Estimating potato leaf area index for specific cultivars

Summary The growth and duration of crop leaf area determines the amount of solar radiation intercepted by the canopy and therefore influences the extent of photosynthesis, evaporation, transpiration and final dry matter yield. The objective of this study was to develop cultivar specific relationships to estimate the daily leaf area index (LAI) for the potato crop (Solanum tuberosum L.) that included the effects of available soil water. The model is divided into three LAI growth stages, the durations of which are partially related to potato heat units (PHU). The LAI in the first stage is estimated from a cultivar specific leaf area-based radiation use efficiency index with a soil water reduction factor. The second stage involves the maintenance of a constant LAI with the duration related to both PHU and a soil water index that can accelerate senescence. The final stage includes a decrease in the LAI from a maximum to zero in response to a cultivar specific PHU accumulation. Model simulations compared favourably with independent LAI measurements obtained with a LI-COR plant canopy analyzer over two seasons.     

Effects of leaf N concentration and leaf area index on determining rice tillering

Relative tillering rate(RTR)increased linear-ly with the increasing of leaf N concentration(NLV)has been already reported.To testwhether this relationship could be used toquantitatively explain the difference in tilleringamong a wide range of N application,field ex- periments were conducted at the IRRI farm,Los Banos,Laguna,the Philippines.Two in- dica cultivars,IR 72 and IR68284H wereused.For each cultivar,12 treatments includ- ing 4 N levels(0,60,120,and 180kgN·ha~(-1))and 3 transplanting spacing(30×20,20×20,and 10×20cm)were arranged in a ran-domized split-plot design with 4 replications.The N treatments were designated as mainplots and spacings as subplots.Fourteen-day-old seedlings were transplanted with 3seedlings per hill.The subplot area was 20m~2.Nitrogen fertilizer was applied as basal,atmidtillering,and at panicle initiation in threeequal splits.P,K,and Zn were applied asbasal at normal dosage.The field was flooded.Plant samples were taken every 7-14 d from 14d after transplanting to flower     

Dynamic change in rice leaf area index and spectral response under flooding stress

Paddy and Water Environment - Analysis of the canopy structure change and spectral response mechanism of rice under flooding stress is an important prerequisite for large-scale monitoring of rice...     

Relationship between leaf area index and ground cover in potato under different management conditions

The ability of a potato (Solanum tuberosum L.) plant to intercept solar radiation is closely related to tuber yield. Leaf Area Index and ground cover measurements are frequently used to estimate light interception. Within this experiment LAI and ground cover were highly correlated even under different management practices with correlation coefficients ranging from 0.52 to 0.92. When correlating LAI and ground cover the slope of the linear correlation varied with management, suggesting that LAI increased more rapidly than ground cover under some conditions. The differences between slopes may provide an estimate of canopy light interception efficiency. Leaf area duration (LAD) explained 74 and 79% of the difference in total tuber yield while ground cover duration (GCD) explained 74 to 87% of the variation in 1997 and 1998, respectively.     

Non-destructive estimation of potato leaf area index using a fish-eye radiometer

Summary Leaf area index (LAI) is widely used in many facets of potato (Solanum tuberosum L.) modelling but direct measurements have historically been difficult. This investigation tested the accuracy of a commercially available instrument (LI-COR LAI-2000) for measuring LAI non-destructively on a potato crop. Accurate estimates of LAI were difficult to obtain with small plots of≈1 m². Results from larger field plots were extremely favourable and indicate that non-destructive measurements of LAI in situ can routinely be estimated within 5 to 10% of the destructively measured LAI. Six thinning tests performed on four potato cultivars produced average root mean square error measurements of LAI that ranged from 0.09 to 0.27.     

Peanut leaf area index,light interception,radiation use efficiency,and harvest index at three sites in Texas

Stability of parameters describing crop growth of peanut (Arachis hypogaea L.) is important because of the diversity of climatic conditions in which peanuts are grown and is valuable when developing simulation models for this species. In contrast, variability in the same parameters is desirable for plant breeders working to develop improved cultivars. This study seeks to quantify key parameters for biomass and yield production of some common peanut cultivars at three sites in Texas. We measured leaf area index (LAI), light extinction coefficient (k) for Beer's law, and harvest index (HI) for four cultivars at Stephenville, TX and one cultivar near Gustine, TX, and for LAI and biomass on four cultivars at Seminole, TX. Mean radiation use efficiency (RUE) values were 1.98 g MJ⁻¹ at Stephenville, 1.92 at Gustine, and 2.02 at Seminole. Highest RUE values were for the Low-Energy Precise Application (LEPA) irrigation treatment at Seminole. Maximum LAI values ranged from 5.6 to 7.0 at Stephenville, from 5.0 to 6.2 at Seminole, and was 5.3 at Gustine. Mean k values ranged from 0.60 to 0.64 at Stephenville and was 0.77 at Gustine. The overall mean HI was 0.36, with a mean of 0.33 for Stephenville, 0.44 for Gustine, 0.53 for spray irrigation at Seminole, and 0.58 for LEPA irrigation at Seminole. Values of RUE, k, and HI for the cultivars in this study and similarities between this study and values reported in the literature will aid modelers simulating peanut development and yield and aid breeders in identifying key traits critical to peanut grain yield improvement.     

Assessing broadband vegetation indices and QuickBird data in estimating leaf area index of corn and potato canopies

Leaf area index (LAI) is a key biophysical variable that can be used to derive agronomic information for field management and yield prediction. In the context of applying broadband and high spatial resolution satellite sensor data to agricultural applications at the field scale, an improved method was developed to evaluate commonly used broadband vegetation indices (VIs) for the estimation of LAI with VI–LAI relationships. The evaluation was based on direct measurement of corn and potato canopies and on QuickBird multispectral images acquired in three growing seasons. The selected VIs were correlated strongly with LAI but with different efficiencies for LAI estimation as a result of the differences in the stabilities, the sensitivities, and the dynamic ranges. Analysis of error propagation showed that LAI noise inherent in each VI–LAI function generally increased with increasing LAI and the efficiency of most VIs was low at high LAI levels. Among selected VIs, the modified soil-adjusted vegetation index (MSAVI) was the best LAI estimator with the largest dynamic range and the highest sensitivity and overall efficiency for both crops. QuickBird image-estimated LAI with MSAVI–LAI relationships agreed well with ground-measured LAI with the root-mean-square-error of 0.63 and 0.79 for corn and potato canopies, respectively. LAI estimated from the high spatial resolution pixel data exhibited spatial variability similar to the ground plot measurements. For field scale agricultural applications, MSAVI–LAI relationships are easy-to-apply and reasonably accurate for estimating LAI.     

Is crop N demand more closely related to dry matter accumulation or leaf area expansion during vegetative growth?

The critical crop nitrogen uptake is defined as the minimum nitrogen uptake necessary to achieve maximum biomass accumulation (W). Across a range of crops, the critical N uptake is related to W by a power function with a coefficient less than unity that suggests crop N uptake is co-regulated by both soil N supply and biomass accumulation. However, crop N demand is also often linearly related to the expansion of the leaf area index (LAI) during the vegetative growth period. This suggests that crop N demand could be also linked with LAI extension. In this paper, we develop theory to combine these two concepts within a common framework. The aim of this paper is to determine whether generic relationships between N uptake, biomass accumulation, and LAI expansion could be identified that would be robust across both species and environment types. To that end, we used the framework to analyze data on a range of species, including C₃ and C₄ ones and mono- and di-cotyledonous crops. All crops were grown in either temperate or tropical and subtropical environments without limitations on N supply. The relationship between N uptake and biomass was more robust, across environment types, than the relationship of LAI with biomass. In general, C₃ species had a higher N uptake per unit biomass than C₄ species, whereas dicotyledonous species tended to have higher LAI per unit biomass than monocotyledonous ones. Species differences in N uptake per unit biomass were partly associated with differences in LAI and N-partitioning. Consequently the critical leaf-N uptake per unit LAI (specific leaf nitrogen, SLN) was relatively constant across species at 1.8–2.0 g m⁻², a value that was close to published data on the critical SLN of new leaves at the top of the canopy. Our results indicate that critical N uptake curves as a function of biomass accumulation may provide a robust platform for simulating N uptake of a species. However, if crop simulation models are to capture the genotypic and environmental control of crop N dynamics in a physiologically functional manner, plant growth has to be considered as the sum of a metabolic (e.g. leaves) and a structural (e.g. stems) compartment, each with its own demand for metabolic and structural N.     

The effects of autumn closing date on sward leaf area index and herbage mass during the winter period

The provision of grass for early spring grazing in Ireland is critical for spring calving grass‐based milk production systems. This experiment investigated the effect of a range of autumn closing dates (CD), on herbage mass (kg DM ha^?1), leaf area index (LAI) and tiller density (m^?2) during winter and early spring. Thirty‐six grazing paddocks, closed from 23 September to 1 December 2007, were grouped to create five mean CD treatments – 29 September, 13 October, 27 October, 10 November, 24 November. Herbage mass, tiller density and LAI were measured every 3 weeks from 28 November 2007 to 20 February 2008; additionally, herbage mass was measured prior to initial spring grazing and tiller density was measured intermittently until September 2008. Delaying CD until November significantly (P < 0·05) reduced herbage mass (by approximately 500 kg DM ha^?1) and LAI (by approximately 0·86 units) in mid‐February. On average, 35% of herbage mass present on swards on 20 February was grown between 28 November and 30 January. LAI was positively correlated with herbage mass (R² = 0·78). Herbage mass increased by approximately 1000 kg DM ha^?1 as spring grazing was delayed from February to April. Tiller density increased from November to February, although it did fluctuate, and it was greatest in April (9930 m^?2). This experiment concludes that in the south of Ireland adequate herbage mass for grazing in early spring can be achieved by delaying closing to early mid‐October; swards required for grazing after mid‐March can be closed during November.     

Chloris gayana Kunth under different defoliation regimes. Morphogenesis,sward structure and leaf area index

Subtropical pastures are an important alternative to increase forage yields to fulfil cattle nutritional requirements. Despite the increasing expansion of these pastures in the semiarid subtropical region of Argentina, there is very little information about their responses to grazing management. The aim of this study was to evaluate the effect of different defoliation regimes on morphogenesis, sward structure and leaf area index of one of the most expanded forage species in this region, Chloris gayana Kunth. A combination of two defoliation frequencies (300 and 500 GDD) and two defoliation intensities (1 and 3 green stubble leaves) was compared by a controlled experiment that comprised 1,500 GDD. Defoliation frequency significantly affected leaf elongation rate (LER) and leaf area index (LAI). Under the high defoliation frequency, LER and LAI resulted almost half than under low defoliation frequency (0.34 ± 0.08 vs. 0.67 ± 0.08 mm·tiller^?1·GDD^?1; 8.31 ± 2.27 m²/m² vs. 13.27 ± 1.59 m²/m², at 300 or 500 GDD respectively), regardless of the intensity. Defoliation frequency or intensity did not affect leaf appearance rate, leaf lifespan, leaf size, number of green leaves per tiller nor tiller density at the end of the experiment. We conclude that to maintain high LER and LAI in Chloris gayana Kunth cv. Épica INTA‐Pemán pastures, defoliation frequency could be of 500 GDD. Since leaf lifespan was 415 ± 110 GDD, under this defoliation frequency, a maximum accumulation of green leaf tissues with very little dead tissues may be achieved.     

低氮条件下密度对红壤旱地秋芝麻产量和叶面积指数的影响

为了探索低氮条件下红壤旱地秋芝麻高产栽培的适宜种植密度,2016年-2017年在进贤县和南昌县开展试验,研究6个密度（D1-15.0、D2-22.5、D3-30.0、D4-37.5、D5-45.0和D6-52.5 株/m2）对秋芝麻产量构成因素、产量和叶面积指数的影响。结果表明：2017年南昌县试验点D1和D2的单株蒴果数较D4显著增加18.32%和20.27%,其它处理的每蒴粒数较D3显著增加15.92%~25.04%;随着密度的增加秋芝麻产量呈现先增后减再增的趋势,2016年进贤点密度为D6时产量较D1显著增加40.78%,2017年进贤点为D2和D6时产量较D3显著增加18.00%和16.74%,2017年南昌点为D2、D5 和D6 的产量较D3 显著增加32.86%~44.15%。D2、D5、D6 的产量平均值较D1 显著增加20.66%~26.82%。叶面积指数随着种植密度的增加而增加,同时随着芝麻生长发育都表现为先增后减的趋势。因此,秋芝麻适宜密度应控制在22.5株/m2或45.0~52.5株/m2,才能够构建合理冠层,达到高产效果。     

Standardization of the leaf index method for the potato

Summary The leaf index was calculated using four different methods; namely, a. average index from 5 plants based only on 4th leaf from the top: b. average index of all the leaves of one plant; c. average index of 20 randomly selected leaves in a culture; d. average index of all the leaver of 5 plants of a culture. No significant differences between the four mthods were observed in the study. The method based only on 4th leaf from the top of the plant is recommended for calculating the leaf index in a potato crop. This method can be used very easily and conveniently in less time giving equivalent efficiency when compared with the other three methods.     

Relationships between ground cover,intercepted solar radiation,leaf area index and infrared reflectance of potato crops

Summary In field trials with potato several methods determining the proportion of intercepted solar radiation by the crop were compared. Non-destructive measurement of the proportion of ground cover with the aid of a grid correlated well with the proportion of intercepted photosynthetically active radiation as measured with a tube solarimeter and with the leaf area index. Measurement of the infrared reflectance of the crop proved to be an efficient and objective method to show differences between treatments. Moreover, it showed a good correlation with ground cover and radiation interception until full closure of the canopy. Percentage ground cover is useful for assessing intercepted solar radiation and leads to fewer errors in calculation of efficiency of conversion into dry matter than the other methods.     

杂交晚稻秧田分蘖习性及促蘖措施

杂交水稻根系强大，晚稻育秧期间温度高，秧田播种较稳，为秧田阶段的分蘖创造好的条件，可使秧田分蘖产量占总产量的２０％～３０％。通过多年对分蘖习性的观察，认为正确促控分蘖是杂交晚稻增加产量降低消耗的中心措施。     

A comparison of spectral reflectance and sward surface height measurements to estimate herbage mass and leaf area index in continuously stocked ryegrass pastures

Measurements of sward surface height and of the ratio of light at 660 and 730 nm reflected from a pasture canopy were correlated with measurements of leaf area index (LAI) and herbage mass of two ryegrass dominant swards. Both pastures were continuously stocked by sheep to maintain a range of sward heights from 2 to 6 cm corresponding approximately to LAI 2 to 5.
Sward height appeared to be linearly related to both LAI and herbage mass, whereas 660/730 reflectance displayed a non-linear relationship with both parameters. The accuracy of prediction by the two methods over the range LAI 1 to 3 or herbage mass 700 to 1800 kg DM ha^-1 was very similar. However, reflectance measurements could not be used above about LAI 3–4 and to this extent were less useful. Nevertheless, reflectance measurements have a potential advantage in their ability to sample large areas of pasture very quickly.     

Growth rate, senescence and photosynthesis of ryegrass swards cut to maintain a range of values for leaf area index

An experiment was carried out in which simulated swards of ryegrass (cv. S23) were grown in boxes. In the first instance the swards were cut at weekly intervals to maintain five levels of leaf area index (LAI) from LAI 1 to 4–5 in simulation of continuous grazing. Measurements were made of growth, senescence and net growth rate and of net canopy photosynthesis at constant irradiance. The results showed that the swards adapted to the defoliation regimes mainly by changes in tiller population density and pseudostem length. When the swards had equilibrated to the cutting regime growth rate increased with LAI but, since tiller density and the partitioning of growth between herbage harvested and that lost by sensecence also changed with LAI, net growth rate was constant over the LAI range 2–4·5. Maximum weight of herbage harvested was obtained between LAI 2 and 3.
After 10 weeks of weekly cutting all the swards were cut back to LAI 1 and allowed to regrow. Growth rate showed almost no response to the previous culling treatments. The relationship of net canopy photosynthesis to LAI was linear for the frequently defoliated swards and curvilinear for regrowing swards. The reasons for this difference were examined.     

Deep neural network algorithm for estimating maize biomass based on simulated Sentinel 2A vegetation indices and leaf area index

Accurate estimation of biomass is necessary for evaluating crop growth and predicting crop yield.Biomass is also a key trait in increasing grain yield by crop breeding.The aims of this study were(i)to identify the best vegetation indices for estimating maize biomass,(ii)to investigate the relationship between biomass and leaf area index(LAI)at several growth stages,and(iii)to evaluate a biomass model using measured vegetation indices or simulated vegetation indices of Sentinel 2A and LAI using a deep neural network(DNN)algorithm.The results showed that biomass was associated with all vegetation indices.The three-band water index(TBWI)was the best vegetation index for estimating biomass and the corresponding R2,RMSE,and RRMSE were 0.76,2.84 t ha−1,and 38.22%respectively.LAI was highly correlated with biomass(R2=0.89,RMSE=2.27 t ha−1,and RRMSE=30.55%).Estimated biomass based on 15 hyperspectral vegetation indices was in a high agreement with measured biomass using the DNN algorithm(R2=0.83,RMSE=1.96 t ha−1,and RRMSE=26.43%).Biomass estimation accuracy was further increased when LAI was combined with the 15 vegetation indices(R2=0.91,RMSE=1.49 t ha−1,and RRMSE=20.05%).Relationships between the hyperspectral vegetation indices and biomass differed from relationships between simulated Sentinel 2A vegetation indices and biomass.Biomass estimation from the hyperspectral vegetation indices was more accurate than that from the simulated Sentinel 2A vegetation indices(R2=0.87,RMSE=1.84 t ha−1,and RRMSE=24.76%).The DNN algorithm was effective in improving the estimation accuracy of biomass.It provides a guideline for estimating biomass of maize using remote sensing technology and the DNN algorithm in this region.     

Modeling temperature- and radiation-driven leaf area expansion in the contrasting crops potato and wheat

The performance of a model for simulating increase in leaf area index (L) was evaluated for potato (Solanum tuberosum L.) and wheat (Triticum aestivum L.) cultivars across environments (years and sites). Rate of L expansion just after emergence was assumed to depend on temperature. After a predefined L, L_s, expansion was assumed to increase in proportion to leaf dry weight increase that depended on intercepted radiation, henceforward: radiation-limited expansion. The L_s value at which the model performed best was considered to be the most realistic L at which expansion shifts from temperature to radiation-limitation. An L_s value of zero leads to solely radiation-limited expansion, whereas a value larger than maximum L leads to solely temperature-limited expansion. The criteria used to evaluate the model were constancy of calibrated model parameters across environments, and predictive ability. For potato and wheat, parameters were most robust across environments, when L_s was neither zero nor at maximum L. Model parameters did not vary with genotype. The model’s predictions were best at an L_s of 1.0 for potato and 1.5 for wheat. Using these L_s values, the coefficient of determination between observed and predicted values was 91% for potato and 88% for wheat. Sensitivity analysis revealed that smaller L_s values led to larger changes in rate of leaf area expansion and crop dry weight than larger values did. Crop dry weight was hardly affected by an increase in L_s. Implications of the results for modeling are discussed.