Almond Orchards Research Articles

Is the Subsurface Drip the Most Sustainable Irrigation System for Almond Orchards in Water-Scarce Areas?

The expansion of irrigated almond orchards in arid and semi-arid areas with scarce water available raises key issues related to the sustainability of the water resources. A 3-year field experiment was conducted on a commercial young almond orchard located in the southeast of Spain to study the effect of two drip irrigation systems (surface, DI and subsurface, SDI) on almond crop growth and their physiological responses under fully-irrigated conditions. Crop evapotranspiration (ETc) and its components (crop transpiration, Tc and soil evaporation, Es) were monitored as well as the irrigation water and nitrogen productivities. To estimate ETc, a simplified two-source energy balance (STSEB) approach was used. Although a lower irrigation water amount was applied in SDI compared to DI (differences between 10% and 13.8%), the almond crop growth and physiological responses as well as the yield components and kernel yield showed no significant differences. The ETc estimates resulted in small differences for spring and fall periods (0.1–0.2 mm day−1) for both treatments, while differences were significant during higher ETo periods (May–August), being 1.0–1.3 mm day−1 higher for the DI treatment than for the SDI treatment. The irrigation water productivity (IWP) was significantly higher in the SDI treatment than in the DI treatment. However, no significant differences between the two treatments were observed for nitrogen productivity. It can be concluded that the SDI system is a suitable strategy for irrigating almond crops, reducing consumptive water use and increasing IWP.

Pollen collection by honey bee hives in almond orchards indicate diverse diets

Almond is one of the world's most economically valuable crops and many varieties require cross pollination for optimal fruit set. For this reason, western honey bee (Apis mellifera L.) hives are often placed in almond orchards. However, little is known about the usage of almond and other pollen sources by individual hives during almond bloom. Here, we investigated the timing, identity and quantity of pollen collection associated with almond floral abundance and spatial location of individual hives by sampling 440 individual pollen tray samples and counting 45,072 pollen grains from 13,200 pollen pellets collected from 80 individual hives across the flowering season in Victoria, south-eastern Australia. A large proportion of hives collected non-almond pollen in addition to almond pollen (63/80 = 79%). The weight of almond pollen collected by the hives at each sampling time was positively related to the number of concurrently open almond flowers. However, non-almond pollen richness and abundance was not related to the number of almond flowers but had a positive relationship with the weight of almond pollen collected. There was no relationship between the distance among hives and identity of pollen collected. Yet, three plant families in the study area were found to account for a high percentage of the non-almond pollen collected, Euphorbiaceae, Fabaceae and Asteraceae. Understanding crop and non-crop pollen collection could inform honey bee diet needs and identify the plant species of importance to inform best practice bee management during almond flowering.

Winter Cover Crops Reduce Spring Emergence and Egg Deposition of Overwintering Navel Orangeworm (Lepidoptera: Pyralidae) in Almonds.

Habitat diversification has been shown to positively influence a variety of ecosystem services to agriculture, including biological control of arthropod pests. The impact of increased biodiversity tends to be species specific though, and practices therefore need to be developed on a case-by-case basis for each cropping system. In perennial systems, numerous studies have demonstrated that cover crops can have positive impacts on soil quality and other ecosystem services, such as pollination and pest management. However, few studies have focused on the use of cover crops to enhance pest control in almond orchards, especially winter cover crops. The primary pest of almonds in North America is navel orangeworm, Amyelois transitella Walker, which overwinter as larva or pupa on remnant nuts, many of which remain on the orchard soil surface. In the spring, first flight adults subsequently use these remnant nuts as reproductive substrate. An experiment was conducted to evaluate the influence of two distinct winter cover crop mixtures on overwintering mortality and spring egg deposition of A. transitella. Remnant nuts placed into cover crop plots produced fewer adult A. transitella in the spring, suggesting increased overwintering mortality. Additionally, spring egg deposition was reduced on remnant nuts in the cover crops, possibly due to the ground covers interfering with host location and access. In this way, winter cover crops appear to contribute to the reduction of A. transitella populations in the orchard by altering abiotic and physical conditions, although studies to document specific mechanisms are still needed.

Comparative Profiling of Wood Canker Pathogens from Spore Traps and Symptomatic Plant Samples Within California Almond and Walnut Orchards.

Fungi causing wood canker diseases are major factors limiting productivity and longevity of almond and walnut orchards. The goal of this study was to compare pathogen profiles from spore traps with those of plant samples collected from symptomatic almond and walnut trees and assess if profiles could be influenced by orchard type and age, rainfall amount and frequency, and/or neighboring trees. Three almond orchards and one walnut orchard with different characteristics were selected for this study. Fungal inoculum was captured weekly from nine trees per orchard using a passive spore-trapping device, during a 30-week period in the rainy season (October to April) and for two consecutive years. Fungal taxa identified from spore traps were compared with a collection of fungal isolates obtained from 61 symptomatic wood samples collected from the orchards. Using a culture-dependent approach coupled with molecular identification, we identified 18 known pathogenic species from 10 fungal genera (Ceratocystis destructans, Collophorina hispanica, Cytospora eucalypti, Diaporthe ampelina, Diaporthe chamaeropis/rhusicola, Diaporthe eres, Diaporthe novem, Diplodia corticola, Diplodia mutila, Diplodia seriata, Dothiorella iberica, Dothiorella sarmentorum, Dothiorella viticola, Eutypa lata, Neofusicoccum mediterraneum, Neofusicoccum parvum, Neoscytalidium dimidiatum, and Pleurostoma richardsiae), plus two unidentified Cytospora and Diaporthe species. However, only four species were identified with both methods (Diplodia mutila, Diplodia seriata, Dothiorella Iberica, and E. lata), albeit not consistently across orchards. Our results demonstrate a clear disparity between the two diagnostic methods and caution against using passive spore traps to predict disease risks. In particular, the spore trap approach failed to capture: insect-vectored pathogens such as Ceratocystis destructans that were often recovered from almond trunk and scaffold; Diaporthe chamaeropis/rhusicola commonly isolated from wood samples likely because Diaporthe species have a spatially restricted dispersal mechanism, as spores are exuded in a cirrus; and pathogenic species with low incidence in wood samples such as P. richardsiae and Collophorina hispanica. We propose that orchard inoculum is composed of both endemic taxa that are characterized by frequent and repeated trapping events from the same trees and isolated from plant samples, as well as immigrant taxa characterized by rare trapping events. We hypothesize that host type, orchard age, precipitation, and alternative hosts at the periphery of orchards are factors that could affect pathogen profile. We discuss the limitations and benefits of our methodology and experimental design to develop guidelines and prediction tools for fungal wood canker diseases in California orchards.

Sensitivity of METRIC-based tree crop evapotranspiration estimation to meteorology, land surface parameters and domain size

Evapotranspiration (ET), a key component of crop water balance, is essential for growers to manage agricultural irrigation. METRIC model is increasingly used to estimate and map ET with satellite observations, especially at daily and field scales. However, the analysis of its uncertainties on tree crop ET estimation is very limited. We used METRIC model to estimate daily ET over the almond and pistachio orchards throughout the entire growing season in the San Joaquin Valley, California, and evaluated the impacts of variations in meteorological variables, land surface parameters and different study sizes on ET estimation. The results showed that the METRIC-based daily ET estimates of the almond and pistachio trees were most sensitive to net radiation (Rn), followed by instantaneous reference ET (ETo), land surface temperature (LST), and near-surface temperature difference (dT). When a 5% error was added to Rn, the uncertainty in daily ET estimates was up to 8.44 ± 1.24%, corresponding to a mean increase of 0.45 ± 0.02 mm/day throughout the entire growing season. A 5% or 0.5 K error in instantaneous ETo, LST, and dT also caused changes in daily ET estimates by 4.15 ± 3.75%, 2.97 ± 0.14%, and 2.31 ± 1.20%, respectively. ET estimates with METRIC were relatively much less sensitive to other variables. The results from different study sizes indicated that daily ET estimates in Size-2 were 0.33 ± 0.08 mm/day overestimation compared with those from Size-1 in the almond site. Similarly, a mean overestimation of 0.30 ± 0.14 mm/day was found between Size-1 and Size-3 in the pistachio sites throughout the entire growing season. This study demonstrates the potential to further improve the accuracy of remote sensing based ET estimation for complex tree crops with METRIC model, by optimizing key parameters and choosing a proper domain size for study area.

Perennial alley cropping contributes to decrease soil CO2 and N2O emissions and increase soil carbon sequestration in a Mediterranean almond orchard

The implementation of alley cropping in orchards can be a sustainable strategy to increase farm productivity by crop diversification and contribute to climate change mitigation. In this research, we evaluated the short-term effect of alley cropping with reduced tillage on soil CO2 and N2O emissions and soil total organic carbon (TOC) in an almond orchard under Mediterranean rainfed conditions. We compared an almond monoculture with tillage in all plot surface (MC) with almond crop with reduced tillage and growth of Capparis spinosa (D1) and almond crop with reduced tillage and growth of Thymus hyemalis (D2). For two years, soil CO2 and N2O were measured, with soil sampling at the start and end of the experimental period. Results showed that CO2 emission rates followed the soil temperature pattern, while N2O emissions were not correlated with temperature nor moisture. Soil CO2 emissions were significantly higher in MC (87 mg m−2 h−1), with no significant differences between D1 and D2 (69 mg m−2 h−1). Some peaks in CO2 effluxes were observed after tillage operations during warm days. Soil N2O emission rates were not significantly different among treatments. Cumulative CO2 and CO2 equivalent (CO2e) emissions were significantly highest in MC. When CO2e emissions were expressed on a crop production basis, D2 showed the significantly lowest values (5080 g kg−1) compared to D1 (50,419 g kg−1) and MC (87,836 g kg−1), owing to the high thyme yield, additional to the almond yield. No production was obtained for C. spinosa, since at least two more years are required. TOC did not change with time in MC neither D1, but it significantly increased in D2 from 3.85 g kg−1 in 2019 to 4.62 g kg−1 in 2021. Thus, alley cropping can contribute to increase the agroecosystem productivity and reduce CO2 emissions. However, it is necessary to grow evergreen alley crops such as thyme to obtain short-term increases in soil organic matter. Thus, to estimate increases in TOC with alley cropping, the plantation density and the period required by the crop to cover most of the surface are essential factors at planning the cropping strategy.

Perennial alley cropping contributes to decrease soil CO2 and N2O emissions and increase soil carbon sequestration in a Mediterranean almond orchard

Perennial alley cropping contributes to decrease soil CO2 and N2O emissions and increase soil carbon sequestration in a Mediterranean almond orchard

Effect of aggregation and disaggregation of land surface temperature imagery on evapotranspiration estimation

Understanding the spatial distribution of evapotranspiration (ET) and other surface energy fluxes in tree crops is vital for optimizing precision irrigation management practices. The land surface temperature (LST) is the primary input to estimate ET at field scale, but currently, available satellite data have a coarse resolution, which is not suitable for estimating ET at the required spatiotemporal scale at the field level. The development of unmanned aerial vehicles (UAVs) or airborne platforms during the last two decades has enabled the acquisition of LST and subsequent derivation of ET at the finer spatial resolution of up to a few centimeters due to the advances in low-weight thermal cameras onboard these platforms. In this study, the disaggregation methodology was applied to Landsat imagery based on aerial imagery collected at 0.5 m resolution over almond orchards in the Sacramento Valley of California, USA, to estimate ET at the orchard scale. The TsHARP algorithm was applied to sharpen the Landsat LST images (30 m spatial resolution) to target resolutions of 0.5, 10, 20 m. Also, the simple average aggregation technique was used to aggregate the aerial imagery (0.5 resolution) to 10, 20, and 30 m scales. Two Source Energy Balance (TSEB) model was used to estimate spatially distributed ET fluxes by combining the ground-based meteorological data for aggregated and disaggregated LST images. The estimated ET fluxes were compared to the measured eddy covariance fluxes, and then the aggregation and disaggregation processes were evaluated at 0.5, 10, 20, and 30 m spatial scales. At four spatial scales (0.5, 10, 20, and 30 m) aggregation and disaggregation derived ET values were highly correlated with the measured eddy covariance fluxes within the source footprint area. Furthermore, both aggregation and disaggregation approaches demonstrated similar ET spatial patterns within the study area, with slight variations observed under the Landsat 30 m resolution. The results indicated that TsHARP downscaled high-resolution imagery provides optimal spatial resolution for mapping and analyzing ET at the plant to orchard scale, with a 95% confidence interval and an RMSE of 0.43 mm/day. Overall, the results suggest that high spatial resolution imagery disaggregated from Landsat was the best alternative for estimating ET fluxes from the plant to the orchard scale, which is beneficial for precision irrigation management in orchards, but the framework can also be applied to other precision agriculture applications.

Evaluating the role of solar-induced fluorescence (SIF) and plant physiological traits for leaf nitrogen assessment in almond using airborne hyperspectral imagery

Accurate, spatially extensive, and frequent assessments of plant nitrogen (N) enabled by remote sensing allow growers to optimize fertilizer applications and reduce environmental impacts. Standard remote sensing methods for N assessment typically involve the use of chlorophyll-sensitive vegetation indices calculated from multispectral or hyperspectral reflectance data. However, the chlorophyll a + b derived from spectral indices is indirectly related to leaf N and saturates at high leaf N levels, dramatically reducing the sensitivity with leaf N under these conditions. Furthermore, these relationships are heavily influenced by canopy structure, variability in leaf area density, proportion of sunlit-shaded tree-crown components, soil background, and understory. Recent studies in uniform crops have demonstrated that estimation of plant N can be improved by considering leaf biochemical constituents derived from radiative transfer model (RTM) and solar-induced fluorescence (SIF). However, it is unclear whether these methods are transferable to tree crops due to their intrinsic physiological differences, structural complexity, and within-tree crown heterogeneity. We investigated how various hyperspectrally derived proxies for leaf N, including RTM-based traits and SIF, could be combined to assess N status on a 1200-ha almond orchard across two growing seasons. RTM-based chlorophyll a + b content (Cab) and SIF were found to be the most important and consistent predictors for leaf N compared to other leaf biochemical and biophysical traits. Cab alone was a modest predictor of leaf N variability (r2 = 0.49, RMSE = 0.16%, p-value <0.001), but when the non-collinear SIF and Cab traits were coupled together, predictions improved dramatically (r2 = 0.95, RMSE = 0.05%, p-value <0.001). Leaf area index (LAI) was poorly associated with leaf N, suggesting that leaf physiological traits may be more important than structural traits in quantifying leaf N in well-managed orchards characterized by high N levels. Consistent results across the 2 years suggests the importance of airborne SIF coupled with Cab for precision agriculture and leaf N status assessment in almond orchards.

Variety specific irrigation of almonds during hull split, effects on yield and quality

Regulated deficit irrigation (RDI) during hull-split can reduce water applied in almond orchards. Strategies for imposing RDI in almond orchards with multiple varieties with different hull-split schedules have not been extensively developed. Commonly, irrigation system design requires the same irrigation schedule for all varieties in the orchard. A 2-year study evaluated the impacts of two different regulated deficit irrigation strategies in an almond orchard with Butte, Aldrich, and Nonpareil varieties in the Sacramento Valley of California, USA. The two strategies were (1) RDI in all varieties during Nonpareil hull-split timing and (2) RDI according to variety-specific hull-split timing. The two levels of irrigation were 50 % and 75 % of potential crop evapotranspiration (ETc) replacement during the hull-split period. Results show that the kernel thickness of the Aldrich almonds increased under 75 % ETc irrigation replacement during the Aldrich hull-split period compared to 75 % ETc and 50 % ETc irrigation replacement during the Nonpareil hull-split period. In the Butte almonds, 75 % ETc and 50 % ETc irrigation replacement during variety-specific hull-split reduced the fraction of sealed shells of the Butte variety compared to 75 % ETc and 50 % ETc irrigation replacement during the Nonpareil hull-split period. This study demonstrated that an irrigation system design that allows for the independent irrigation scheduling of each variety can change the almond physical quality in the Butte and Aldrich varieties. RDI according to variety-specific hull-split did not result in significant marketable kernel yield improvements after two years of imposing the irrigation strategies. More research should be conducted for different orchard designs, varieties, and climates.

Trunk growth rate frequencies as water stress indicator in almond trees

The continuous monitoring of water stress will increase the accuracy of the deficit irrigation scheduling. Almonds are very sensitive to water stress conditions and an important water consumer. Recently, a novel approach to the use of trunk growth rate (TGR) data has been proposed for olive trees. These works suggested the use of TGR frequencies to evaluate water status of the trees. The aim of the current work was to compare the seasonal pattern of three different indicators derived from the daily curves of trunk diameter fluctuations with midday stem water potential. During three consecutive seasons (2017–2019), an irrigation experiment was carried out in a mature almond orchard (cv Vairo) at Dos Hermanas (Seville, Spain). Four irrigation treatments replicated in four blocks were evaluated using the daily curves of midday stem water potential and trunk diameter fluctuations. The different irrigation treatments were: Control, full irrigated conditions; RDI-1 (irrigation scheduling based on midday stem water potential with a deficit irrigation during kernel filling [values around −1.2 MPa]); RDI-2(similar to RDI-1 but with a more severe water stress [−2 MPa]) and incomplete recovery after harvest due to limitation of the seasonal amount of water (around 100 mm); SDI, sustained deficit irrigation with a seasonal applied water equal to RDI-2. Trunk diameter fluctuations were measured with a wireless band dendrometer. The daily curves were processed to obtain three different indicators. Maximum daily shrinkage (MDS) was the difference between the daily maximum and minimum. Trunk growth rate (TGR) was the difference between two consecutive daily maximums. The frequencies of several ranges of TGR were compared with the midday stem water potential. Weekly frequencies of values greater than 0.3 mm day−1 decreased with the reduction of midday stem water potential, but the pattern changed greatly in different seasons. The weekly frequency of values between − 0.1 and 0 and between 0 and 0.1 mm day−1 were steadier in different seasons. Differences between seasons were related to growth pattern and yield.

Evaluation of Fungicides and Application Strategies for the Management of the Red Leaf Blotch Disease of Almond

Red leaf blotch (RLB) of almond, caused by Polystigma amygdalinum, is an important foliar disease of this nut tree in the Mediterranean basin and especially in Spain. In recent years, the control of this disease has become a key factor in the management of Spanish almond orchards. The management of RLB is not easy due to intrinsic factors of the disease (e.g., long infection and latency periods) and the low number of registered fungicides in this country. From 2015 to 2019, different field trials were conducted in the Lleida region, NE Spain, to evaluate the efficacy of several fungicide products and of application strategies to control this disease. Systemic fungicides, which included fluopyram, trifloxystrobin, and mixtures of fluopyram + trifloxystrobin and pyraclostrobin + boscalid, performed better than contact and penetrant products and showed up to 90% control against RLB. However, the efficacy of the tested fungicides varied depending on the year. In terms of application strategies, when fungicide applications were conducted following specific meteorological conditions (after 15 days from &gt;15 mm rainfalls with ≈10–15 °C as the minimum average temperature), their efficacy was comparable to that of calendar-based treatments (every 14, 21, or 31 days from petal fall) but with fewer applications (depending on the year, 2–4 applications as compared with 5–9 for calendar treatments).

Estimation of turbulent fluxes over almond orchards using high-resolution aerial imagery with one and two-source energy balance models

Estimation of actual crop evapotranspiration (ETc) using high-resolution aerial remote sensing data is important to detect water stress, map, and manage water resources in precision agriculture. High-resolution ETc can be estimated using land surface energy balance models and remotely sensed land surface temperatures (LST) obtained using manned or unmanned aerial vehicles equipped with thermal cameras. In this study, three remote sensing ETc models were compared, i.e., Two-Source Energy Balance (TSEB) model, Mapping Evapotranspiration with Internalized Calibration (METRIC), and Surface Energy Balance Algorithm for Land (SEBAL) models. Thermal images were obtained using an airplane flying daily over almond orchards in California during the 2020 growing season. The LST images were obtained at 0.5 m spatial resolution. Model comparisons indicated that all three models produced latent heat fluxes and net radiation estimates that agreed with eddy covariance measurements in the order of TSEB (R2 of 0.89 for LE and 0.88 for Rn), METRIC (R2 of 0.81 for LE and 0.86 for Rn), and SEBAL (R2 of 0.81 for LE and 0.83 for Rn). However, METRIC and SEBAL overestimated the latent heat fluxes while underestimating the sensible heat fluxes as compared to the two-source model (TSEB). The root mean square error (RMSE) of the instantaneous latent and sensible heat fluxes were less than 38 W m−2 for TSEB, and were within 58 W m−2 for METRIC and SEBAL models. The TSEB model’s good performance can be attributed to its partitioning of surface temperature between soil, crop cover in the inter rows, and almond tree canopies. Overall, the results suggest that both one and two-source surface energy models originally developed for satellite imagery are able to estimate instantaneous turbulent fluxes and spatial variability in ETc using high-resolution imagery. In addition, systematic variations in LST due to variable rate irrigation scheduling as depicted in the high spatial resolution imagery provided confidence in the spatially distributed latent heat flux maps estimated by the energy balance models. This study shows that high-resolution aerial imagery combined with energy balance models originally developed for satellite remote sensing can be used to accurately estimate site specific ETc that is critical to achieving precision irrigation management in almond orchards and other crops.

Correction: Montesinos et al. Phenotyping Almond Orchards for Architectural Traits Influenced by Rootstock Choice. Horticulturae 2021, 7, 159

In the original publication [...]

Unravelling soil water dynamics in almond orchards characterized by soil-heterogeneity using electrical resistivity tomography

Characterizing soil heterogeneity helps to improve the management of the natural resources (mainly water, nutrients and soil itself) at the farm level and enhances crop growth and relative yield sustainability. In this context, the geophysical monitoring based on direct current methods (such as the Electrical Resistivity Tomography, ERT) can help to detect the soil heterogeneity by exploring the soil water variability. ERT time-lapse surveys were carried out in almond orchards characterized by different soil types in terms of structure (i.e. layered, light and heavy soil profiles) and texture features (i.e. prevalently clay loam versus sandy clay loam). Specifically, two-dimensional ERT surveys were combined with the monitoring of multiple soil-plant-atmosphere factors, including the components of the surface energy balance using an eddy covariance system, the soil moisture and the plant water status measured using a neutron probe and pressure chamber measurements, respectively. The interpretation of the ERT results together with the ancillary data has provided spatially and temporally distributed information about the soil water processes that occurred within the almond root-zone during irrigation, allowing us to identify where the most root-water uptake occurs and the delineation of the irrigation wet bulbs under micro-irrigations conditions.

Crop coefficients and water use of young almond orchards

An observational study was conducted in the northern Sacramento Valley in California, United States to determine crop water use and crop coefficients of three adjacent young Nonpareil/Monterey almond orchards. Methods used to quantify evapotranspiration estimates of crop water use include (1) a soil water balance and (2) a land surface energy balance using eddy covariance. Three adjacent almond orchards that were planted in 2016, 2017, and 2018 were monitored from 2018 to 2020. Actual crop coefficients were determined using actual evapotranspiration estimates from each orchard and short grass reference evapotranspiration from the Gerber South California Irrigation Management Information System station. Results showed that crop water use and crop coefficients increased until the 4th year, indicating the need to closely consider tree development and orchard age as factors in irrigation scheduling of young almond trees. The results led to the conclusion that farmers should use development or age-specific crop coefficients in developing orchards for irrigation scheduling until the 4th year when they can start using mature almond crop coefficients. The mid-season actual crop coefficients were 0.35, 0.55, 0.88, 1.04, and 0.99 for 1-, 2-, 3-, 4-, and 5-year-old almond orchards. This study has generated baseline data on crop water requirements of young almond orchards that could be useful for (1) developing irrigation scheduling tools for young almond orchards, and (2) determining water budgets for areas with new almond orchards.

Impacts of winter cover cropping on soil moisture and evapotranspiration in California's specialty crop fields may be minimal during winter months

As fresh water supplies become more unreliable, variable and expensive, the water-related implications of sustainable agriculture practices such as cover cropping are drawing increasing attention from California's agricultural communities. However, the adoption of winter cover cropping remains limited among specialty crop growers who face uncertainty regarding the water use of this practice. To investigate how winter cover crops affect soil water and evapotranspiration on farm fields, we studied three systems that span climatic and farming conditions in California's Central Valley: processing tomato fields with cover crop, almond orchards with cover crop, and almond orchards with native vegetation. From 2016 to 2019, we collected soil moisture data (3 years of neutron hydroprobe and gravimetric tests at 10 field sites) and evapotranspiration measurements (2 years at two of 10 sites) in winter cover cropped and control (clean-cultivated, bare ground) plots during winter months. Generally, there were not significant differences in soil moisture between cover cropped and control fields throughout or at the end of the winter seasons, while evapo-transpirative losses due to winter cover crops were negligible relative to clean-cultivated soil. Our results suggest that winter cover crops in the Central Valley may break even in terms of actual consumptive water use. California growers of high-value specialty crops can likely adopt winter cover cropping without altering their irrigation plans and management practices.

ADIYAMAN İLİNDE BADEM ÜRETİMİNİN MALİYET VE KARLILIK ANALİZİ

According to the statistics of 2020, 150,000 tons of almonds are produced in Turkey. When the production amount of total almond production is examined according to the provinces, Mersin ranks first with 22,929 tons, Adıyaman ranks second with 15,470 tons, while Muğla takes third place with 9,955 tons of almond production. It is understood that there has been a great increase in almond production areas in the province of Adıyaman in recent years, and considering the data for 2020, Turkey has the largest almond production area with 72,350 decares of almond production area. This situation will be reflected in the production amount soon. In this study, it is aimed to reveal the almond production potential of the city by determining the almond production costs and profitability in Adıyaman, which is on the way to becoming the almond city of Turkey. For this purpose cost and profitability analyzes of almond orchard investments in the study area were made. As a result of these analyzes, it has been seen that the benefit/cost ratio of the garden facilities in the region is 1.70. In addition, it was concluded that the internal rate of return was 28.74%, well above the cost of capital (13.50%). As a result of net present value (NPV), internal rate of return (IRR), and cost-benefit analysis (CBA), it has been revealed that almond production is very profitable for the producers of the region and these investments will make positive contributions to the regional economy. It is considered that carrying out activities that increase the efficiency and profitability of almond production in the region (promotion, brandization, information, agricultural support) may contribute to the sustainability of production.

Prediction of Almond Nut Yield and Its Greenhouse Gases Emission Using Different Methodologies

The evaluation of a production system to analyze greenhouse gases is one of the most interesting challenges for researchers. The aim of the present study is to model almond nut production based on inputs by employing artificial neural networks (ANNs) and adaptive neuro-fuzzy inference systems (ANFIS) procedures. To predict the almond nut yield with respect to the energy inputs, several ANN and ANFIS models were developed, evaluated, and compared. Among the several developed ANNs, a network with an architecture of 8-12-1 and a log-sigmoid, and a linear transfer function in the hidden and output layers, respectively, is found to be the best model. In general, both approaches had a good capability for predicting the nut yield. The comparison results revealed that the ANN procedure could predict the nut yield more precisely than the ANFIS models. Furthermore, greenhouse gas (GHG) emissions in almond orchards are determined where the total GHG emission is estimated to be about 2348.85 kg CO2eq ha−1. Among the inputs, electricity had the largest contribution to GHG emissions, with a share of 72.32%.

PEST RISK ANALYSIS IN COMSTOCK MEALYBUG (PSEUDOCOCCUS COMSTOCKI) IN POMEGRANATE AND DATES

Dangerous pest is widespread in Uzbekistan. The most dangerous of these are coccidia. They damage many plants. Damages pomegranate, date, unabi, apple, pear, plum, quince, peach, almond, hawthorn, pine, poplar and other orchards and ornamental trees. In Uzbekistan, comstock worms reproduce three times a year, and partly for the fourth time. But with the fall of the cold, the fourth generation perishes. In pomegranate and palm crops, different levels of infestation were observed in different varieties by comstock worms. In pomegranate, 53.8% of Ok dona, 49.5% of Kizil anor, 39.1% of Kozoki anor and 22.8% of Achchik dona were damaged. 38.3% of Zenju-maru, 25.9% Tamopan and 20.1% Xiakume dates were damaged.