Net Crop Research Articles

The Potential Impact of Climate Extremes on Cotton and Wheat Crops in Southern Punjab, Pakistan

The assessment of climate extremes’ impact on crop yield is essential to improve our understanding of agricultural resilience. In the present study, we analyzed the potential impact of climate extremes on wheat and cotton production in Southern Punjab, Pakistan using 30-year observed data from the Pakistan Meteorological Department (PMD) and the fifth-generation reanalysis data (ERA-5) from the European Center for Medium-Range Weather Forecasts (ECMWF). Cotton is a Kharif season crop that is sown in May and harvested in October, and wheat is a Rabi season crop that is planted in November and harvested in April. The agricultural data (1985–2015) that contained the crop area and crop yield were obtained from the Bureau of Statistics, Punjab for six selected districts in Southern Punjab. Three precipitation indices, namely consecutive dry days (CDD), consecutive wet days (CWD) and total precipitation of wet days (PRCPTOT), and four temperature indices, namely warm days (TX90p), warm nights (TN90p), cool days (TX10p) and cool nights (TN10p), were selected to analyze the potential impacts of climate extremes on crop production. (1) We found a potential association of TX10p, TN10p, TX90p and TN90p with crop yield in those years for which the production area remained the same. (2) In a few districts of the study area, the wheat yield losses in the Rabi season were associated with an increase in warmer days and warmer nights. (3) The grain size was suppressed due to an increase in the frequency of TX90p and TN90p, which ultimately reduced the net crop production. (4) In some districts, we found strong positive correlations between extreme temperature indices and crop yield; however, other potential factors such as the use of advanced technology, fertilizer, seeds, etc., may lead to improved net production. This study can help in adaptation planning for resilient agricultural production under the stress of climate extreme events in Southern Punjab.

Determining Economical Irrigation Depths in a Sandy Field Using a Combination of Weather Forecast and Numerical Simulation

Advancement of modern technologies has given numerical simulations a crucial role to effectively manage irrigation. A new numerical scheme to determine irrigation depths was incorporated into WASH 2D, which is a numerical simulation model of crop response to irrigation. Based on two predicted points of cumulative transpiration—water price and quantitative weather forecast—the scheme can optimize an irrigation depth in which net income is maximized. A field experiment was carried out at the Arid Land Research Center, Tottori, Japan, in 2019, to evaluate the effectiveness of the scheme on net income and crop production compared to a tensiometer-based automated irrigation system. Sweetcorn (Zea mays L., Amaenbou 86) was grown in three water balance lysimeters per each treatment, filled with sandy soil. The scheme could achieve a 4% higher net income, due to a 7% increase in green fodder yield, and an 11% reduction in irrigation amount, compared with the automated irrigation method. These results indicate that the numerical scheme, in combination with quantitative weather forecasts, can be a useful tool to determine irrigation depths, maximize net incomes which are farmers’ targets, and avoid large investments that are required for the automated irrigation system.

RESPON PERTUMBUHAN DAN HASIL TANAMAN KAILAN TERHADAP PEMBERIAN KAPUR DOLOMIT DAN PUPUK BOKASHI KOTORAN SAPI DI TANAH GAMBUT

The study aimed to determine the response of growth and yield of kailan on the interaction effect of a dolomite lime with bokashi of cow manure and its single factor effect. The experiment was conducted in Completely Randomized Design (CRD) with two factors in three replications. The first factor was dolomite lime which consists of 2 t ha-1 (k1), 5 t ha-1 (k2), 10 t ha-1 (k3) and 15 t ha-1 (k4), while the second factor was bokashi of cow manure consisting of 0 t ha-1 (b0), 10 t ha-1 (b1), 15 t ha-1 (b2), and 20 t ha-1 (b3). By observing growth components consisting of relatif growth rate (RGR), crop growth rate (CGR), net assimilation rate (NAR), shoot/root ratio (S/R), and crop yield. As well as the components of soil nutrient content of N, P, K, C-organic content, pH and cation exchange capacity (CEC). The results showed that the application of dolomite lime at a dose of 15 t ha-1 with bokashi fertilizer at a dose of 20 t ha-1 give the highest value of crop growth rate (CGR), net assimilation rate (NAR), shoot/root ratio (S/R), C-organic content, phosphorus (P), and Potassium in peat soil. The application of bokashi fertilizer at a dose of 15 t ha-1 was not different with 20 t ha-1 in terms of relatif growth rate (RGR), crop yield and cation exchange capacity (CEC), and respectively higher than the dose of 10 t ha-1 and without bokashi fertilizer. The application of dolomite lime at a dose of 10 t ha-1 was not different with 15 t ha-1 on the relative growth rate (RGR), and pH of peat soil, and each dose was higher than the doses of 5 t ha-1 and 2 t ha-1 . In terms of nitrogen (N) content, the application of dolomite lime at a dose of 5 t ha-1 was not different with the dose of 10 t ha-1 , and 15 t ha-1 , the N content was higher than the dose of 2 t ha-1 . The increase in the dose of dolomite lime at 20 t ha-1 of bokashi fertilizer showed a positive linier correlation, except for the Potassium which showed a quadratic correlation. The increase dose of dolomite lime in the bokashi fertilizer, the plant growth rate (PAR), net assimilation rate (NAR), shoot/root ratio (S/R), C-organic content, and phosphorus (P) would increase as well. Each single factor of the dose of dolomite lime and bokashi fertilizer showed a positive linier relationship to the relatif growth rate (RGR), crop yield, N-total, pH, and cation exchange capacity (CEC) of peat soil, except for N-total and pH in bokashi fertilizer.

Government Policy and Performance of Agricultural Cooperatives: A Case Study in Chitwan District, Nepal

Agricultural cooperatives are producer-owned and controlled organizations to improve farmers’ livelihoods by correcting market failure. They support collective activities where individual incentives are insufficient to produce public goods. The government of Nepal has been investing economic resources in this sector, prioritizing cooperatives as part of a strategy for poverty reduction. This study examines poor farmers’ access to agricultural cooperatives and the impact of membership on farm and total household income, based on a household survey of 572 households and key informant interviews of 37 cooperative managers. The ethnicity of the family and the neighborhood, smallholder land size, distance to an agricultural cooperative, distance to the nearest local market, and distance to a motorable road are key determinants that influence cooperative membership. The analysis of the effects of cooperative membership is based on propensity score matching, controlling for a large array of household and community characteristics. The estimates imply that cooperative membership may significantly affect family net crop income, but the overall effects on total family income are modest. Agricultural cooperatives appear to be focused on financial services such as savings and credit activities but are less concerned with agricultural production, and cooperatives engage in almost no marketing activities.

Effect of Phosphate Fertilization and Iron Spraying on Growth Parameter and Yield of Oat (Avena Sativa L.)

A field experiment was conducted during the agricultural season 2020-2021 at the Agricultural Research Station/College of Agriculture/University of Basra (Al-Haritha site) (20 km from the center of Basra Governorate). To study the effect of four levels of phosphate fertilizer (P0=0, P1=50, P2=100 and P3=150 Kg ha-1) and four concentrations of iron spray(F0=0, F1=1000, F2=2000 and F3=3000 PPM). on the growth, yield and quality of oats (Avena sativa L.) Janzania cultivar the experiment was carried out in a split-plot arrangementusinga randomized complete block design (RCBD) with three replications. Phosphate fertilizer levels occupied the main plot, and iron concentrations occupied the sub-plots. The results showed that the P3 level was significantly superior in all the studied traits, which gave the highest grain yield of 6.13 mcg ha-0. The concentration F2 was significantly superior in all the studied traits, which gave the highest grain yield of 5.29 mcg ha-0. The interaction also showed the superiority of the combination P3*F2 in plant height, flag leaf area, number of branches and grain yield, while the interaction was not significant in the trait of leaf area index and Net Assimilation rate and crop growth rate

Effect of Intercropping Between Garlic and Faba Bean on Yield and Infestation by Some Piercing-Sucking Insect Pests

Faba bean is an important food crop in Egypt, with seeds of 22 % protein. In addition, it is considered a land reclaiming crop, as it enriches the soil with some nitrogen fertilizer. The current study was conducted at the experimental farm of Sakha Agricultural Research station to manage some piercing-sucking insects with unconventional methods. Garlic was intercropped with faba bean to find the repellent effect of garlic, as a volatile crop, against the abovementioned insects. The solid faba bean gave the highest values of faba bean yield, number of branches, pods and seeds per plant, as well as number of seeds / pod, 100-seed weight and protein content. On the other hand, these values, except plant height, were higher in case of intercropping faba bean with Balady garlic compared to Sids-40 garlic. Concerning garlic yield attributes, Balady garlic intercropped with faba bean produced higher values of bulb diameter and bulb weight / plant, as well as number of cloves per bulb and clove weight compared to Sids-40 garlic. In 2018 / 19 season, the population density of Aphis craccivora was reduced by 55.66 and 32.47 % due to intercropping between faba bean and Balady garlic or Sids-40 garlic, respectively. Empoasca lybica population was reduced by 54.67 and 35.72%, and that of Bemisia tabaci was 59.92 and 35.26 %. Similar results were obtained in 2019/20 season. The current results show that intercropping between faba bean and garlic enhanced the total net crop income, and helped in managing these insects.

A multi-objective algorithm for crop pattern optimization in agriculture

The crop growth and crop yield in agriculture depend upon many factors such as weather conditions, soil type, and application of fertilizers. The crop net return can be increased by deciding suitable crops for a particular land depending upon its weather conditions. The application of an appropriate amount of fertilizers also promotes crop growth and yield. On the other hand, the use of fertilizers needs to be minimized to reduce the capital cost as well as to prevent its harmful effect on soil and the environment. This paper models the problem of increasing net crop benefit and reducing the application of fertilizers as multi-objective optimization functions. A hybrid CSA-PSO optimization algorithm is proposed for solving multi-objective problems by combining crow search algorithm (CSA) and particle swarm optimization (PSO). The performance of the proposed algorithm is evaluated against CEC 2009 benchmark functions. This algorithm is implemented for crop pattern optimization in India’s Telangana state, which depicts the proposed algorithm’s feasibility and effectiveness.

The Effects of Tunnel Technology on Crop Productivity and Livelihood of Smallholder Farmers in Nepal

Technologies-based production practices are critical for agricultural growth and sustainable development in low-income countries like Nepal. In the last few years, tunnel house has been increasingly promoted as tools to enhance smallholder farmers’ livelihood and tackle climate adversaries. However, little is known about what factor determines its adoption and whether it helps smallholders adapt to climate change and experience better livelihood. We address these gaps using the cross-sectional survey data collected from 62 adopters and 92 non-adopters in three municipalities of Bagmati Province. We employed descriptive analysis and probit model and found out that age, farm size, and ethnicity strongly influence the technology adoption amongst smallholder farmers. Additionally, treatment model and ordinary least square (OLS) regression were utilized to examine tunnel technology’s effect. Our study shows that tunnel significantly increases production by 32 tons/year/hectare and protects crops from climate change effects such as heavy rainfall and temperature change. Likewise, tunnel technology increases the net crop income by $1700/year/hectare. However, the economic benefit is not substantial compared to technology’s adoption cost as adopters incur enormous costs of $12,000/year/hectare on equipment, labor and resources. These results suggest policymakers should concentrate on reducing the technology’s cost, which could be achieved through subsidies, financial support, or price control mechanisms. Ensuring technology’s affordability can contribute to smallholder farmers’ sustainable livelihood in Nepal and countries with similar contexts.

Examining the Economic Impacts of Climate Change on Net Crop Income in the Ethiopian Nile Basin: A Ricardian Fixed Effect Approach

Climate change affects crop production by distorting the indestructible productive power of the land. The objective of this study is to examine the economic impacts of climate change on net crop income in Nile Basin Ethiopia using a Ricardian fixed effect approach employing the International Food Policy Research Institute (IFPRI) household survey data for Ethiopia in 2015 and 2016. The survey samples were obtained through a three-stage stratified sampling technique from the five regions (Amhara, Tigray, Benishangul Gumuz, Oromia, and Southern Nation Nationality and People (SNNP) along the Nile basin Ethiopia. There are only 12–14% female household heads while there are 80–86% male households in the regions under study. In the regions, more than half of (64%) the household heads are illiterate and almost only one-tenth of them (12%) had received remittance from abroad from their relatives or children. Crop variety adoption rate is minimal, adopted by the 31% of farmers. Only 30% of the surveyed farmers mentioned that they planted their crop seeds in row whereas the rest 70% had not applied this method. The regression results from the fixed effect least square dummy variable model showed that literacy, household size, remittance, asset value, and total land holdings have significant and positive impacts on the net crop income per hectare. The regional dummy variables estimate indicated that all the regions are negatively affected by climate change at varying levels. Strategies to climate change adaptation have significant and positive contributions in leveraging the damaging effects of climate change. The results also showed that increased winter and summer temperature and rainfall increase net crop income per hectare. The estimated coefficient of the interaction term of spring temperature and rainfall is significant and negative. On the other hand, while the mean annual temperature is damaging to crops, annual rainfall is beneficial. It can be deduced that, while increased temperature and rainfall in summer and winter increase the net crop income, the converse is true for winter and spring seasons. The study also proposes a specific, context-dependent, farm-level adaptation analysis of how farmers cope with the different climatic impacts of the Nile Basin and maintain the income levels that they have previously enjoyed.

Effects of legume intercropping and nitrogen input on net greenhouse gas balances, intensity, carbon footprint and crop productivity in sweet maize cropland in South China

How to achieve greater crop productivity with lower greenhouse gas (GHG) emissions from limited farmland has been a hotspot of interest in global agricultural production. In this study, we analyzed the effects of legume intercropping and nitrogen (N) fertilizer level on net greenhouse gas balances (NGHGB), yield-based greenhouse gas emissions intensity (GHGI), carbon footprint (CF) and crop productivity in sweet maize cropland in South China based on a long-term field experiment during 2013–2018. Results demonstrated that the sweet maize/soybean intercropping pattern could improve crop productivity on the unit of arable land, but the yield advantage of the intercropping system was totally derived from the soybean. Accordingly, the intercropping pattern reduced the GHGI with significant difference compared to the sweet maize mono-cropping system. Therein, the difference between the sweet maize/soybean intercropping with crop line ratios of 2:3 (S2B3) and 2:4 (S2B4) were not significant. Furthermore, suitable N input during the sweet maize cultivation in the region were necessary for improving the crop productivity and decreasing the GHGs emission in farmland. Also, the difference of N levels was significant to the GHGs emissions, soil organic carbon sequestration, GHGI and NGHGB. The 300 kg N ha−1 showed the better effect for lowering the NGHGB and CF in sweet maize farmland when keeping crop productivity. The interaction effect of the N level and crop pattern just showed on the crop yields and GHGI. The S2B4 with 300 kg N ha−1 showed significant benefits with respect to maintaining the yields and reducing the net GHGs emissions compared to conventional sweet maize farming system in the Pearl River Delta in China. These advanced agricultural practices contributed to the development of clean agricultural production in China.

Valuation of Cropland Ecosystem Products of Smallholder Farm Households in Hare River Catchment, Southern Ethiopia

The crop production value of nature has to be boldly appreciated in Ethiopia where agriculture is the main livelihood source of most people. However, studies aimed at estimating cropland services were rare in Ethiopia and Hare Catchment. Thus, the objective of this study was to estimate the crop production value of the nature of smallholder farmers of Hare Catchment, Southern Ethiopia. The study applied a quantitative approach and survey design. Data was collected using a questionnaire of 465 households (identified via systematic random sampling) and interviews. Mean, t-test, analysis of variance, and linear regression were used for data analyses. The average net crop production value of nature in the lower, middle and the upper catchment of Hare was US$ 907.3, 455.1, and US$ 512.3 per household/year, respectively. The average production (20.4 quintals) and gross value (US$ 704.8) per/household/year of Hare catchment revealed significant variation among households based on the difference in gender, farm size, labor, and fertilizer used for farming at a 99% confidence level. 78.2% of the crop production variation among farmers was significantly predicted by farm size, labor, seedling, fertilizer, and seed used for farming. The average annual net crop harvest value (US$ 643) of nature was 91.2% of the average revenue (US$ 704.8) from cropland products of Hare. While farm size was the strongest predictor of crop production variation in the lower Hare, labor was the strongest predictor of its variation in the middle and the upper catchment. Thus, government bodies and farmers should take integrated actions to tackle the yield bottle-necks of croplands in Hare Catchment, Southern Ethiopia.

Diverging land-use projections cause large variability in their impacts on ecosystems and related indicators for ecosystem services

Abstract. Land-use models and integrated assessment models provide scenarios of land-use and land-cover (LULC) changes following pathways or storylines related to different socioeconomic and environmental developments. The large diversity of available scenario projections leads to a recognizable variability in impacts on land ecosystems and the levels of services provided. We evaluated 16 projections of future LULC until 2040 that reflected different assumptions regarding socioeconomic demands and modeling protocols. By using these LULC projections in a state-of-the-art dynamic global vegetation model, we simulated their effect on selected ecosystem service indicators related to ecosystem productivity and carbon sequestration potential, agricultural production and the water cycle. We found that although a common trend for agricultural expansion exists across the scenarios, where and how particular LULC changes are realized differs widely across models and scenarios. They are linked to model-specific considerations of some demands over others and their respective translation into LULC changes and also reflect the simplified or missing representation of processes related to land dynamics or other influencing factors (e.g., trade, climate change). As a result, some scenarios show questionable and possibly unrealistic features in their LULC allocations, including highly regionalized LULC changes with rates of conversion that are contrary to or exceed rates observed in the past. Across the diverging LULC projections, we identified positive global trends of net primary productivity (+10.2 % ± 1.4 %), vegetation carbon (+9.2 % ± 4.1 %), crop production (+31.2 % ± 12.2 %) and water runoff (+9.3 % ± 1.7 %), and a negative trend of soil and litter carbon stocks (−0.5 % ± 0.4 %). The variability in ecosystem service indicators across scenarios was especially high for vegetation carbon stocks and crop production. Regionally, variability was highest in tropical forest regions, especially at current forest boundaries, because of intense and strongly diverging LULC change projections in combination with high vegetation productivity dampening or amplifying the effects of climatic change. Our results emphasize that information on future changes in ecosystem functioning and the related ecosystem service indicators should be seen in light of the variability originating from diverging projections of LULC. This is necessary to allow for adequate policy support towards sustainable transformations.

Does Minimum Tillage Improve Smallholder Farmers' Welfare? Evidence from Southern Tanzania

This study evaluated the welfare effects of minimum tillage among smallholder households in Southern Tanzania. A propensity score matching technique was employed to assess the causal impact of adopting minimum tillage using data from a random sample of 608 households. Results indicated that minimum tillage adoption is influenced by gender of the household head, asset index, training on personal values, drought experience, farmer organization and access to NGO information. Minimum tillage also impacts positively on smallholder households' per capita net crop income with the algorithms ranging between 162,430 – 192,208 Tanzania shillings. Further, it reduces the total household labor demands allowing the households to engage in other income-generating activities with an average of -15.67 labor per man-days. Based on this, the authors recommend supporting households to use complementary farm inputs, credit access, and extension-specific information to improve the intensity of adopting minimum tillage.

Effects of chemical mutagens on the physio-chemical traits of Tomato (Lycopersicon esculentum)

A field experiment was conducted at the Horticultural Research station, Odisha University of Agriculture and Technology, Bhubaneswar, Odisha during Rabi 2017 and 2018 seasons. Five hundred seeds of variety Utkal Kumari (BT 10) were taken and subjected to single and combined mutagenic treatment as per the specification. The experiment was laid down in Randomised Block Design (RBD) with three replications. Leaf area (dm2/plant), total dry matter and chlorophyll content were measured at 30, 60 and 75 days after transplanting(DAT). NAR (Net assimilation rate) and CGR (Crop growth rate) were also calculated at 30-40 DAT and 50-60 DAT. All the treatments showed increase in yield over control and buffer except in treatment Sodium Azide (SA) 0.06% which indicated that the mutagens had positive effect on the plant for increasing yield. The increase in yield depends on leaf area or photosynthesizing tissues, total respiring tissues or total biomass, photosynthetic efficiency as reflected by chlorophyll content, Net assimilation rate (NAR) and crop growth rate (CGR). Ethyl methane sulphate (EMS) at 0.6% concentration had shown maximum increase in yield which was attributed to maximum leaf area (55.19 dm2/plant), maximum total dry matter (19.44g/plant) and maximum crop growth rate (0.347g.m−2.day−1). The chlorophyll content and NAR (Net assimilation rate) were also significantly high for this treatment.

Does Minimum Tillage Improve Smallholder Farmers’ Welfare? Evidence from Southern Tanzania

Conservation agriculture continues to be promoted in developing nations as a sustainable and suitable agricultural practice to enhance smallholder productivity. A look at the literature indicates that this practice is successful in non-African countries. Thus, this research sought to test whether minimum tillage (MT), a subset of conservation agriculture, could lead to a significant impact on smallholder households’ welfare in Southern Tanzania. Using cross-sectional data from 608 randomly selected smallholder households, we applied propensity score matching to determine the effects of adopting minimum tillage on smallholder households’ per capita net crop income and labor demand. Our results indicated that minimum tillage adoption has positive impacts on smallholder households’ per capita net crop income. Further, it reduces the total household labor demands, allowing households to engage in other income-generating activities. However, the adoption rate of minimum tillage is in the early majority stage (21.38%). Thus, we propose the government to support household credit access and extension-specific information to improve the probability of adopting minimum tillage.

Assessment of the potential of rainwater harvesting for maize production in the Lubombo plateau

Eswatini has persistently experienced below average and dwindling maize production chiefly due to low rainfall characterized by erratic patterns. The objective of the study was to assess the potential of rainwater harvesting for rain-fed maize production in the Lubombo plateau. Rainy season characterization, determination of maize crop net irrigation requirements, and assessment of runoff potential and identification of suitable rainwater harvesting sites were carried out to achieve the objective of the study. Rainy season characterization was carried out in INSTAT Plus Statistical software. The net crop irrigation requirement was calculated using CROPWAT 8.0 while the ArcCN-Runoff tool was used to estimate the potential runoff volume generated in the study area. Multi-layer merging of rainfall, slope, soil texture and land use layers was performed in GIS environment to locate potential rainwater harvesting sites. The study revealed that the probabilities of prolonged dry spells are relatively higher during the maize growing season. Nearly 60% of the catchment's area was found to be suitable for rain water harvesting. Through harvesting runoff generated in croplands, the study established that 45% of the crop water requirement deficit could be met. This shows that there is high potential for rainwater harvesting and subsequent use of harvested water to stabilize maize yield in the Lubombo Plateau. These findings can facilitate better planning for rain-fed agriculture in Eswatini while minimizing related climate risks. This study also managed to bridge the literature gap in viability of rainwater harvesting for rain-fed agriculture in the country.

Exogenous Cry1Ab/c Protein Recruits Different Endogenous Proteins for Its Function in Plant Growth and Development.

Current risk assessments of transgenic crops do not take into consideration whether exogenous proteins interact with endogenous proteins and thereby induce unintended effects in the crops. Therefore, the unintended effects through protein interactions in insect-resistant transgenic rice merit investigation. Here, a yeast two-hybrid assay was used to evaluate interactions between Bacillus thuringiensis (Bt) protein-derived Cry1Ab/c insect resistance rice Huahui-1 and the endogenous proteins of its parental rice Minghui-63. The authenticity of the strongest interactions of Cry1Ab/c and 14 endogenous proteins involved in photosynthesis and stress resistance, which may be primarily responsible for the significant phenotypic differences between transgenic Huahui-1 and parental Minghui-63, were then analyzed and validated by subcellular co-localization, bimolecular fluorescence complementation and co-immunoprecipitation. As the exogenous full-length Cry1Ab/c protein was found to have self-activating activity, we cleaved it - into three segments based on its three domains, and these were screened for interaction with host proteins using the yeast two-hybrid assay. Sixty endogenous proteins related to the regulation of photosynthesis, stress tolerance, and substance metabolism were found to interact with the Cry1Ab/c protein. The results of bimolecular fluorescence complementation and co-immunoprecipitation verified the interactions between the full-length Cry1Ab/c protein and 12 endogenous proteins involved in photosynthesis 23KD, G, PSBP, Rubisco, Trx, THF1 and stress resistance CAMTAs, DAHP, E3s, HKMTs, KIN13A, FREE1. We used a combination of yeast two-hybrid, bimolecular fluorescence complementation, and co-immunoprecipitation to identify Cry1Ab/c interacting with rice proteins that seem to be associated with the observed unintended effects on photosynthesis and stress resistance between Huahui-1 and Minghui-63 rice plants, and analyze the possible interaction mechanisms by comparing differences in cell localization and interaction sites between these interactions. The results herein provide a molecular analytical system to qualify and quantify the interactions between exogenous proteins and the endogenous proteins of the recipient crop. It could help elucidate both the positive and negative effects of creating transgenic plants and predict their potential risks as well as net crop quality and yield.

Optimization of the land use pattern in Horqin Sandy Land by using the CLUMondo model and Bayesian belief network

Land use and cover change is an important concept in the study of ecosystem services, especially in ecologically fragile areas. This study generated three scenarios, namely historical trend (HT), national planning (NP), and windbreak and sand fixation (WS), by using the CLUMondo model and Bayesian belief network (BBN) to explore land use with diverse demands. The CLUMondo model was utilized to simulate the land use probability surface of Horqin Sandy Land in 2025 under different scenarios. A BBN was constructed to investigate the net primary productivity (NPP), crop production (CP), and wind protection and sand fixation (WPSF) of Horqin Sandy Land in 2025 under uncertain land use to identify the short board areas of various services. The following results were obtained from the analysis. (1) The land use pattern of Horqin Sandy Land in 2025 under the HT scenario will be dominated by cultivated land expansion and grassland reduction. Under the NP scenario, forest will increase, and unused land and grassland will decrease considerably. Under the WS scenario, cultivated land will still maintain a similar growth state, but the difference is that forest and grassland will significantly increase. (2) NPP had the highest probability of being the Highest and the lowest probability of being Low, whereas CP and WPSF obtained the highest probability of being Medium and the lowest probability of being Higher. (3) Tuquan County and Wengniute Banner with a high probability of providing few ecosystem services should be regarded as key areas for ecological restoration. Kailu County and Horqin Left-wing Middle Banner can provide higher ecosystem services. The methodology adopted in this study establishes the connection between the land use probability surface and the optimized pattern of ecosystem services and can therefore be applied in areas where multi-objective comprehensive improvement of ecosystem services is expected.

Climate change adaptation impact on cash crop productivity and income in Punjab province of Pakistan.

Assessing the current farm-level efforts of climate change adaptation is essential to distinguish their usefulness and implying policy level advance measures for future. The present study investigated cotton farmers' climate change adaptation and its impact on increasing cotton productivity and net cotton income in Punjab province of Pakistan. A pretested and well-structured questionnaire was used for data collection of 480 cotton farmers from three major cotton-producing divisions of cotton-wheat zone of Punjab, Pakistan. Logistic regression analysis approach was used in this study to find out the factors of adaptation and propensity score matching method employed to identify connecting adaptation impact on cotton productivity and cotton income. Empirical estimates of this study indicated as owing to some external and internal constraint farmers were limited focused on adaptation while conscious about adverse effects of climate change. Usage of required and recommended types of fertilizer, variation in planting dates, and changing varieties of crop were main adaptation strategies implemented by cotton farmers. Cotton farmers' adaptation decision was significantly influenced by some major factors as weather forecasting, market information, easy access to agricultural extension services, farming experience, and education of cotton farmer. Farm-level increase in cotton productivity and net cotton crop income was direct while overall increases in national output and improving rural area farmer well-being were indirect and significant outcomes of implementing climate change adaptation of cotton farmers. Cotton farmers were using various combinations of adaptation strategies and achieving more benefits regarding their crop productivity and net returns. Findings of the study suggest need for larger investment in farm-level extension services, farmers' schooling, and develop climate change institutional setup for enhancing farmers' adaptation capability to increasing cotton productivity, improving well-being of farming community, and securing agriculture from future climatic uncertainties. Future policies must deal with farm-level limitations of advanced adaptation measures like making available information and sustaining sponsoring soil conservation practices, launching climate smart varieties and advanced adaptation measures based on various agro-ecological zones.

Predicting Crop yield and Effective use of Fertilizers using Machine Learning Techniques

In-season crop yield estimation has various applications such as the farmer taking corrective measures to increase the yield. We are exploring the efficient use of fertilizers. The various data mining techniques are used on data for environment. The data is related to humidity, PH. value, water, soil type and atmospheric pressure these are responsible for crop yield. This result is obtained by this algorithm are useful for farmers to take decisions about further implantation of crop yield. Crop selection method is widely used to build decision tree to overcome many problems in real time real world. One of the most important fields is decision tree. By analyzing the soil and atmosphere at particular region best crop in order to have more crop yield and the net crop yield can be predicted. This prediction will help the farmers to choose appropriate crops for their farm according to the soil type, temperature, humidity, water level, spacing depth, soil PH, season, fertilizer and months. This prediction can be carried out using Random Forest classification machine learning algorithm.