Evaluation of Drought Tolerance in Arkansas Cowpea Lines at Seedling Stage

Cowpea [Vigna unguiculate (L.) Walp.] is not only a healthy, nutritious and versatile leguminous crop, it also has a relatively high adaptation to drought. Researches have shown that cowpea lines have a high tolerance to drought, and many of them can survive over 40 days under very hot and dry conditions. The cowpea (Southern pea) breeding program at the University of Arkansas (UA) has been active for over 50 years and has produced more than 1,000 advanced breeding lines. And the purpose of this study is to evaluate the drought-tolerant ability in Arkansas cowpea lines and use the drought tolerant lines in cowpea production or as parents in cowpea breeding. A total of 36 UA breeding lines were used to screen drought tolerance at the seedling stage in this study. The experiment was conducted in greenhouse using completely randomized design (CRD) with two replicates. Drought stress was applied for four weeks, and three drought tolerant related traits were collected and analyzed. Results showed that cowpea breading line: 17-81, 17-86, Early Scarlet, and AR Blackeye #1 were found to be drought tolerant

Crop Characteristics Research: Growth and Reflectance Analysis

Much of the early research in remote sensing follows along developing spectral signatures of cover types. It was found, however, that a signature from an unknown cover class could not always be matched to a catalog value of known cover class. This approach was abandoned and supervised classification schemes followed. These were not efficient and required extensive training. It was obvious that data acquired at a single time could not separate cover types. A large portion of the proposed research has concentrated on modeling the temporal behavior of agricultural crops and on removing the need for any training data in remote sensing surveys; the key to which is the solution of the so-called 'signature extension' problem. A clear need to develop spectral estimaters of crop ontogenic stages and yield has existed even though various correlations have been developed. Considerable effort in developing techniques to estimate these variables was devoted to this work. The need to accurately evaluate existing canopy reflectance model(s), improve these models, use them to understand the crop signatures, and estimate leaf area index was the third objective of the proposed work. A synopsis of this research effort is discussed

Adaptasi Tanaman Kedelai terhadap Intensitas Cahaya Rendah : Karakter Daun untuk Efisiensi Penangkapan Cahaya

This research was conducted to identify some leaf characters related to light capture efficiency. It used split plot design with sub plot nested at the main plot. The main plot was light intensity consisted of two levels: I100 = light intensity 100% and I50 = light intensity 50%, while the sub plot was soybean genotype consisted of G1 = Pangrango, G2 = Ceneng, G3 = Godek, and G4 = Slamet. Leaf characters measured were : leaf total area, specific leaf area, trifoliate leaf area, leaf hairs (trichome) density, leaf thickness, length of palisade, chlorophylls content (chlorophyll a, b, and ratio a/b), and the greenness intensity. The result of research indicated that Ceneng has lower total leaf area, higher specific and trifoliate leaf area, less leaf hair density, thinner leaf, shorter palisade, higher greenness intensity, higher chlorophyll content (a and b), and also lower ratio chlorophyll a/b

Why does low intensity, long-day lighting promote growth in Petunia, Impatiens, and tomato?

Numerous reports demonstrate that low intensity, long-day (LD) lighting treatments can promote growth. However, there are conflicting suggestions as to the mechanisms involved. This study examines the responses of Petunia, Impatiens, and tomato to LD lighting treatments and concludes that no single mechanism can explain the growth promotion observed in each case. Petunia showed the most dramatic response to photoperiod; up to a doubling in dry weight (DW) as a result of increasing daylength from 8 h d–1 to 16 h d–1.This could be explained by an increase in specific leaf area (SLA) comparable to that seen with shading. At low photosynthetic photon flux densities (PPFD), the increased leaf area more than compensated for any loss in photosynthetic capacity per unit leaf area. In Petunia, the response may, in part, have also been due to changes in growth habit. Impatiens and tomato showed less dramatic increases in DW as a result of LD lighting, but no consistent effects on SLA or growth habit were observed. In tomato, increased growth was accompanied by increased chlorophyll content, but this had no significant effect on photosynthesis. In both species, increased growth may have been due to a direct effect of LD lighting on photosynthesis. This is contrary to the generally held view that light of approx. 3 – 4 μmol m–2 s–1 is unlikely to have any significant impact on net photosynthesis. Nevertheless, we show that the relationship between PPFD and net photosynthesis is non-linear at low light levels, and therefore low intensity LD lighting can offset respiration very efficiently. Furthermore, a small increase in photosynthesis will have a greater impact when ambient light levels are low

An algorithm for estimating crop calendar shifts of spring small grains using LANDSAT spectral data

There are no author-identified significant results in this report

Spectral estimates of solar radiation intercepted by corn canopies

Reflectance factor data were acquired with a Landsat band radiometer throughout two growing seasons for corn (Zea mays L.) canopies differing in planting dates, populations, and soil types. Agronomic data collected included leaf area index (LAI), biomass, development stage, and final grain yields. The spectral variable, greenness, was associated with 78 percent of the variation in LAI over all treatments. Single observations of LAI or greenness have limited value in predicting corn yields. The proportions of solar radiation intercepted (SRI) by these canopies were estimated using either measured LAI or greenness. Both SRI estimates, when accumulated over the growing season, accounted for approximately 65 percent of the variation in yields. Models which simulated the daily effects of weather and intercepted solar radiation on growth had the highest correlations to grain yields. This concept of estimating intercepted solar radiation using spectral data represents a viable approach for merging spectral and meteorological data for crop yield models

Quantitative estimation of plant characteristics using spectral measurement: A survey of the literature

There are no author-identified significant results in this report

Growth and reflectance characteristics of winter wheat canopies

A valuable input to crop growth and yield models would be estimates of current crop condition. If multispectral reflectance indicates crop condition, then remote sensing may provide an additional tool for crop assessment. The effects of nitrogen fertilization on the spectral reflectance and agronomic characteristics of winter wheat (Triticum aestivum L.) were determined through field experiments. Spectral reflectance was measured during the 1979 and 1980 growing seasons with a spectroradiometer. Agronomic data included total leaf N concentration, leaf chlorophyll concentration, stage of development, leaf area index (LAI), plant moisture, and fresh and dry phytomass. Nitrogen deficiency caused increased visible, reduced near infrared, and increased middle infrared reflectance. These changes were related to lower levels of chlorophyll and reduced leaf area in the N-deficient plots. Green LAI, an important descriptor of wheat canopies, could be reliably estimated with multispectral data. The potential of remote sensing in distinguishing stressed from healthy crops is demonstrated. Evidence suggests multispectral imagery may be useful for monitoring crop condition

Applicability of selected wheat remote sensing technology to corn and soybeans

There are no author-identified significant results in this report

Processing techniques development, volume 2. Part 1: Crop inventory techniques

There are no author-identified significant results in this report