Total Leaf Area Index Research Articles

Effect of Maize (Zea mays) and Soybean (Glycine max) Cropping Systems on Weed Infestation and Resource Use Efficiency

Agriculture has consistently improved to meet the needs of a growing global population; however, traditional monoculture farming, while highly productive, is facing challenges such as weed infestation and inefficient resource utilization. Herbicides effectively control weeds. However, their widespread use in weed management has the potential to contaminate soil and water, endangering the ecosystem by damaging non-target plant and animal species. Therefore, the main objective of this study was to evaluate the impact of different maize and soybean cropping systems on weed infestation and resource utilization. The experiment was a randomized complete block design with three replications consisting of three cropping systems: sole maize (SM), sole soybean (SS), and maize–soybean strip intercropping (MSI). In this study, the main difference between SM, SS, and MSI was the planting density, which was 60,000 (SM), 100,000 (SS), and 160,000 (maize–soybean in MSI). We observed that a higher total leaf area index in MSI resulted in increased soil cover, which reduced the solar radiations for weeds and suppressed the weed growth by 17% and 11% as compared to SS and SM, respectively. Whereas the radiation use efficiency for companion crops in MSI was increased by 39% and 42% compared to SS and SM, respectively. Moreover, the increased soil cover by total leaf area index in MSI also increased the efficiency of water use. Furthermore, our results indicated that reduced weed-crop competition increased the resource use in MSI, which resulted in increased crop yield and land equivalent ratio (LER 1.6). Eventually, this resulted in reduced inputs and increased land productivity. Therefore, we suggest that MSI should be adopted in resource-limiting conditions with higher weed infestation as it can simultaneously promote ecological balance and improve agricultural output, thereby reducing the environmental effects of traditional cropping systems.

Estimation of canopy photon recollision probability from airborne laser scanning

The past two decades have witnessed the widespread application of the spectral invariant theory (p-theory) in modeling the shortwave radiation absorbed or scattered by vegetation. The basic principle of this theory is that the canopy reflectance is solely determined by the optical properties of leaves and the photon recollision probability p. As one of the spectral invariants, p serves as a critical bond between the spectral characteristics of the canopy at any wavelength and the reflectance, transmittance, or absorptance of the vegetation canopy, and is intimately associated with the solution of the radiative transfer equation. Currently, estimation of p-value is predominantly accomplished through canopy structural parameters, such as the spherically averaged silhouette to total area ratio (STAR¯) or Leaf Area Index (LAI). In this work, we provide an approach to estimate canopy photon recollision probability directly from Airborne Laser Scanning (ALS) data. We showed that the recollision probability can be interpreted as the interceptions of virtual rays emitted from sampling points within tree crowns described with turbid media, which avoided detailed reconstruction of leaf structures. The approach was evaluated with both virtual experiments as well as field measurements. The virtual experiments employed the Large-scalE remote Sensing data and image Simulation model (LESS) to simulate virtual ALS scanning data based on three RAdiation transfer Model Intercomparison (RAMI) actual canopies, with each divided into 25 segments, for which the p-values could be obtained through LESS. Our findings showed that p-values can be accurately estimated from ALS point clouds. Specifically, it exhibited great consistency with RMSE% less than 5% for broadleaved forest scenes, 25% for mixed forest scenes, and less than 10% for coniferous forest scenes in virtual experiments, respectively, and less than 25% compared to field measurements. This study displays the potential of ALS as a promising tool for forest structure characterization and short-wave radiation modeling in forest ecosystems.

WOFOST-N: An improved WOFOST model with nitrogen module for simulation of Korla Fragrant pear tree growth and nitrogen dynamics

Few studies have focused on simulating fruit tree growth under fertilization constraints and evaluating nitrogen utilization efficiency. This study aimed to improve the WOFOST (World Food Studies) model by embedding the nitrogen dynamics module into the original WOFOST model (WOFOST-N) to simulate the Korla Fragrant pear tree growth, nitrogen transport, nitrogen use efficiency and nitrogen stress. In addition, we used the BBCH scale to provide a more detailed description of the phenological development process of pear trees to improve phenology simulation performance. Field trials were conducted in 2021 and 2022 in two pear orchards in the Alar region of China. The results showed that the simulated total dry weight (leaves and fruits, TAGPl,f) and leaf area index (LAI) growth dynamics agreed well with the measured values in each treatment in 2021 and 2022. The R2 values of the simulated TAGPl,f was between 0.87 and 0.97, and the R2 values of the simulated LAI were between 0.80 and 0.95. The improved model also showed relatively high simulation accuracy (8.2 % ≤ NRMSE ≤ 20.5 % for TAGPl,f, 7.1 % ≤ NRMSE ≤ 20.1 % for LAI). The improved model had good global simulation performance for soil nitrogen content in six treatments with a good consistency (R2 = 0.87 in 2021 and 0.89 in 2022) and low error (NRMSE = 12.4 % in 2021 and 11.8 in 2022). The simulated yields and nitrogen use efficiencies (NUE) in the two orchards also showed good performance, with R2 = 0.94 and 0.93, NRMSE = 5.2 % and 7.5 % for yields, R2 = 0.93 and 0.96, NRMSE = 10.7 % and 9.6 % for NUE, respectively. The proposed method provides a promising method to simulate fruit trees' growth and nitrogen dynamic effects.

Sugarcane exudates as nitrification inhibitors; improvement of soybean nitrogen recovery and yield by reducing soil nitrification and N2O emission using 15N tracing techniques

BNI (biological nitrification inhibition) derived from root exudates is typically used in rotation cropping systems to increase the crop nitrogen efficiency (NUE). Recently, the root exudates secreted by three sugarcane varieties in Thailand have been found to inhibit the nitrification and accumulation. The objective of the study was to evaluate the effectiveness of the sugarcane root exudate on (i) soil nitrification rate and N dynamics (soil mineral N and nitrous oxide (N2O) emission) and (ii) growth, yield, and 15N recovery by soybean under greenhouse conditions. The experiment was laid out as a randomized complete block design (RCBD), with five treatments and four replications: (i) N fertilizer (Control); (ii) Control + Uthong 13 sugarcane root exudate (UT13); (iii) Control + Khon Kaen 3 sugarcane root exudate (KK3); (iv) Control + wild cane sugarcane root exudate (Spone) and (v) Control + dicyandiamide (DCD). 15N fertilizer was applied to a micro-plot for 15N recovery. Soybean was planted and fertilized at 75 kg ha−1 N as (NH4)2SO4. Soil samples were collected at 1, 3, 7, 14, 21 and 28 days after N fertilization (DANF) for pH, potential nitrification rate (PNR), NH4+, NO3− and MBN measurement at 0–15 and 15–30 cm soil depths. A gas sample was collected by the soil chamber technique for an N2O emissions study on the soil sampling date. The soybean growth was monitored at 30 and 60 DAP (days after planting) for height, leaf area, leaf area index (LAI), SCMR and dry weight (DW). At soybean harvest, seed yield, yield components and N uptake were recorded. Our study revealed that the sugarcane root exudates significantly decreased PNR up to 14 DANF and increased NH4+ content in soil and reduced commutative N2O–N fluxes after 14 DANF, compared to N treatment (p < 005). The root exudate treatments not only increased growth (total DW and LAI at 60 DAP), yield (number of pods and seeds per plant) and N uptake (17–19%) but also 15N recovery in the total plant. This confirms the capacity of BNIs from sugarcane root exudates. In conclusion, sugarcane root exudates can effectively mitigate N2O emissions and enhance soybean N uptake under greenhouse conditions.

Dynamics of Agronomic Characteristics and Plant Diversity in Lemon Verbena (Aloysia citrodora Paláu) Cultivation in Greece

Nowadays, there is an increasing negative environmental effect of using chemical fertilizer. For this reason, the use of biofertilizers is promoted in the agriculture sector. The purpose of this investigation was to carry out an evaluation of the effects of biological fertilizer (biofertilizers are organic materials that can be used to improve soil properties) use on the growth and agronomic characteristics of Aloysia citrodora. To achieve this aim, a two-year randomized complete blocks field experiment was carried out in central Greece. The experiment included four biological fertilizer levels (0, 50, 100 and 150 N kg ha−1) with three replications. Plant height, dry stem, dry leaves, dry total yield and leaf area index (LAI) were measured during the two growing years. The results showed that in the first and second studied years, the maximum plant height and total dry yield were observed in the BF150 treatment. Moreover, LAI was ameliorated by applying the BF100 and BF150 treatments in both studied years. A key finding in this study is that the A. citrodora ecosystem favors herbaceous plant species richness. Also, soil factors (soil organic matter, P and K) promote positive herbaceous plant diversity within the A. citrodora ecosystem. Finally, A. citrodora could be a promising medicinal plant, cultivated under Mediterranean climatic conditions.

Methods for prediction of morphophysiological variables of Brachiaria decumbens grass

AbstractThe purpose of this study was to evaluate different methodologies used in the field in order to find the one that could most effectively relate to the morphophysiological condition of Brachiaria decumbens cv. Basilisk (syn. Urochloa decumbens cv. Basilisk Stapf R.D. Webster). Two light interception frequencies (LI, 85% and 95%) and two defoliation intensities were adopted as targets for the residual leaf area index (RLAI 1.3 and 1.8). The treatments consisted of evaluating different methods of measuring the canopy height (CH) through its ability to correlate with the morphophysiological variables of species B. decumbens cv. Basilisk. High correlations between the methods CH, compressed height (CHe), weighted height 1 (WH1) and weighted height 8 (WH8) were observed mainly with the variables total forage biomass (TFB) and leaf area index (LAI) in both residual and pre‐grazing conditions. The path analysis showed degrees of multicollinearity, which determined the use of the “k” constants in order to correct the distortions of the diagonal elements of the correlation matrix X'X. Path analysis provided direct cause/effect indexes on TFB using LAI = 0.1435, photosynthesis (A) = −0.1061, CH = 0.1616, CHe = 0.0913, WH1 = 0.1386 and WH8 = 0.0575; on LAI using CH = 0.2404, CHe = 0.2164, WH1 = 0.2307 and WH8 = 0.2183; and on photosynthesis rate (A) using LAI = 0.2895, CH = 0.0203, CHe = −0.1170, WH1 = 0.0352 and WH8 = 0.0937. Similarity was observed between intercepts and slope coefficients for TFB prediction using CH, CHe, WH1 and WH8, providing mean values of 1069.57 and 204.06, respectively. Methods CH and WH1 presented a significant correlation with most morphophysiological variables and can be used to quantify TFB and LAI, while CH and WH8 can be used only for TFB.

Matching light and nitrogen distributions in the maize canopy to achieve high yield and high radiation use efficiency

Light and nitrogen distribution within a plant's canopy reflect growth adaptation of crop to the environment and are conducive to improving the carbon assimilation ability. So is it possible to rationalize regulation in crop production to maximize yield by improving light and nitrogen distribution without adding additional inputs? In this study, the effects of different nitrogen application rates and planting densities on canopy light and nitrogen distribution of two high-yielding maize cultivars (i.e., XY335 and DH618) and the regulation of canopy physiological characteristics on radiation use efficiency (RUE) and yield were studied based on high yield field experiments in Qitai, China, during 2019 and 2020. The results showed that the distribution of photosynthetically active photon flux density (PPFD) in the maize canopy has been decreasing from top to bottom, while the vertical distribution of specific leaf nitrogen (SLN) initially increased and then decreased from top to bottom in the canopy. When SLN began to decrease, the PPDF of XY335 and DH618 were 0.5 and 0.3, corresponding to 40.6 and 49.3% of the total leaf area index (LAI). The KN/KL in the middle and lower canopy of the XY335 (0.32) was 0.08 higher than that of DH618 (0.24). Yield and RUE of the XY335 (17.2 t ha-1, 1.8 g MJ-1) were 7.0% (1.1 t ha-1) and 13.7% (0.2 g MJ-1) higher than that of DH618 (16.1 t ha-1, 1.6 g MJ-1). Therefore, better light conditions (the proportion of LAI in the upper and middle canopy is small) improved the light distribution when SLN started to decrease, thus helping to mobilize nitrogen distribution and maintain a high nitrogen extinction coefficient (KN) and KN/light extinction coefficient (KL). And KN/KL was a key parameter for yield improvement when maize nutrient requirements were met at 360 kg ha-1. At this time, an appropriately optimized high planting density could promote nitrogen utilization and produce higher yield and higher efficiency. This study will be important for maize high yield and high efficiency cultivation and breeding in the future.

Effect of Seed Priming and Moisture Conservation Measures on Growth and Yield of Baby Corn (Zea mays L.) under Rainfed Upland Situation

A field experiment was conducted during rabi, 2019-20 and 2020-21 at the PG experimental plot of the Department of Agronomy, BNCA to assess seed priming and moisture conservation measures on productivity and profitability of baby corn under the rainfed situation. The soil of the experimental site was acidic (pH 4.64), sandy loam in texture, medium in organic carbon (0.64%), low in available N (232.06 kg ha-1), P2O5 (13.84 kg ha-1) and K2O (115.27 kg ha-1). The experiment was laid out in factorial randomized block design with 4 levels of seed priming methods. S0: No priming; S1: Seed priming with 1% urea solution; S2: priming with 1% potash solution (MOP); S3: priming with 3 times diluted cow urine and 3 levels of soil moisture conservation measures viz. M0: No mulching; M1: use of bio mulch; M2: use of black polythene mulch. Results revealed that the highest and quickest seedling emergence (11.96 numbers m-2) was recorded under the treatment of seed priming with three times diluted cow urine which was at par with the treatment of seed priming with 1% urea and 1% KCl (MOP) solution. The total number of leaves m-2, total leaf area plant-1 and leaf area index (LAI) of baby corn were also changed significantly due to different moisture conservation measures but those parameters remain static due to different seed priming methods. The CGR (g m-2 day-1), RGR, (g g-1 day-1) and NAR (mg cm-1 day-1) of baby corn were also changed significantly due to different soil moisture conservation measures. The highest and most significant baby corn yield without husk(22.59 q ha-1) with 305.61 q ha-1 of green fodder yield along with harvest index (6.00), production efficiency (25.67 kg‑1 day-1 ha-1) and nutrient use productivity (9.41 kg‑1 ha-1 kg-1) were recorded under the treatment where black polythene mulching was used as soil moisture conservation measure.

Humic substances in the morphophysiology and production of Schizolobium parahyba (Vell.) Blake var. parahyba seedlings

The experiment was carried out in a seedling nursery of Federal University of Tocantins - Campus Gurupi. The treatments were into a 2x5 factorial scheme, the first referring to two methods of HS application and the second five doses. The parameters here evaluated were: plant height, stem diameter, number of leaves and leaflets, stem dry mass, leaves dry mass, root dry mass, shoot dry mass, total dry mass, chlorophyll a, chlorophyll b, total chlorophyll, chlorophyll a/b ratio, relative water content, internal CO2 concentration, net photosynthesis, stomatal conductance, evapotranspiration, specific leaf area, total leaf area, leaf area index, and developmental quality index. The application of HS in S. parahyba seedlings improves the traits: stem diameter, number of leaves and leaflet, chlorophyll b, net photosynthesis, evapotranspiration, water use efficiency, total leaf area and leaf area index.

The development of a global LAI and FAPAR product using GCOM-C/SGLI data

The Japan Aerospace Exploration Agency (JAXA) launched the Global Change Observation Mission - Climate (GCOM-C) satellite on December 23rd, 2017. As a part of the standard products of JAXA’s GCOM-C satellite, we developed the Leaf Area Index (LAI) and the Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) product. In comparison to other global LAI and FAPAR products by the National Aeronautics and Space Administration (NASA) and the Copernicus Global Land Service (CGLS), our products have the following advantageous features: high spatial and temporal resolution (250 m and daily); the retrieval algorithm (look-up-table) is based on “the Forest Light Environmental Simulator” (FLiES) which is a full 3-D canopy radiative transfer model as well as a vegetation landscape model and a global forest landscape map created for this study. The algorithm and ancillary data sets are completely independent of the existing products that are more or less influenced by the MODIS LAI/FAPAR, providing an alternate and independent source of LAI and FAPAR. The dataset has been created since April 2018 and is freely available on JAXA’s G-Portal site (https://gportal.jaxa.jp/gpr). As a result of accuracy assessment with in-situ data, the Root Mean Square Errors (RMSEs) for total LAI and FAPAR were 0.776 and 0.112, respectively. We also compared our LAI and FAPAR estimates with three existing global datasets (PROBA-V/OLCI, MODIS and VIIRS product). The spatial distribution of LAI and FAPAR showed different characteristics among the datasets although their temporal trends were similar. The differences in estimation results among datasets due to differences in the retrieval algorithms, base map (or land cover data) and input data need to be evaluated in the future.

A Semiempirical Approach for Decomposition of Remotely Sensed Leaf Area Index Into Overstory and Understory Components Over Russian Forests

Forest is a multi-layered canopy, where overstory and understory implement different biogeochemical cycles, phenology and functional role. Remote sensing products typically estimate forest total Leaf Area Index (LAI), while few quantify its components. The theoretical understanding of foliage distribution between layers is still quite limited. In this study we’ve developed a semi-empirical model for decomposition of forest total LAI between layers. Decomposition was implemented over the full extent of Russian forests, exhibiting a wide dynamic range of the forest total LAI. This paper addresses both the theoretical and practical aspects of the problem. In terms of theory we formalized the principles of forest layers "biological/radiometric coupling" into a parametric model allowing to analyze the relationship between overstory/ understory LAI and overstory crown fraction. The model captures various features of layers foliage growth, including the "understory seasonal dip effect". In terms of practical aspects, we generated time series of the MODIS layered LAI product for 2001-2020 at the spatial resolution of 230-m over Russian forests. We calculated mean layered LAI of species and contrasted with typical values from the literature surveys. According to our estimates relative contribution of understory LAI increases from South to North- 28% of forests pixels have understory LAI which exceeds that of overstory, those pixels are located in the northern part of the eastern Siberia and occupied by larch forests. The layered LAI product was intercompared/validated with multiple ground and remote sensing data.

Estimation of vegetation traits with kernel NDVI

Vegetation indices computed from spectral signatures are vastly used for monitoring the terrestrial biosphere. Indices are convenient proxies for canopy structure, and leaf pigment content, and consequently to estimate the photosynthetic activity of vegetation. Owing to its simplicity, the celebrated Normalized Difference Vegetation Index (NDVI) has been used as a proxy for greenness and canopy structure. Unfortunately, NDVI can only capture linear relationships of the near infrared (NIR) - red difference with the parameter of interest. To account for higher-order relations between the spectral channels, kernel NDVI (kNDVI) was proposed in (Camps-Valls et al., 2021). In this work, we give useful prescriptions for its proper use and show its good performance in a wider set of applications. We discuss the good characteristics of the index like boundedness, low error propagation. Furthermore, we give empirical evidence of performance in estimating in-situ vegetation parameters (leaf area index (LAI), gross primary productivity (GPP), leaf, and canopy chlorophyll content, green and total LAI and fraction of absorbed photosynthetically active radiation (fAPAR)) as well as the estimation of latent heat at flux tower level. We confirm the generally good performance of the index (correlation coefficient of kNDVI and canopy chlorophyll content is 0.919 and 0.933 for maize over two sites, as well as the correlation coefficient between kNDVI and carotenoid, is 0.816, 0.520 and 0.579 for three forest sites) and highlight its convenience in monitoring terrestrial ecosystems. To foster wider adoption of the new family of the index, we provide source code in 6 programming languages as well as efficient implementations in the Google Earth Engine (GEE) platform at https://github.com/IPL-UV/kNDVI.

Influence of Organic and Inorganic Nitrogen on the Growth and Yield of Wheat

To assess the effects of organic and inorganic N fertilizers regarding wheat yield and growth a field experiment was carried out from November 2019 to March 2020 at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh. There were three replications of the experiment, which was set up using a randomized full block design. The experiment comprises four varieties viz. BARI Gom-28, BARI Gom-30, BARI Gom-31, BARI Gom-32 and five levels of N viz. Control, 90 kg N ha-1 from prilled urea (PU), 57 kg N ha-1 from prilled urea (PU) + 3 t ha-1 poultry manure (PM) as organic N source, 62 kg N ha-1 from PU + 5 t ha-1 cowdung as organic N source, 29 Kg N ha-1 from PU + 4 t ha-1 vermicompost as organic N source. The outcome of the experiment revealed that there were substantial differences in the growth and yield of wheat due to different varietal effects and application of organic and inorganic nitrogen fertilizers, although some of the attributes were not found significant. At growth, BARI Gom-32 produced the highest number of total tillers hill-1 and leaf area index, while the highest number of total tillers hill-1 and leaf area index were obtained from 57 kg N ha-1 from PU and 3 t ha-1 PM at 20, 40, 60 and 80 DAS. At harvest, the highest number of effective tillers plant-1 (2.82), filled grain spike-1 (32.06), 1000-grain weight (61.07 g), grain yield (3.94 t ha-1), straw yield (5.85 t ha-1) and harvest index (40.11%) were obtained from BARI Gom-32. While, application of 57 kg N ha-1 from PU and 3 t ha-1 PM produced the tallest plant (95.49 cm), number of total tillers plant-1 (3.96), number of effective tillers plant-1 (3.20), filled grain spike-1 (36.61), 1000-grain weight (60.18 g from T5), grain yield (4.34 t ha-1), straw yield (6.23 t ha-1) and harvest index (41.07%). Again, the maximum number of total tillers plant-1 (4.06), number of effective tillers plant-1 (3.46), filled grain spike-1 (39.13), 1000-grain weight (64.62 g), grain yield (4.38 t ha-1), straw yield (6.27 t ha-1 ) and harvest index (41.16%) were found from BARI Gom-32 in combination with 57 kg N ha-1 from prilled urea and 3 t ha-1 poultry manure. Therefore, it can be concluded that BARI Gom-32 in combination with 57 kg N ha-1 from prilled urea and 3 t ha-1 poultry manure was more potential in terms of yield and would be suggested for the cultivation of wheat.

Maize/soybean strip intercropping produces higher crop yields and saves water under semi-arid conditions.

Sustainable increases in crop production require efficient use of resources, and intercropping can improve water use efficiency and land productivity at reduced inputs. Thus, in a three-year field experiment, the performance of maize/soybean strip intercropping system differing with maize plant density (6 maize plants m-2, low, D1; 8 maize plants m-2, medium, D2; and 10 maize plants m-2, high, D3) was evaluated in comparison with sole maize or soybean cropping system. Results revealed that among all intercropping treatments, D2 had a significantly higher total leaf area index (maize LAI + soybean LAI; 8.2), total dry matter production (maize dry matter + soybean dry matter; 361.5g plant-1), and total grain yield (maize grain yield + soybean grain yield; 10122.5kg ha-1) than D1 and D3, and also higher than sole maize (4.8, 338.7g plant-1, and 9553.7kg ha-1) and sole soybean (4.6, 64.8g plant-1, and 1559.5kg ha-1). The intercropped maize was more efficient in utilizing the radiation and water, with a radiation use efficiency of 3.5, 5.2, and 4.3g MJ-1 and water use efficiency of 14.3, 16.2, and 13.3kg ha-1 mm-1, while that of intercropped soybean was 2.5, 2.1, and 1.8g MJ-1 and 2.1, 1.9, and 1.5kg ha-1 mm-1 in D1, D2, and D3, respectively. In intercropping, the land and water equivalent ratios ranged from 1.22 to 1.55, demonstrating that it is a sustainable strategy to improve land and water use efficiencies; this maximization is likely associated with the species complementarities for radiation, water, and land in time and space, which resulted in part from competition avoidance responses that maximize the economic profit (e. g., 1300 US $ ha-1 in D2) over sole maize (798 US $ ha-1) or sole soybean (703 US $ ha-1). Overall, these results indicate that optimizing strip intercropping systems can save 20-50% of water and land, especially under the present scenario of limited resources and climate change. However, further research is required to fully understand the resource capture mechanisms of intercrops in intercropping.

Response of Grain Yield and Water Use Efficiency to Irrigation Regimes during Mid-Season indica Rice Genotype Improvement

Understanding the performance of rice (Oryza sativa L.) agronomic traits and efficiency in water usage as well as grain yield under various irrigation regimes is crucial to achieving high resource use efficiency and high yield. In this study, 12 mid-season indica rice genotypes that have been grown in the lower reaches of the Yangtze River for the past 80 years were studied in a field experiment for two years under two irrigation regimes, i.e., conventional irrigation (CI) and alternate wetting and drying irrigation (AWD). The results showed that with genotype improvement in irrigation regimes, the total number of spikelets, shoot and root dry weight, root oxidation activity, total leaf area index (LAI), effective LAI, leaf photosynthetic rate, and abscisic acid contents and zeatin + zeatin riboside contents in root bleeding sap were significantly increased at main growth stages. AWD irrigation synchronously increased rice resource use efficiency (water use efficiency (WUE), radiation use efficiency (RUE), and temperature use efficiency (TUE)) and grain yield. Compared to CI, AWD more significantly enhanced the performances of rice genotypes in all studied traits. Based on our findings, a semi-dwarf hybrid rice genotype has great potential for high resource use efficiency and high yield under alternate wetting and drying irrigation, which was attributed to the improved agronomic characteristics and superior root traits.

The Effect of Planting Time and Plant Density on Radiation Use Efficiency (RUE) on Lowland Rice (Oryza sativa L.) Cv. Inpari 30

The right planting time and plant density in rice cultivation in the rainy season affect the generative phase, where absorption of solar radiation intensity more efficiently increases productivity. This study aims to improve the absorption of energy efficiency of solar conversion with differences in planting time and planting density. The experiment was carried out from January to June 2019 in the experimental garden of Brawijaya University, Malang City, East Java. The research design used is a nested design with three replication. The main factor is planting time which consists of 3 levels, namely: January (B1); February (B2); March (B3). The nested factor is plant density which consists of 3 levels, namely: 111.111 plant ha-1 (T1); 166.667 plant ha-1 (T2); 226,667 plant ha-1 (T3). Data analysis used variance (ANOVA). If the results are significantly different, then the honest significant difference test (HSD) is continued at the 5% level. The results showed the differences in total leaf area index, plant dry weight, panicle weight every clump, grain weight every clump, grain weight every harvest plot, yield per hectare, and radiation use efficiency (RUE). The planting time in March has a higher RUE value than the planting time in January or February. The yield per hectare shows the planting time in March is higher than the planting time in January or February planting time. Plant density of 30x30 cm shows yields per hectare higher than planting density of 30x20 cm and planting density of 40x20x12.5 cm.Â

Spatially Distributed Overstory and Understory Leaf Area Index Estimated from Forest Inventory Data

Forest change affects the relative magnitudes of hydrologic fluxes such as evapotranspiration (ET) and streamflow. However, much is unknown about the sensitivity of streamflow response to forest disturbance and recovery. Several physically based models recognize the different influences that overstory versus understory canopies exert on hydrologic processes, yet most input datasets consist of total leaf area index (LAI) rather than individual canopy strata. Here, we developed stratum-specific LAI datasets with the intent of improving the representation of vegetation for ecohydrologic modeling. We applied three pre-existing methods for estimating overstory LAI, and one new method for estimating both overstory and understory LAI, to measurements collected from a probability-based plot network established by the US Forest Service’s Forest Inventory and Analysis (FIA) program, for a modeling domain in Montana, MT, USA. We then combined plot-level LAI estimates with spatial datasets (i.e., biophysical and remote sensing predictors) in a machine learning algorithm (random forests) to produce annual gridded LAI datasets. Methods that estimate only overstory LAI tended to underestimate LAI relative to Landsat-based LAI (mean bias error ≥ 0.83), while the method that estimated both overstory and understory layers was most strongly correlated with Landsat-based LAI (r2 = 0.80 for total LAI, with mean bias error of -0.99). During 1984-2019, interannual variability of understory LAI exceeded that for overstory LAI; this variability may affect partitioning of precipitation to ET vs. runoff at annual timescales. We anticipate that distinguishing overstory and understory components of LAI will improve the ability of LAI-based models to simulate how forest change influences hydrologic processes.

Assessing the influence of integrated nutrient management on growth performance of aromatic fine rice

An experiment was conducted at the Agronomy Field Laboratory, Bangladesh Agricultural University, Mymensingh during July 2017 to December 2017 to study the combined effect of vermicompost with inorganic fertilizers on the growth attributes of aromatic fine rice varieties. The experiment comprised three varieties viz. BRRI dhan34, Binadhan-13 and Kalizira, and five nutrient managements viz. Control (no application of manures and fertilizer), Recommended dose of inorganic fertilizers ( i.e. 150, 95, 70, 60, 12 kg ha-1 of Urea, TSP, MOP, Gypsum and Zinc Sulphate, respectively), vermicompost @ 3 t ha-1, 25% less than recommended dose of inorganic fertilizer + vermicompost @ 1.5 t ha-1, 50 % less than recommended dose of inorganic fertilizer + vermicompost @ 3 t ha-1. The experiment was laid out in a randomized complete block design with three replications. Growth characters of aromatic fine rice were significantly influenced by variety, nutrient management and interaction of variety and nutrient management. In case of variety, the highest number of total tillers hill-1 leaf area index, total dry matter production and chlrophyll content were obtained from Binadhan-13 at all sampling dates. While, Kalizira produced the lowest number of total tillers hill-1, total dry matter, leaf area index and chlorophyll content except plant height at all sampling dates. In case of nutrient management, the tallest plant, the highest number of total tillers hill-1, total dry matter production, leaf area index and chlrophyll content were obtained from 50 % less than recommended dose of inorganic fertilizer + vermicompost @ 3 t ha-1 at all sampling dates. But the shortest plant, the lowest number of total tillers hill-1, leaf area index, total dry matter production, crop growth rate and chlorophyll content were found in control (no manures and fertilizers) at all sampling dates. In case of interaction of variety and nutrient management, the highest number of total tillers hill-1, leaf area index, total dry matter production and chlorophyll content were found in Binadhan-13 along with 50 % less than recommended dose of inorganic fertilizer + vermicompost @ 3 t ha-1 at all sampling dates. So, it can be concluded that Binadhan-13 along with 50% less than the recommended dose of inorganic fertilizers + vermicompost @ 3 t ha-1 combination might be a promising practice for aromatic fine rice cultivation.

Energy and evapotranspiration partitioning over a humid region orchard: Field measurements and partitioning model comparisons

Understanding energy and water flux cycling and quantifying their components are essential steps to elucidate the hydrological process and sustainable water resources management in agricultural ecosystems. The challenge of partitioning energy and evapotranspiration (ET) components (canopy transpiration Tc and surface evaporation Es) was addressed by the combination of eddy covariance (EC) technique, micro-lysimeters, and sap flow methods in a humid region kiwifruit orchard of Southwest China. The variations of energy and water flux and their controls were assessed, then the measured ET and its component were compared with the simulated values by Priestley-Taylor Jet Propulsion Laboratory model (PT-JPL), Shuttleworth-Wallace (S-W), and FAO-56 dual crop coefficient models (Dual-FAO). The results showed that latent heat flux (LE) dominated the consumption of net radiation energy (Rn), with the averaged ratio (EF = LE/Rn) above 0.70 during the growing seasons. More radiation energy is released in the form of LE with increased surface moisture and vegetation cover (total leaf area index, LAIt). Tc accounted for 41%–46% ET. The increase of canopy leaf area index (LAIc) strongly affected ET partitioning through the early growing seasons, while atmospheric evaporation demand dominated the Tc/ET and even caused the energy to be redistributed since high atmospheric evaporation demand caused a decrease of Tc while an increase of Es during the active growing seasons (LAIc > 2.5 m2 m−2). All the ET models performed well in estimating ET (R2 = 0.84–0.92) and its components (Tc, R2 = 0.70–0.74; Es, R2 = 0.63–0.69), allowing individual estimation of water interception by the canopy is one of the merits of the PT-JPL model for ET simulation in this humid site, with R2 of 0.92, RMSE of 0.55 mm d−1, while the S-W model performed slightly better in ET component simulations (Tc, R2 = 0.74, RMSE = 0.35 mm d−1; Es, R2 = 0.69, RMSE = 0.38 mm d−1). The results of our study may have much referential significance for eco-hydrological process analysis and water flux estimation in regions with similar environmental conditions.

Impact of Different Methods of Root-Zone Application of Biochar-Based Fertilizers on Young Cocoa Plants: Insights from a Pot-Trial

Effective and efficient nutrient management is central to best-practice agriculture, facilitating sustainable intensification while reducing negative externalities. The application of biochar-based fertilizers (BBF) in tropical agronomy has the potential to improve nutrient management by enhancing nutrient availability and uptake. Here, we performed pot-trials with Theobroma cacao L. seedlings planted in an Oxisol with critically low phosphorus levels. Four fertilizer levels were deployed, including BBFs using micro-dosed biochar (16 g plant−1 i.e., 0.3% soil amendment w/w) charged with mineral fertilizer. Three different fertilizer-placement levels (topsoil, root-zone hotspot and root-zone layer) were evaluated. The results from the topsoil application of mineral fertilizer (farmer practice) served as the reference data. The root-zone layer application of BBF increased the aboveground biomass, total leaf area and chlorophyll content index by 56%, 222%, and 140% respectively. Foliar phosphorus levels were also significantly elevated by 53%. The N:P ratio of the foliar tissue was improved, indicating the potential of BBF to ameliorate P limitations. Thus, low dosages of biochar, which is upgraded to BBF, can considerably improve plant nutrition. Small scale technology to produce biochar can be easily adopted and integrated in T. cacao systems. We suggest that BBF production and application within tropical, perennial systems can contribute to achieving a range of sustainable development goals (SDGs), including climate action.