrow, no-tillage with stubble mulching, and no-tillage with straw mulching on ridge and furrow) on the root spatial distribution and the relationship between the roots and shoots of maize were investigated using stratified digging methods, with maize as the test crop. The distribution of maize roots was cone shaped and gradually extended from 20 cm to 40 cm below the surface during the elongation stage. Under the different mulch tillage models, the effects on maize root growth were positive. The mulching measures significantly affected the control and support of the early and later stages of maize growth. The maize significantly differed in the root weight density (P=0.026<0.05) and the root surface area (P =0.005<0.01) with different mulching measures. No-tillage with straw mulching on the ridge and furrow was the only mulching model in which the growth of the roots and leaves of maize was limited. However, the other maize growth measures were better than conventional tillage. In addition, no-tillage with straw mulching on the ridge and furrow had an advantage in terms of the growth of the surface roots, while stubble mulching and strip mulching had advantages in terms of the growth of deep roots and radial roots, respectively. Surface tillage with straw mulching was an ideal cultivation method for the cold and arid regions of North China and had significant advantages in terms of the growth of the root weight, root surface area and root-shoot ratio.

Effect of Water Stress on Growth and Root Characteristics of Lentil

2020 ◽  
Author(s):  
Ramprosad Nandi ◽  
Prasanta Kumar Bandyopadhyay ◽  
Pragun Paul ◽  
Amit Karmakar ◽  
Prabir Chakraborti
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Drought Stress ◽  
Stress Condition ◽  
Root Length Density ◽  
Moisture Stress ◽  
Root Surface ◽  
Root Surface Area ◽  
Residual Soil ◽  
Root Characteristics

Background: Lentil mainly grows on residual soil moisture under rainfed conditions leading to abrupt soil moisture depletion causing mid or terminal drought stress to plants. Application of supplemental irrigation and adopting high yielding cultivars could alleviate drought stress and secure higher yield. Our present study aimed to study the growth of some promising varieties of lentil under four moisture regimes. Methods: To study the physiological responses of some promising lentil varieties under water stress, a pot experiment was performed at Bidhan Chandra Krishi Viswavidyalaya, Nadia, West Bengal during 2018-2019. Four lentil varieties i.e. Asha, PL 6, Subrata and Ranjan were grown under four moisture stress treatments through supplying water maintaining irrigation water (IW): cumulative pan evaporation (CPE) at its 100, 75, 50 and 25%.Result: Without stress condition Asha maintained the highest RLWC of 82.6 and 66.1% during flowering and pod formation stages, respectively; while Subrata got the maximum chlorophyll content (2.82 g l-1) during flowering stage. Under no stress root length density, root surface area and root volume were experienced the maximum values in all varieties, while, average root diameter was the highest under severe stress treatment for Ranjan. Our study concluded that Asha had potential to withstand water stress but Subrata was proved to be the best variety under no stress condition.

scholarly journals Estimating the Leaf Nitrogen Content with a New Feature Extracted from the Ultra-High Spectral and Spatial Resolution Images in Wheat

2021 ◽  
Vol 13 (4) ◽  
pp. 739
Author(s):  
Jiale Jiang ◽  
Jie Zhu ◽  
Xue Wang ◽  
Tao Cheng ◽  
Yongchao Tian ◽  
...  
Keyword(s):  
Nitrogen Content ◽  
Precision Agriculture ◽  
Field Experiments ◽  
Mean Squared Error ◽  
Growing Season ◽  
Leaf Nitrogen ◽  
Textural Analysis ◽  
Hyperspectral Images ◽  
Leaf Nitrogen Content ◽  
New Feature

Real-time and accurate monitoring of nitrogen content in crops is crucial for precision agriculture. Proximal sensing is the most common technique for monitoring crop traits, but it is often influenced by soil background and shadow effects. However, few studies have investigated the classification of different components of crop canopy, and the performance of spectral and textural indices from different components on estimating leaf nitrogen content (LNC) of wheat remains unexplored. This study aims to investigate a new feature extracted from near-ground hyperspectral imaging data to estimate precisely the LNC of wheat. In field experiments conducted over two years, we collected hyperspectral images at different rates of nitrogen and planting densities for several varieties of wheat throughout the growing season. We used traditional methods of classification (one unsupervised and one supervised method), spectral analysis (SA), textural analysis (TA), and integrated spectral and textural analysis (S-TA) to classify the images obtained as those of soil, panicles, sunlit leaves (SL), and shadowed leaves (SHL). The results show that the S-TA can provide a reasonable compromise between accuracy and efficiency (overall accuracy = 97.8%, Kappa coefficient = 0.971, and run time = 14 min), so the comparative results from S-TA were used to generate four target objects: the whole image (WI), all leaves (AL), SL, and SHL. Then, those objects were used to determine the relationships between the LNC and three types of indices: spectral indices (SIs), textural indices (TIs), and spectral and textural indices (STIs). All AL-derived indices achieved more stable relationships with the LNC than the WI-, SL-, and SHL-derived indices, and the AL-derived STI was the best index for estimating the LNC in terms of both calibration (Rc2 = 0.78, relative root mean-squared error (RRMSEc) = 13.5%) and validation (Rv2 = 0.83, RRMSEv = 10.9%). It suggests that extracting the spectral and textural features of all leaves from near-ground hyperspectral images can precisely estimate the LNC of wheat throughout the growing season. The workflow is promising for the LNC estimation of other crops and could be helpful for precision agriculture.

Improved growth and yield of Faba beans (Vicia faba cv. Fiord) by inoculation with strains of Rhizobium leguminosarum biovar. viciae in acid soils in south west Victoria

1994 ◽  
Vol 45 (3) ◽  
pp. 613 ◽  
Author(s):  
JM Carter ◽  
WK Gardner ◽  
AH Gibson
Keyword(s):  
Vicia Faba ◽  
Rhizobium Leguminosarum ◽  
Field Experiments ◽  
Natural Populations ◽  
Acid Soils ◽  
Growth And Yield ◽  
Nitrogen Accumulation ◽  
Commercial Strain ◽  
South West ◽  
Faba Beans

The response of faba beans (Vicia faba L. cv. Fiord) to seed inoculation with eight strains of Rhizobium leguminosarum biovar. viciae was examined in field experiments at six sites on acid soils in south-west Victoria. At two of the sites, two additional strains were examined, and in 1988, 14 strains were examined at one site. Very low natural populations of R. leguminosarum bv. viciae were found at the experimental sites. Most strains resulted in improved early nodulation and increased grain yield at all sites, when compared to inoculation with the commercial strain of rhizobia (SU391). Plant dry matter production and nitrogen accumulation in the plant shoot tissue was also increased at one site during the flowering period by some strains. Large visual differences between plots inoculated with SU391 and other strains were evident at most sites. Most uninoculated treatments were not nodulated and yielded very poorly. Treatments inoculated with the strain SU391 performed similarly to the uninoculated treatments.

scholarly journals Improved Rice Technology Adoption: The Role of Spatially-Dependent Risk Preference

Agriculture ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 691
Author(s):  
Omotuyole Isiaka Ambali ◽  
Francisco Jose Areal ◽  
Nikolaos Georgantzis
Keyword(s):  
Field Experiments ◽  
Climatic Factors ◽  
Risk Preferences ◽  
Risk Preference ◽  
Probit Model ◽  
Climatic Conditions ◽  
High Yield ◽  
Risk Attitudes ◽  
Policy Action ◽  
Rice Varieties

This study analyses farmers’ adoption of improved rice technology, taking into account farmers’ risk preferences; the unobserved spatial heterogeneity associated with farmers’ risk preferences; farmers’ household and farm characteristics; farm locations, farmers’ access to information, and their perceptions on the rice improved varieties (i.e., high yield varieties, HYV). The study used data obtained from field experiments and a survey conducted in 2016 in Nigeria. An instrumental-variable probit model was estimated to account for potential endogenous farmers’ risk preference in the adoption decision model. Results show that risk averse (risk avoidant) farmers are less likely to adopt HYV, with the spatial lags of farmers’ risk attitudes found to be a good instrument for spatially unobserved variables (e.g., environmental and climatic factors). We conclude that studies supporting policy action aiming at the diffusion of improved rice varieties need to collect information, if possible, on farmers’ risk attitudes, local environmental and climatic conditions (e.g., climatic, topographic, soil quality, pest incidence) in order to ease the design and evaluation of policy actions on the adoption of improved agricultural technology.

The use of natural conditions of the high alpine province of Dagestan for reproduction of prospective varieties and hybrids of potato

2021 ◽  
pp. 34-37
Author(s):  
В.К. Сердеров ◽  
Д.В. Сердерова
Keyword(s):  
Field Experiments ◽  
Climatic Conditions ◽  
High Yield ◽  
Potato Varieties ◽  
Caspian Lowland ◽  
The Republic ◽  
High Yielding Varieties ◽  
Almost All ◽  
The Cost ◽  
Mountain Province

Большое значение в увеличении продуктивности картофеля имеет внедрение в производство перспективных высокоурожайных сортов и гибридов, приспособленных к местным природно-климатическим условиям возделывания, от чего зависят эффективность отрасли и себестоимость продукции. Цель работы – изучить влияние климатических условий на продуктивность и качественные показатели сортов и гибридов картофеля, а также использование ими благоприятных почвенно-климатических условий высокогорья Республики Дагестан, для размножения и внедрения в производство новых перспективных, высокоурожайных, приспособленных к условиям среды выращивания сортов картофеля с комплексом хозяйственно-ценных признаков. Объектом изучения послужили сорта картофеля раннего, среднераннего и среднего сроков созревания российской, белорусской и иностранной селекции. Полевые опыты закладывали в 2014–2017 годах на высоте 2000–2200 м, на землях горного опорного пункта «Курахский» Курахского района и на равнинной провинции (Прикаспийской низменности) на территории дачного массива «Наука» Махачкалинского района Республики Дагестан. Схема посадки – 70×30 см, повторность – четырехкратная. Технология выращивания картофеля – гребневая. При проведении полевых опытов использовали общепринятые методики. Практически все сорта картофеля, выращенные на равнинной провинции, сформировали высокий урожай в первый год и при дальнейшем размножении в результате развития вирусных болезней резко снизили свои продуктивные качества. Наиболее высокая урожайность в среднем за три года отмечена у сортов Жуковский ранний (20,8 т/га), Импала (20,5 т/га), Невский (17,8 т/га), Предгорный (16,9 т/га) и Удача (16,3 т/га). В свою очередь, горная провинция Дагестана характеризовалась благоприятными почвенно-климатическими условиями для возделывания как продовольственного картофеля, так и для организации первичного семеноводства на безвирусной основе и размножения перспективных сортов этой культуры. В среднем за годы исследований в горной провинции по урожайности выделились сорта Сильвана (37,4 т/га), Удача (37,6 т/га), Рокко (33,3 т/га), Импала (31,7 т/га), Жуковский ранний (29,0 т/га), Предгорный (27,7 т/га) и Примобелла (27,7 т/га), а также гибриды № 12.40/17 (43,1 т/га) и № 13.61/61 (38,8 т/га). The introduction of promising high-yielding varieties and hybrids adapted to the local natural and climatic conditions of cultivation is of great importance in increasing the productivity of potatoes, which determines the efficiency of the industry and the cost of production. The aim of the work is to study the influence of climatic conditions on the productivity and quality indicators of potato varieties and hybrids, as well as their use of favorable soil and climatic conditions in the highlands of the Republic of Dagestan, for breeding and introducing into production new promising, high-yielding, adapted to the growing environment of potato varieties with a complex of economically valuable characteristics. The object of the study was potato varieties of early, mid-early and medium maturation periods of Russian, Belarusian and foreign selection. Field experiments were conducted in 2014–2017 at an altitude of 2000–2200 m, on the lands of the mountain stronghold Kurakhsky of the Kukhar district and on the plain province (the Caspian lowland) on the territory of the suburban area Nauka of the Makhachkala district of the Republic of Dagestan. The landing scheme is 70×30 cm, the repeatability is four times. The technology of growing potatoes is combed. When conducting field experiments, generally accepted methods were used. Almost all potato varieties grown in the lowland province formed a high yield in the first year and, with further propagation, as a result of the development of viral diseases, sharply reduced their productive qualities. The highest yield on average for three years was observed in the varieties Zhukovskiy ranniy (20.8 t/ha), Impala (20.5 t/ha), Nevsky (17.8 t/ha), Predgornyy (16.9 t/ha) and Udacha (16.3 t/ha). In turn, the mountain province of Dagestan was characterized by favorable soil and climatic conditions for the cultivation of both food potatoes, and for the organization of primary seed production on a virus-free basis and the reproduction of promising varieties of this crop. On average, over the years of research in the mountain province, the varieties Silvana (37.4 t/ha), Udacha (37.6 t/ha), Rocco (33.3 t/ha), Impala (31.7 t/ha), Zhukovskiy ranniy (29.0 t/ha), Predgornyy (27.7 t/ha) and Primobella (27.7 t/ha), as well as hybrids No.12.40/17 (43.1 t/ha) and No.13.61/61 (38.8 t/ha) were distinguished by yield.

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